HETEROGENEOUS WIRELESS NETWORK USING NON …

HETEROGENEOUS WIRELESS NETWORK

USING NON-ORTHOGONAL MULTIPLE ACCESS

METHOD IN 5G FOR

SECRET COMMUNICATION

A thesis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy

in

Electronics and Communication Engineering

by

Pankaj Manubhai Patel

[139997111012]

Under the supervision of

Dr Chetan B Bhatt

GUJARAT TECHNOLOGICAL UNIVERSITY

AHMEDABAD

SEPTEMBER - 2021

copyPankaj Manubhai Patel

DECLARATION

I declare that the thesis entitled lsquoHeterogeneous Wireless Network using Non-

Orthogonal Multiple Access Method in 5G for Secret Communicationrsquo submitted

by me for the degree of Doctor of Philosophy is the record of research work carried out

by me during the period from January 2014 to November 2021 under the supervision

of Dr Chetan B Bhatt and this has not formed the basis for the award of any degree

diploma associateship fellowship titles in this or any other University or other

institution of higher learning

I further declare that the material obtained from other sources has been duly

acknowledged in the thesis I shall be solely responsible for any plagiarism or other

irregularities if noticed in the thesis

Signature of the Research Scholar Date 17092021

Name of Research Scholar Pankaj Manubhai Patel

Place Ahmedabad

CERTIFICATE

I certify that the work incorporated in the thesis lsquoHeterogeneous Wireless Network

using Non-Orthogonal Multiple Access Method in 5G for Secret Communicationrsquo

was submitted by Shri Pankaj Manubhai Patel was carried out by the candidate under

my supervisionguidance To the best of my knowledge (i) the candidate has not

submitted the same research work to any other institution for any degreediploma

Associateship Fellowship or other similar titles (ii) the thesis submitted is a record of

original research work done by the Research Scholar during the period of study under

my supervision and (iii) the thesis represents independent research work on the part of

the Research Scholar

Signature of Supervisor Date 17092021

Name of Supervisor Dr Chetan B Bhatt

Place Ahmedabad

Coursework Completion Certificate

This is to certify that Mr Pankaj Manubhai Patel enrolment No 139997111012 is a

PhD scholar enrolled in the PhD program in the branch Electronics and

communication Engineering of Gujarat Technological University Ahmedabad

(Please tick the relevant option(s))

HeShe has been exempted from the coursework (successfully completed during

the MPhil Course)

HeShe has been exempted from Research Methodology Course only

(successfully completed during the MPhil Course)

HeShe has successfully completed the PhD coursework for the partial

requirement for the award of PhD Degree His Her performance in the

coursework is as follows

Grade Obtained in Research Methodology

(PH001)

Grade Obtained in Self Study Course

(Core Subject)

(PH002)

BC BB

Supervisorrsquos Sign

Name of supervisor Dr Chetan B Bhat

Originality Report Certificate

It is certified that PhD Thesis titled lsquoHeterogeneous Wireless Network using Non-

Orthogonal Multiple Access Method in 5G for Secret Communicationrsquo by Shri

Pankaj Manubhai Patel has been examined by us We undertake the following

a The thesis has significant new workknowledge as compared to already

published or is under consideration to be published elsewhere No sentence

equation diagram table paragraph or section has been copied verbatim from

previous work unless it is placed under quotation marks and duly referenced

b The work presented is original and the own work of the author (ie There is no

plagiarism) No ideas processes results or words of others have been presented

as the Authors own work

c There is no fabrication of data or results which have been compiledanalyzed

d There is no falsification by manipulating research materials equipment or

processes or changing or omitting data or results such that the research is not

accurately represented in the research record

e The thesis has been checked using (copy of originality report attached) and found

within the limits as per GTU Plagiarism Policy and instructions issued from time

to time (ie Permitted similarity index lt=25)



Place Ahmedabad



Place Ahmedabad

132

Document Information

Analyzed document 20210915_Thesis all-Chdocx (D113152706)

Submitted 2021-09-22 091500

Submitted by

Submitter email pankaj4goggmailcom

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URL httpsarxivorgpdf160906261

Fetched 2021-09-22 0916001

Gujarat Technological University 20201220_ thesis_CH2docDocument 20201220_ thesis_CH2doc (D90785952)

Submitted by ap_rgandhigtueduin

Receiver radhikagandhigtunianalysisurkundcom

2


Fetched 2019-11-28 1244286

URL httpswwwresearchgatenetpublication342326303_On_the_Security_Enhancement_of_Up

link_NOMA_Systems_with_Jammer_Selection

Fetched 2020-11-03 060445

1

SODH PAPER FOR PLAGRIASMdocxDocument SODH PAPER FOR PLAGRIASMdocx (D47816804)

1

PhD THESIS Non-Exclusive License to


In consideration of being a PhD Research Scholar at GTU and in the interests of the

facilitation of research at GTU and elsewhere I Pankaj Manubhai Patel has Enrollment

No139997111012 hereby grants a non-exclusive royalty-free and perpetual license to

GTU on the following terms

a) GTU is permitted to archive reproduce and distribute my thesis in whole or in part

andor my abstract in whole or in part (referred to collectively as the ldquoWorkrdquo) anywhere

in the world for non-commercial purposes in all forms of media

b) GTU is permitted to authorize sub-lease sub-contract or procure any of the acts

mentioned in paragraph (a)

c) GTU is authorized to submit the Work at any National International Library under

the authority of their ldquoThesis Non-Exclusive Licenserdquo

d) The Universal Copyright Notice (copy) shall appear on all copies made under the authority

of this license e) I undertake to submit my thesis through my University to any Library

and Archives Any abstract submitted with the thesis will be considered to form part of

the thesis

f) I represent that my thesis is my original work does not infringe any rights of others

including privacy rights and that I have the right to make the grant conferred by this

nonexclusive license

g) If third party copyrighted material was included in my thesis for which under the terms

of the Copyright Act written permission from the copyright owners is required I have

obtained such permission from the copyright owners to do the acts mentioned in paragraph

(a) above for the full term of copyright protection

h) I retain copyright ownership and moral rights in my thesis and may deal with the

copyright in my thesis in any way consistent with the rights granted by me to my

university in this non-exclusive license

i) I further promise to inform any person to whom I may hereafter assign or license my

copyright in my thesis of the rights granted by me to my university in this non-exclusive

license

j) I am aware of and agree to accept the conditions and regulations of a PhD including

all policy matters related to authorship and plagiarism

Signature of the Research Scholar

Name of Research Scholar Pankaj Manubhai Patel Date 17092021

Place Ahmedabad

Signature of Supervisor

Name of Supervisor Dr Chetan B Bhatt Date 17092021

Place Ahmedabad

Seal

i

ABSTRACT

The landscape of future fifth-generation (5G) radio access networks is

expected to seamlessly and ubiquitously connect everything and

support higher traffic volumes densely connected wireless devices and

diversified requirements on reliability latency battery lifetime etc as

opposed to the current fourth-generation (4G) cellular networks

Moreover in unexpected or emergencies (such as disaster relief and

service recovery) the deployment of terrestrial infrastructures is

economically infeasible and challenging due to high operational

expenditure as well as sophisticated and volatile environments To

address such novel issues intelligent heterogeneous architecture by

leveraging unmanned aerial vehicles (UAVs) (or commonly known as

drones) has been considered to be a promising new paradigm To

improve the system performance of UAV communication in 5G

networks physical layer techniques are of much concern as they affect

the applications of UAVs significantly In this research work security

aspects of NOMA-based UAV communication network have been

considered for optimization as physical layer security in a wireless

communication network is not as robust as wired communication due to

fading and varying SNR scenarios Here primarily two usersrsquo models

as the trusted and untrusted user communicating with BS have been

optimized for outage-optimal performance considering pair Outage

probability and Secrecy outage probability as performance metrics The

achieved results are extended to multi-user scenarios also and for the

optimal policymaking dynamic programming and Partially Observable

Markov Decision Process (POMDP) optimization approaches have

ii

been simulated and verified The simulated results have shown that

POMDP has potential consideration as a resource scheduling

optimization technique in the NOMA-UAV communication network for

providing secure and more robust performance

iii

Acknowledgment

Completing a PhD is a tough task that requires hard work and a lot of effort This is

often an overwhelming but also great experience that I would not have been able to

complete without the assistance and support of so many people Thus it is my great

pleasure to thank all those people First of all I would like to thank almighty for giving

me the strength to carry out this task I would like to deeply thank Dr Chetan B Bhatt

my supervisor for his guidance encouragement and support over these years This

research work would not have been possible without his constructive pieces of advice his

systematic guidance and his patient support thought out the duration of my research work

I would like to express my sincere gratitude to Dr Harshal A ALOORKAR and Dr

KIRAN R TRIVEDI Dr Mehul Raval my doctoral progress committee members Their

rigorous style of reviewing and constructive feedback with valuable suggestions of Dr

Prakash Gajjar Mr Hitesh Panchal and Mrs Monali Mandli who spent their valuable

time whenever required for discussing aspects of this work and provided relevant material

as well Mr Parth Modi and Mr Jagadish Patankar to initiate and inspired me a lot to

continue my work Mr Mukesh Sharma who help in maintain documents I am also

thankful to my parents and family members who always stood with me in each critical

situation and supported me endlessly I am thankful to all EC departments of various

polytechnic and degree engineer colleges for their cooperation in every possible means

Lastly I would thank all the people who directly or indirectly helped me during this very

important phase of my life


vi

List of Abbreviation

3GPP 3rd Generation Partnership Project

5G Fifth Generation

A2G Air to Ground

AWGN Additive White Gaussian Noise

BDM Bit Division Multiplexing

BS Base Station

BPCU Bits Per Channel Use

CDMA Code Division Multiple Access

CR Cognitive Radio

CSI Channel State Information

CNPC Control and Non-Payload Communications

CRN Cognitive Radio Networks

D2D Device-to-Device

DCP Difference of Concave Programing

DOMP Dynamic Optimization Method of Programming

FR Floating Relay

GSM Global System for Mobile Communications

HLPSL High-Level Protocol Specification Language

ICT Information and Communication Technology

IoT Internet of Things

IRS Intelligent Reflecting Surface

IMT Information Management Technology

vi

LDS Low-Density Spreading

LTE Long Term Evolution

LTE-A Long Term Evolution Advance

MCR Multicast Cognitive Radio

MI Mobile Internet

MIMO Massive Multiple-Input Multiple-Output

mm-Wave millimeter Wave

MTC Machine-Type Communication

MUSA Multi-User Mutual Access

NOMA Non-Orthogonal Multiple Access

OFDMA Orthogonal Frequency Division Multiple Access

OMA Orthogonal Multiple Access

OP Outage Probability

POMDP Partially Observable Markov Decision Process

PLS Physical Layer Security

PDMA Pattern Division Multiplexing Control

PUN Primary User Networks

QoS Quality of Service

RIS Reconfigurable Intelligent Surface

RNRF Random Near-Random Far

Rs Target Secrecy Rate

SAGIN Space-Air-Ground Integrated Networks

SIC Successive Interference Cancellation

STBC Space-Time Block Coding

vi

SBF Secrecy Beam Forming

SCMA Sparse Code Multiple Access

SOP Secrecy Outage Probability

TAS Transmit Antenna Selection

TDMA Time Division Multiple Access

UAVC Unmanned Aerial Vehicle Communication

UMTS Universal Mobile Telecommunication Systems

URLLC Ultra-Reliable Low Latency Communication

vii

List of Figures

Figure Title Page

No

11 Usage of wireless sensor network and UAV in the

hazardous disaster control

6

12 UAV network applications types with security services

architecture

8

13 UAV-assisted heterogeneous network architecture 12

14 Security problems in the UAV 15

15 Comparative analysis of NOMA vrsquos OMA 18

21 Vehicular communication NOMA system 28

22 RS-NOMA against an external eavesdropper 31

31 Downlink NOMA network 44

32 Uplink NOMA network 46

33 Multi-two user architecture of NOMA system 49

34 Flow Diagram of the proposed system 50

35 Near and Far User 51

41 Impact on Sop with increase distance between BS and user U2 60


43 Feasible pairing t Vs pair OP 61

44 Infeasible pairing t Vs pair OP 62

45 Secrecy outage probability 63

46 Pair outage probability 63

47 SNR versus Strictly positive secrecy rate 64

48 Power radiated by per MMBs antenna 64

viii

List of Tables

Table Title Page

No

11 Physical layer hazards and measures in UAV wireless

communication network

13

21 Comparative analysis 33

31 List of parameters59 54

41 Simulation parameters 59

ix

Table of Content

Sr

No

Title Page

No

I Abstract I

II Acknowledgment II

III List of Abbreviation III

IV List of Figures Iv

V List of tables V

1 Introduction 1

11 Modern technology and its needs 1

111 Long term evolution of 4G network 2

112 Migration from 4G LTE to 5G for UAV communication 3

12 UAV assisted communication in heterogenous sensor network 5

121 Introduction to UAV Communication network 7

122 Tyews of UAVs 8

1221 UAVs as flying BSs 8

1222 UAVs as aerial UBs 10

13 Unmanned aerial vehicle for 5G network 11

14 Physical layer insecurity in UAV communication network 12

141 Principles of security 13

15 Non-Orthogonal Multiple Access (NOMA) system secured

communication

16

151 Comparison of NOMA Vs OMA 16

1511 Spectral throughput and efficiency 17

1512 User fairness and higher lately 17

1513 Compatibility 17

16 Problem identification 18

17 Motivation 19

18 Aim and objective of the research 20

19 Thesis organization 21

2 Literature review 23

x

21 Integration of UAV Networks for 5G and B5G communication 23

22 UAV-NOMA in physical layer security enhancement 26

23 Research methodology 38

24 Summary 39

3 System model for NOMA-UAV communication 41

31 NOMA -UAV system secured communication for 5G 41

311 The basic scheme of NOMA 41

312 Downlink of NOMA 44

313 Uplink of NOMA 46

314 Comparison of NOMA and OMA 47

32 PLS performance metrics in NOMA -UAV communication 47

321 SOP and OP - two user and multi-user NOMA system 48

322 System Model 48

323 Partially Observable Markov Decision Process-POMDP 50

324 Problem formulation 52

33 Performance Analysis Improving PLS Insecurity of NOMA

System

53

331 The pair OP calculation 53

332 Pseudo-code for the proposed algorithm 55

34 Summary 57

4 Result and discussion 58

41 Performance measure of secured NOMA-UAV communication

model

58

42 Numerical result and discussion 59

421 Feasible amp Infeasible pairing of trusted amp untrusted

users

60

422 The secrecy outage probability and pair outage

probability

62

423 SNR versus strictly positive secrecy rate 63

424 Power radiated by per MMBs antenna

64

43 Conclusion and scope of future work 65

431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION

11 Modern technology and its needs

Mobile technology has undergone various generational shifts transforming the

cellular framework into a worldwide set of interconnected networks In recent days

the fifth generation (5G) has delivered voice as well as video streaming It has a

very complex range of networking services for more than nine billion users and also

billions of devices that will be connected (Hu 2016) However 5G offers a new

outlet for reflection It involves a radial network architecture for the installation of

communication-type machines 5G network can also include powerful support

applications with widely varying operating parameters 5G is a blend of network

technologies that have been developed The new 5G technology will be able to

exchange information anywhere every time for the benefit of people enterprise

and society and technical environments using a restricted access bandwidth to

carry data Now it is more than a modern series of technologies and as opposed to

previous generations would entail tremendous infrastructure or machinery

upgrades This technology aims to expand on the advances that telecommunications

systems have already achieved The projected standards of efficiency that

technologies would need to resolve are

bull Five times reduce end-end latency

bull Ten to a hundred times the higher complex rate of user data

bull Battery life is ten times longer

bull 10 to 100 times higher number of connected devices

In this research work the UAV-assisted communication over the 5G network has

been proposed with enhanced physical layer security aspects NOMA has been

proposed as the reference framework architecture for UAV communication as one

of the recent popular 5G techniques Along with the advantage of suitability in UAV

communication network NOMA has the disadvantage of insecurity in the physical

layer Here the migration of Long Term Evolution (LTE) to advanced physical layer

2

security for Unmanned Aerial Vehicle communication (UAV) over 5G network has

been proposed and also improve the insecurity of Non-Orthogonal Multiple Access

(NOMA) System We will discuss in the further chapter the proposed work This

chapter describes the introduction and basic concepts of the 5G networks with

methodology techniques and types It states the problem identification motivation

and further aim and objective of this work

111 Long Term Evolution of 4G Network

LTE is customary for 4G wireless broadband trends that provide improved network

capability and gives mobile device users speed It offers high peak data transform

rates in the range of 100 Mbps and 30 Mbps downstream and upstream

respectively It provides a capacity of scalable bandwidth mitigated latency and

backward compatibility with the previous Global System for Mobile

Communications (GSM) and Universal Mobile Telecommunication Systems

(UMTS) technology

The fourth development of cellular networks (4G) has already been developed to

meet the standards of the 3G and 2G families Every 10th year a new mobile

generation claimed to be familiarized with the first 1G system in 1981 tracked by

the 2G system that went on to roll out in 1992 and 3G launched in 2001 growth in

the year 2002 of 4G networks The actual new revolution began in December 1998

with the 3rd Generation Partnership Project (3GPP) With high-quality video and

images 3G networks are designed for multimedia networking with them Peoples

communication can also be enhanced and connectivity to public and private

network information and resources has improved with higher frequencies and new

flexible communication features third-party device applications

With the start of LTE-Advanced several vital demands and improvements are

beginning to emerge Various importance purposed for LTE-Advanced can be

exemplified as follows (Abed)

bull Provides spectrum output with LTE delivered more than three times

bull Spectrum can help scalable bandwidth and convergence of the spectrum

where it is necessary to use a non-contiguous range

3

bull Provides uplink and downlink spectrum output that varies between

15bpsHz and 30bpsHz

bull The edge throughput must be twice that of the user cell in LTE

bull From idle status to connected status the communication latency scenario is

smaller than 50msec and less than 5msec for direct packet transfer

bull Any users total throughput must be three times that of LTE

bull LTE advancement will provide 3GPP as well as LTE compatibility via inter

networking

bull The mobility conditions that are used in LTE are identical

The latest LTE advanced requirements are not yet included in device

specifications there are high-level purposes Before it is fixed in the specifications

and needs to be tested much effort remains to be approved

112 Migration from 4G LTE to 5G for UAV communication

The productive implementation of a UAV communication network in 4G and the

upcoming wireless network is included in identifying combined solutions to test

the correlation with both multitudes and also energy-efficient transmission Then

the process of the UAV-BS to optimize coverage and power It is stated that the

energy efficiency of the UAV-aided communication system is needed Efficient

energy utilization contributes to increased air time in the contact system and

increased joulesbits at a provided energy level Also aerial cell coverage and

ability may be because of various parameters such as antenna gains transmission

strength radio access technology UAV altitude and deployment environment

4G is the fourth generation of network infrastructure technologies to replace 3G and

in addition to the popular 3G4G methods Code Division Multiple Access

(CDMA) Time Division Multiple Access (TDMA) and Orthogonal Frequency

Division Multiple Access (OFDMA) Researchers are designing the latest Non-

Orthogonal Multiple Access (NOMA) technologies to be used because of their

capability to improve the performance of communication networks Non-

4

orthogonality-based device designs have recently been developed for use in

communication networks and drawn considerable interest from researchers

Henceforth Multiple Access (MA) methods can be sub-divided as OMA and

NOMA Each user may utilize orthogonal communication resources to determine

multiple access interference inside a frequency band code and time slot in OMA

Its methods such as First generation (1G)- FDMA 2G -TDMA 3G -CDMA and

4G - OFDMA have been used in previous network generations In NOMA by

producing a higher spectral efficiency however enabling some amount of multiple

entree intrusion in receivers and multiple users may use non-orthogonal resources

simultaneously Recently the credibility of NOMA as a solution to the problems of

the next generation of wireless networks has been increased Compared with OMA

technologies NOMA has been described to improve spectral quality be well-

adjusted with air connectivity and can provide accommodations for multiple

strategies at the same time of frequency Therefore enabling excellent progress to

massively correlated devices

In particular NOMA also affects mitigating interference by using OFDMA as an

orthogonal method or through offering a standard intra-cluster access beam across

multiple users and inter-cluster access in NOMA Recent studies have concentrated

primarily on the provision of Air to Ground (A2G) connectivity services through

optimization of a different point of view

The output of the UAV-based communication network was discussed in the Device

to Device (D2D) implementation setup The proposed system hypothesized

interference caused through D2D network nodes deprived of acknowledging the

occurrence of global BS Also several studies addressed the efficiency of NOMA

It permitted the deployment of fixed-wing to assist coverage in-ground user located

outer location of offloaded BS

NOMA systems are divided into two categories namely code domain and power

domain multiplexing In the power domain user accounts are allocated to different

power coefficients as per their channel complaint to reach optimal device

efficiency Multiple user signals are applied to the side of the sender Then on the

received signal Successive Interference Cancellation (SIC) is implemented to

decipher signals in sequential order until the predicted signal is achieved offering

5

a good trade-off between efficiency of the system and user fairness Different code

domain multiplexing is Sparse Code Multiple Access (SCMA) Low-Density

Spreading (LDS) and Multi-User Mutual Access (MUSA) Compared to power and

code domain multiplexing there are alternate NOMA techniques such as Bit

Division Multiplexing (BDM) and Pattern Division Multiplexing Control (PDMA)

However this multiplexing is capable of improving the efficacy of spectral It

requires a large transfer of bandwidth which is not appropriate for new methods

But on the other side the power domain has direct execution since there is no need

for significant improvements to the current networks It also does not necessitate

bandwidth to increase spectral efficiency In this chapter the main emphasis

depends on the power domain NOMA While OMA strategies can produce the best

results also with necessary receivers due to no mutual intervention among users in

an optimal situation they cannot even resolve increasing problems due to growing

demands on connectivity growth and even beyond

12 UAV assisted communication in heterogeneous sensor network

Wireless communications had created a golden chance for urban and rural

territories The LTE (Long term evolution) and LTE-A (Long term evolution

Advance) had offered the service (with QoS) for all customers through wireless

The traffic properties in the machine type communications (MTC) and the

accumulation of the MI (Mobile Internet) had made the difficulty of implementing

the cellular communication networks Installing base stations was impractical in the

urban areas due to its cost To overcome this issue the UAV suggested that it

contains the merits of compatibility and high battery life and is affordable Most of

the devices like the sensor nodes and professional cameras had been used in UAV-

assisted networks Here the UAV-assisted floating relay (FR) was launched in the

cellular communication networks UAVs were implemented more with WSN

(wireless sensor networks) The base stations were adopted with the UAV So the

MI and MTC traffic challenges were controlled (Yue Li amp Cai 2017)

UAV-assisted Heterogeneous networks had implemented in vast practical

applications UAV helped heterogeneous networks were applied in the military

department In the military the UAV had examined and surveyed the opposing

6

countryrsquos activities for security The UAV-based heterogeneous networks were

used in the military sectors where a novel authentication scheme was introduced

As The one-to-one communication via WSN was considered as secured

communication WSN had the disadvantage of consuming power The

authentication was implemented in the tool of Automated Validation

of Internet Security Protocols and Applications (AVISPA) in which the expression

had been written in the High-Level Protocol Specification Language (HLPSL)

programming language The authentication had evaluated between the user and the

base station Similarly the authentication between the user and the UAV was

calibrated The citizen and economic safety are predicted and conserved through

reliable communication in the military by obtaining foes exploration information

The faithful secured communication was confirmed using AVISPA (Rashid et al

2019)

Figure 11 Usage of wireless sensor network and UAV in the hazardous

disaster control

The integration of the wireless sensor networks and the unmanned aerial vehicle

UAV was analyzed and applied to manage the natural disaster illustrated in Figure

11 The aircraft can prevent the fire spreading drop sensors the temperature map

and biodiversity map by sensors the wildfire can easily route The wild animals can

7

be tracked and the dynamic data of moving animals can be gathered by WSNs The

biologists can fix the sensor in the animals collar the radiation that positively

affects humans can be observed in affected areas The WSNs help to prevent heart

attack of a person by monitoring heart rate The state of health can be known

through a message alarm using a GPRS system

The cooperative networks of WSN and UAV were implemented in the military

sector for the advantageous feature The UAV was providing good connections

overlapping and overall data rate The conventional UAV method aided sensor

networks concentrated only on the single tasks of monitoring accumulating

information and localization The multi-UAV had not been implemented in the

sensor networks The animal colony perception technique was utilized for

scheduling the resourced and the target assignment Functions of multi-data were

used for localization by the target recognition method (Gu Su et al 2018)

The Physical Layer Security (PLS) was achieved through 5G technologies delicate

coding for the PLS dense MIMO multi-input multi-output mm-Wave frequency

band using heterogeneous sensor networks NOMA and full-duplex mode of

communication IoT and Machine-type communications (MTC) emerged in the 5G

systems (Wu et al 2018)

121 Introduction to UAV communication network

The usage of the UAV will develop more in the next era These pre-programmed

aircraft are intended for applications in several civil settings as well as industrial

visualization agriculture rescue and search and then receiving of scientific data

These devices are called the unsuccessful inaccuracy of drones which must be

incorporated into the system of national airspace as well as worldwide The usage

of UAVs in the neutral form is always secure It has a direct inference for the control

and a payload communication system that is utilized to function effectively

Similarly surveillance and navigation operations must be made more accurate and

consistent Due to these critical factors many kinds of research in a UAV testing

development and standardization difficulties are undergone through industries

education and governments

8

Even though civil aircraft had been operating for many years yet UAV offers new

consequences in terms of various flight profiles For example high dynamic

maneuvers and low elevation flights need bandwidth video and different ground

site characteristics namely clutter locations and elevation antennas which are low

This chapter explains the core topic of the proposed work The migration of LTE

4G towards the advanced one of the physical layers for UAV communication It has

higher mobility and lower expense identified in a broad range of applications

122 Types of UAVs

The UAVs have a two-network application with security services such as UAVs as

Flying Base Stations (BSs) and UAVs as Aerial BSs in the presence of

eavesdroppers

(a) UAVs as Flying BSs (b) UAVs as Aerial mobile UEs

Figure 12 UAV network applications types with security services

architecture

1221 UAVs as flying BSs

The required infrastructure can be destroyed in natural disasters particularly

tsunamis earthquakes and snowstorms and the requisite emergency data traffic

cause both overloading and congestion of neighboring mm-Wave (Zeng et al

2016) A capable explanation is to rapidly introduce low-altitude UAVs as flying

9

BSs in such a network breakdown to improve the communication infrastructure to

mitigate cell congestion or site failure thus creating a small aerial cell

In this situation wireless communications can occur in an ad-hoc manner with

UAVs to UEs UAVs to UAVs As highlighted in Figure-12 (a) and control

stations of UAVs to ground It will increase capability dramatically and enlarge the

target of wireless networks in provisional measures as it is possible to create LoS

communication links among UAVs and UEs supported on the ground Yet form an

operating aerial cell system to monitor ground segments of UEs mobility which is

more stable to minimize sporadic connectivity on the other side

Also this can be expanded to allow several UAVs-BSs to be deployed to increase

the exposure area for supporting a wide range of UEs A network period various

UAVs-BSs is entirely independent A new paradigm was introduced through

collaboration between UAVs-BSs to extend the feasibility for a single UAV from

either a stand-alone active sensor to a wireless network over the next generation

There is a growing concern about the privacy problem in tandem with the brief

introduction of this network Wireless protection is the central issue of the

communication level wherever eavesdropping subsidizes for deliberately listening

to a source of secret information which harms the extensive placement of UAV-

BSs

A UAV-BSs is to mount several antennas in the UAV-BSs the benefits of multi-

antenna innovations geographical degree of freedom that offers an ability for UAV-

BSs to transmit eavesdropping airborne beams

Notice that in UAV systems multi-antenna technology can be technically applied

while directly modifying the separation of the antennas The existing system has

shown that transmitted beam forming models can significantly boost the

confidentiality efficiency of wiretap channels for multiple antenna transmitters

Noise may be inserted with the signal to substantially degrade the acknowledged

SINR at the eavesdroppers to prevent the information overflow

10

1222 UAVs as aerial UEs

This has already been demonstrated by reaping the benefits of Wi-Fi and LTE

technologies through field trials (Van der Bergh et al 2016) UAV-UEs typically

get their tasks for a variety of convincing IoT applications mainly in air freight

services like the google wing project Unlike conventional land base package

delivery but UAV delivery has distinctive merits such as

bull Acceleration of land transport as UAVs are not liable to road jams

bull Connection to areas that are difficult to reach

bull Decreasing the use of capital about workforce and electricity

UAV distribution is significantly dependent on having reliable and secure wireless

communication among UAVs and ground BSs especially if the UAV needs control

outside LoS the UAV-UEs are used which can develop LoS connectivity to cellular

BSs The UAV-UEs on the one hand provides high-speed access to data as it can

fly continuously in either direction On the other hand the installation of UAV-UEs

can lead to significant interference with the ground BSs in the execution of their

missions

A wide-scale installation of UAV-UEs is only feasible for this reason if the issues

of interference management are tackled It is widely known that interference

negatively affects wireless networks As highlighted in Figure-12 (b) indeed aerial

and ground UEs are served through a cellular network with a possible eavesdropper

that tries to intercept the message intended for permissible basic UEs

A cost-effective approach is to be used for coordination among ground BS and

UAVs to enhance secure transmission which is part of the UAVs acting as friendly

transmitters to degrade the wiretapping channels efficiency and thus enhance

secrecy efficiency A UAV acting as a mobile jammer can dramatically and

dynamically change its position as near as possible to the earth eavesdropper and

distribute them by sending the radio signals whereas strong LOS connection

characteristics are a beneficial feature with less earthly fading and shadowing

impairment

11

13 Unmanned Aerial Vehicle for 5G Networks

UAVs have technologically advanced as a revolutionary movement in delivering

pervasive connectivity from either the platforms of the sky as aerial

communication particularly for temporary User Equipment (UEs) (B Li et al

2019) Due to fully controllable UAV flexibility through miniaturization as well as

continuous cost reduction low-altitude UAVs are rapid and flexible designed for

operation and reconfiguration They are probable to have higher Line-of-Sight

(LoS) ties to ground UEs

A broad range of applications like inspection of infrastructure precision farming

and disaster area monitoring is becoming accessible in this aspect Moreover

further projects have also been set up to employ aerial platforms for broadband

access to distant elements such as the Google Loon and the Facebook Drone Project

to mention Highly populated UEs are desperate for broadband wireless

communications with the coming 5G period and network providers are supposed

to maintain numerous networks with high demands for wireless data like

multimedia streaming and also video downloads The relentless growth in the

amount of traffic of mobile networks puts a burden on operators in the form of

higher capital and operational expenditure Deploying small cell networks is an

intuitive alternative to outsource cellular traffic

Although in unforeseen or temporary events as mobile environments are

complicated volatile and heterogeneous the implementation of terrestrial

infrastructures is difficult The accessibility of aerial access points to enable

extensive complex connections is one possible solution However in unforeseen or

temporary events as mobile environments are complicated volatile and

heterogeneous the implementation of terrestrial infrastructures is difficult The

accessibility of aerial access points to enable extensive complex connections is one

possible solution UAV communication performance benefits from the simplicity

of the compact transceiver and progressive control methods that obtain broad

exposure and set up internet networks

12

Figure 13 UAV-assisted heterogeneous network architecture

The above Figure 13 is depicted to build flexibility of the network with enhanced

ability and elasticity It is a good network that offers security endowment This is

due to the transmitting information to UAV communication which is tapped

through ground unauthorized user and is known as an eavesdropper

Here through eavesdropper based on the upper layer cryptographic techniques

wireless communication in contradiction of unauthorized access has been protected

However it is very tough to achieve because of key management as well as more

computational difficulties in developing network architecture PLS affects the

characteristics of intrinsic wireless networks as a fascinating preparation such as

interference noise fading loss collecting signal characteristics in malicious

eavesdroppers and techniques of signal processing

14 Physical Layer Insecurity in UAV communication network

Jamming is either a well-defined WSN attack on a physical layer It disrupts the

radio waves being used by nodes of the network The attacker successively

expresses the denial of the simple MAC protocol over the wireless network The

impressive network can be disrupted at which a single frequency is being used

13

throughout a network (Modares et al 2011) In addition jamming can increase

energy consumption in the node by inserting impudent packets The receiver nodes

will also generate resources when receiving the packets In (Jeon 2006) four

different terms of jamming attacks that an intruder could use to interrupt the

wireless network activity Tampering is yet another physical layer assault

Table 11 Physical layer hazards and measures in UAV wireless


(Kumar et al 2014)

Hazard Security measures

Jamming Channel blacklisting and hopping

Interference Channel hopping and blacklisting

Tampering Security and key modification

Sybil Physical security of the system

Table 11 describes physical layer hazards and their security measures in WSN

which tampering and jamming are considered as the main attack in the physical

layer in WSN

141 Principles of security

The security requirement of UAV communication network is as follows (Kumar et

al 2014)

Confidentiality Ensure that only the approved sensor nodes could get the contents

of the texts

bull Authentication Ensure that the data is introduced from the sound source

bull Integrity Ensure that every received text has not been modified to be sent

by unauthorized users

14

bull Freshness Make confirm that no old information has been reiterated

bull Availability services are feasible at any time through WSN or by a single

node

The standard attacks of the physical layer are as follows (Sastry et al

2013)

bull Jamming The transmission of the radio signal can interfere only with radio

frequencies used through WSN which is known as jamming As the

capacity grows it may influence more significant portions of the network

by transmitting other radio signals The opponent will use a few nodes to

occupy the entire channel This state is called physical layer jamming which

results in a denial of service In this scenario the opponent will not be

permitted to have any knowledge but will be capable of preventing

communication to any nodes

bull Tampering Often the nodes tampered through an opponent This mode is

called tempering Here the attackers can destroy exchange and

electronically confront nodes to obtain information from counter measures

towards jamming that have been planned as spread as well as frequency

hopping

bull A security mechanism is used in WSN to track avoid and recover from

security attacks A wide range of security schemes can be devised to counter

malicious threats which can be classified as high and low levels

bull Secrecy and Authentication Most network sensor applications need

protection from eavesdropping packet alteration and injection Early

networks are used for connection layer cryptography as this approach offers

the easiest deployment of network cryptographic solutions

bull Privacy Like all other conventional networks the radio networks have also

brought secret issues to allow Initially sensor networks are implemented

for legitimate purposes and can eventually be used unexpectedly

Knowledge of active sensor nodes as well as the acquisition of data is

exceptionally crucial

15

bull Critical launch and trust setup The primary prerequisite for setting up a

network is the development of keys (cryptography) Sensor devices

typically have minimal computing capacity and public cryptographic

primitives are too difficult to adopt Critical establishment and strategies

need to be scaled to network with thousands of nodes

bull Secure routing Routing as well as data forwarding is a problem that

confronts to facilitate communication in networks Regrettably the latest

protocols encounter a variety of security flaws

bull Robustness of communication Does An opponent challenges to interrupt

the operation of the network

Figure 14 Security problems in the UAV

Figure 14 illustrated the security difficulties in a UAV The physical layer security

in the UAV wireless networks was examined The UAV had affected by both active

eavesdropper and passive eavesdropper This paper proposed the trajectory design

and cooperative UAV for constraining the eavesdropper NOMA MIMO mm-

Wave frequency band in UAV would cause better spectral efficiency and security

(Xiaofang Sun et al 2019)

UAV implementation of the 5G communication was considered advantageous The

UAV was assumed as the novel wireless network technique for the territory users

and their base stations The UAV had resulted in high altitude So the UAV had

16

considered a superior line of sight At the same time the possibility of security

problems was raised in a UAV The secrecy in the existence of eavesdropper the

jammer in the ground was performed using the UAV UAV aided territory security

was proposed The UAV was involved in inspecting the eavesdropper and hazard

jammers on the base stations territory UAV had targeted the global position system

spoofing for assisting the authentic users and performed the role of an artificial

eavesdropper for excluding the eavesdropper and jammers in the ground (H-M

Wang et al 2019)

15 Non-Orthogonal Multiple Access (NOMA) System Secured

Communication

NOMA is visualized as a hypothetically capable method for addressing some

dangerous tasks in the 5G networks namely massive connectivity and spectral

efficiency (He et al 2017) Two leading NOMA solutions which are channel

estimation multiplexing and code domain multiplexing have been recommended

for future networks Various users are assigned different power levels as per their

channel conditions with power domain multiplexing and the consecutive

cancellation of interference is being used to cancel multiuser interference Here the

different users are allocated other systems for code domain multiplexing eg space

code multiple access and then combined with the same frequency resources

NOMA output with organized users was examined in (Ding et al 2014) From an

equality standpoint the layout question of the NOMA method was discussed in

(Timotheou amp Krikidis 2015) To boost machine reliability cooperative NOMA

schemes were explored (Choi 2014) Multiple-Input Multiple-Output (MIMO)

techniques were made known to systems of NOMA in (Choi 2015) that provide

additional spatial flexibility

151 Comparison of NOMA Vs OMA

Comparison of the NOMA and OMA can be discussed as follows

17

1511 Spectral throughput and efficiency

In OMA a resource is allotted to the distinct user whether it is good or bad in a

channel scenario like OFDMA Thus the whole process moves from less

throughput and performance

While the same frequency is allotted to the multiple-use at the same time with good

or bad channel operation in NOMA here the weak user gets the allocated for the

resources which the strong user can also use it And the interference can be reduced

by the SIC process on the receptor side of the user Consequently the probability

with the increased spectral efficiency as well the high throughput will be

maximized

1512 User fairness and higher lately

A user of fair channel complaints has higher precedence to be served in OMA In

contrast a user with a poor channel complaint is to remain activity which causes

the issue of user fairness and higher latency Yet OMA cannot assist colossal

connectivity Whereas NOMA helps multiple users with various channel

procedures and offers increased fairness massive connectivity and lower latency

1513 Compatibility

NOMA has compatibility with the current and upcoming scenario meanwhile no

need for necessary changes to the previous methods As an instance NOMA has

been bought up in the 3G Partnership Project LTE Advanced (3GPP LTE) Though

NOMA contains many characteristics that can assist the upcoming generations and

it has some restrictions that can be explored with its full benefits Those restrictions

are as follows

bull Each user has to decrypt the signals of other users until decrypted their

signal the complexity of the receiver would be strengthened in NOMA as

opposed to OMA which creates a long pause

bull Also data on channel quality for all users should be returned to the BS but

this results in substantial CSI input overhead Furthermore if any issues

arise to any consumer during the SIC process the likelihood of consecutive

decrypting errors will be improved

18

Figure 15 Comparative analysis of NOMA vrsquos OMA

As an outcome the number of users is reduced to ignore the spread of such

debugging Another aim of restricting the number of users is that there must be

substantial variations in channel revenues between users with different channel

grievances to provide network reliability

16 Problem Identification

The NOMA-based architectures main feature is to configure trusted and untrusted

users when more than one eavesdropper is present in the dense setting of todayrsquos

and future sophisticated wireless communication networks This research aims to

examine the security efficiency suggested for mission-critical applications in the

NOMA-based UAV communication network The proposed system underpins two

user NOMA frameworks The possibility of paring both users was explored with

PHY performance measures in mind Outage probability (OP) and Secrecy Outage

Probability (SOP) Dynamic Optimization Method Programming (DP) and Partially

Observable Markov Decision Process (POMDP) optimization have also been

analyzed to explore the feasibility of achieving an outage-optimal output for the

pair under the heavy users secrecy outage restriction The optimized theoretical

findings are applied to the multiuser scenario The identifications were tested

through a computer model in which POMDP has shown substantial progress over

the dynamic optimization method to program

19

17 Motivation

Unmanned aerial vehicle (UAV) wireless communications have experienced an

upsurge of interest in both military and civilian applications due to its high

mobility low cost on-demand deployment and inherent line-of-sight air-to-ground

channels However these benefits also make UAV wireless communication

systems vulnerable to malicious eavesdropping attacks

Despite the promising gains brought by UAVs the open nature of air-to-ground

wireless channels makes secure information transfer a challenging issue

specifically on the one hand information signals transmitted over wireless LoS

channels are likely to be intercepted by some undesired receivers which lead to a

risk of information leakage On the other hand wireless UAV transceivers are

vulnerable to malicious jamming attacks Hence security plays an extremely

important role in UAV wireless communications Unfortunately traditional

encryption techniques require high computational complexity leading to a large

amount of energy consumption which may not be suitable for UAV systems As an

alternative physical layer security is computationally efficient and effective in

safeguarding wireless communication networks via exploiting the inherent

randomness of wireless channels As a result various physical layer techniques

have been proposed in the literature for guaranteeing communication security

NOMA is viewed as a promising technique to provide superior spectral efficiency

by multiplexing information signals at different power levels [13] Hence it is

expected that NOMA can bring additional rate and robustness to enhance the

achievable rate in UAV physical layer security communications Consider a

scenario where a UAV acts as a relay to facilitate data delivery to two receivers

with different security clearance levels within a maximum cruising duration T The

receiver with a lower security clearance level and a higher potential with an

eavesdropper Since it has a strong motivation in intercepting signals intended for

a receiver with a higher security clearance Then when the eavesdropper suffers

from a bad channel condition NOMA is adopted to forward both confidential and

public information simultaneously Otherwise UAV only broadcasts the public

information for security issues The mode selection between NOMA and unicast is

20

chosen based on the results of the proposed resource allocation optimization In

particular for maximizing the spectral efficiency one needs to jointly optimize the

transmission scheme resource allocation and UAVrsquos trajectory However the

coupled optimization variables generally result in non-convex optimization

problems which are difficult to solve optimally As an alternative an iterative

suboptimal algorithm based on successive convex approximation can be employed

to facilitate a computationally efficient joint design We have discussed that the

NOMA scheme always outperforms OMA in all the considered scenarios which

demonstrates the spectral efficiency advantage brought by NOMA in striking a

balance between public data rate and confidential data rate

The main motive of this research is to enhance the inherently insecure PHY layer

of the NOMA-based UAV communication network NOMA-UAV communication

network requires feasible paring between trusted amp untrusted users (attacker) for

cooperative communication mainly in real-time field applications The power

allocation factor need to be optimized as per the trustworthiness of the associated

users (reliable user) and keeping the outage probability minimum for secured and

cooperative communications The pair Outage Probability and the SOP have been

optimized jointly for feasible pairing between BS amp the associated Users

18 Aim and Objective of the Research

The proposed works main objective is to examine the design of a NOMA-based

UAV communication network for enhanced Physical Layer security (PLS)

features Remarkably it is anticipated infrastructures and resources to connect

numerous devices and provide various services Researchers these days

concentrating on ways to design a heterogeneous framework like deployed small

cells air and ground-based deploy multifarious communication methods in 5G

such as millimeter-wave (mm-Wave) device-to-device (D2D) massive multiple-

input multiple-output (MIMO) Cognitive Radio (CR) and so on for improving

spectrum and energy efficiency

As a critical need especially for emergency applications the adoption of NOMA

transmission of UAV communication needs to be improved PLS A new optimal

resource allocation algorithm for some more robust and stable communication in

21

single and multiuser scenarios has been suggested here The PLS in dense

heterogeneous sensor networks has improved by the feasible pairing of trusted and

untrusted users (K Cao 2019 T Zhao 2018) In the instance of untrusted users

dynamic programming and POMDP are subjected to the channel conditions

details optimizing OP and SOP as a restricted parameter accompanied by resource

allocation (Davis 2018 L Hou 2018)

The main aim of the proposed research work areas

bull To analyze the underlying NOMA UAV communication framework with

enhanced Physical Layer security (PLS) implications for particular quest

applications

bull To examine the potential pairing of trusted and untrusted users in the

NOMA-based UAV contact network with two users and multiuser scenarios

for certain channel conditions called Channel State Information (CSI)

bull To maximize resource allocation among trusted and untrusted users by

pairing OP and Secret Outage Probability (SOP) as performance measures

with the POMDP optimization method

bull To evaluate POMDP and dynamic programming resource allocation with

two users and multiple users for both protected NOMA-based UAV

communication network scenarios

19 Thesis Organization

Chapter 1 Provides the introduction and basic concept of the proposed work with

the problem identification motivation and aim and objective of the proposed work

Here we described LTE 4G and its advanced techniques than about the NOMA and

its basic scheme UAV concepts represent their types and basic working strategy

Chapter 2 Provides a survey of the existing technologies which is related to the

proposed work The NOMA transmission schemes Merits and De-merits related

to security UAV assisted communication in heterogeneous sensor networks UAV

networks of 5G and beyond communications has been explained then about UAV-

NOMA PHY secured communication techniques as well

22

Chapter 3 Describes the proposed work of improvement of physical layer

insecurity of the NOMA The overflow and its performance measures with

simulated output have been defined in this chapter

Chapter 4 Describes Migrations proposed work from 4G LTE to advanced PHY

techniques for UAV communication The overflow and its performance measures

with simulated output have been explained in this chapter Concludes and explains

the proposed work with its outcome and the future scope of the proposed work

23

CHAPTER 2

LITERATURE REVIEW

21 Integration of UAV Networks for 5G and B5G communication

5G and B5G had been anticipated to give a unique connection among universal

users The UAV had been emerged for its advantage of wireless network and

relaying high data rate The UAV in the 5G and B5G was introduced and 5G and

B5G were updated with the new concept of Space-Air-Ground Integrated Networks

(SAGIN) Three layers were established named physical network communication

link and evaluation Besides the usage among the dense population IoT was

applied in satellite communication In which the IoT had provided the uninterrupted

service with high data rate communication The scope for flying UAVs had been

created for enhancing the number of mobile users with IoT (Ali et al 2018)

5G and B5G had projected the UAV as the vital constituent One to multiple point

transmission can be possibly advance in 5G and B5G The structural design of the

upcoming UAV (multi-tier drones) was driven by the routine of different structures

like the maximum functioning altitude communication overlap coverage and

determination The UAVs practicability (multi-tier drones) among conventional

UAVs (single-tier drones) is scrutinized in that perspective By ascertaining the

circumstances UAV (multi-tier drones) could supplement the older terrestrial

networks with RF Initially UAV (multi-tier drones) and drone-aided wireless

networks were related to finding the tasks The modified UAV (multi-tier drones)

and the drone-administered wireless networks were analyzed The enactments of

UAV (multi-tier drones) were scrutinized in the contest of spectral efficiency in the

downlink networks Their effect had exhibited the detailed network parameters The

UAV distribution (multi-tier drones) was considered advantageous for the spectral

efficiency from the downlink transmission over traditional terrestrial wireless

networks (Sekander et al 2018)

The growth of 5G and B5G wireless networks prominently hang on the

incorporation of the terrestrial and aerial systems in innovative heterogeneous

network architecture They had advanced a creative and tangible multiple UAV

24

made up of cluster UAV ndash base stations and Poisson point process with UAV and

mm-Wave frequency band Ground user equipment and UAV had exhibited as the

Poisson cluster process and then spread around the public cluster in the distinctive

cluster In particular the scrutiny was accompanied by the accumulation of extra

tiers Extra tiers were made up of multi-cluster UAV base stations and single ground

user base stations in the characteristic cluster Four-tier network systems were

designed correspondingly from the subdivision of the above-said base stations

Two-tier and four-tier association patterns were built for discovering the

involvement of the cluster networks The coverage probability for the downlink and

network throughput was derived (Ji et al 2020) The numerous subordinate title

role of the multifaceted communication systems was performed by the UAVs The

UAV was acted as the air relay in the maintenance of ground networks The UAVs

were used in the countryside hilly zones whereas the communication was

inadequate The author anticipated resolving the viable communication difficulty in

5G and B5G vehicular ad-hoc The associate communication pattern established on

the smart UAVs was planned given the crisis condition of the car ad-hoc The smart

UAVs were supporting the vehicular ad-hoc strong communication in real

situations Above and beyond its actual characteristics of the vehicular ad-hoc were

needed to be endangered to avoid the prohibited features from attaining and

exhausting for law-breaking practices Innovative UAV with a secret authentication

key arrangement was recommended in the 5G and B5G vehicular ad-hoc Because

of supporting efficiency the vehicle network which guaranteed communication

confidentiality was not negotiated The suggested pattern was confirmed to be

unaffected by numerous outbreaks by exploiting the broadly applied natural or

random ROR scheme

Furthermore the projected scheme had well calibrated the communication

overhead from the performance estimation (J Zhang et al 2020) The UANs had

obtained a phenomenal role in the research area the emergent sector of aerial

robotics The parcel transport organization monitoring occurrence shooting

surveillance and tracing were the metropolises general operations utilizing the

UAV Various domains would use 5G and B5G to improve UAV networks UAV

ecological unit was advantageous in present 5G and B5G mobile communications

For UAVs intrinsic features they were concerned for flexible movement of three-

25

dimensional space independent actions and smart locations These devices were

provided with extensive scope in cellular networks The author proposed an in-

depth assessment of implementing cooperation between UAV and 5G and B5G In

which UAV had been assimilated as a novel user equipment of aerial in present

mobile communications The UAV had implemented the duty of flying users within

the network coverage named the cellular-connected UAVs in this amalgamation

The author showed a broad examination of the incorporation tasks with 5G and

B5G novelties Continued efforts in the prototyping and validation of mobile

communication UAVs were conducted using the ground trial The paper had

focused on the current growth in 3GPP The social-economic had not been taken

into account which was considered disadvantageous (Mishra amp Natalizio 2020)

The UAV was anticipated as the significant constituent in the 5G and B5G wireless

networks 5G enables the UAV to be used in broadcasting and end-to-end

communications using the small UAV They needed a devoted and endangered

aerial spectrum in the aircraft cargo by letting small UAVs run in space in

supervisory authority The security information was obtained from the link Control

and Non-Payload Communications (CNPC) The security information contained

the regulation of UAV and the line of sight of terrestrial The CNPC application in

the 5G and satellite communication was scrutinized in this paper Payload

communication like mm-Wave networks and UAV were analyzed in this paper The

direction-finding and reconnaissance difficulties were examined UAV

communication systems were scrutinized and the hardware challenges were

discussed (Hosseini et al 2019)

The potential gain from the UAV-assisted data gathering was found in

indiscriminate IoTs The characteristic propagation was represented by utilizing the

complicated channel method (contained small- and large-scale fading) IoTs were

updated in constrain of transmit power (in high) and total energy The multi-antenna

UAV was selected in the IoTs in sequence The virtual MIMO was created by the

communication between UAV and singe antenna IoT in every transmission (W

Feng et al 2018)

The UAV was applied in the aerial coverage surveillance agricultural prediction

constructional areas and power line supervising and blood donation The flight

26

period increment payload capability fast movement and speedy placements were

implied features in the UAV so that the UAV was exploited by the applications of

5G and B5G (Ullah et al 2020)

The UAV was considered a motivation for many emergent usages and reformed

social-economic welfares The wireless networks for the UAV and the base stations

were desired for the UAV function Mobile communications were considered

suitable for finding tracing and regulating the flying UAV The wireless

communications were selected for their features of broad coverage quality of

service and secrecy The wireless communication in the UAV improved

productivity besides the line of sight (G Yang et al 2018)

22 UAV-NOMA in Physical Layer Security enhancement

The NOMA has been applied in the fifth generation (5G) technology The Multicast

Cognitive Radio (MCR) network is implemented using the NOMA and coined as

MCR- MOMA The transmission side is also included with the superimposition

code The decoding was applied at the receiving end So an unknown user is

deduced in their methodology (Meng et al 2020)

The physical layer security for the cooperative NOMA was examined Amplify

and forward decode and forward were taken into consideration for achieving

secure transmission (Chen et al 2018)

The physical layer security of the NOMA was analyzed in the broader network with

varying locality The single and multi-antenna were established in the following

cases The single antenna was taken for an end-to-end connection in a secured

manner And the multi-antenna was used for the connection of base station and

random user Finally achieved security for the multi-antenna on the transmission

side The security of the single antenna was attained by introducing the excluding

area for eliminating eavesdroppers The individual expression of security outage

probability for both single antenna and multi-antenna were derived (Yuanwei Liu

et al 2017)

The secure transmission of NOMA in large-scale applications was investigated

Stochastic Geometry was utilized for placing the eavesdropper and user nodes The

equation for secrecy outage probability was derived and expressed for evaluating

27

secure transmission Security can be improved by expanding the protected zone

(Qin et al 2016)

The power domain NOMA had the disadvantage of decoding data by other

unauthentic users of the same source For reducing unauthentic users the base

station should treat the unauthentic users with different cleaning methods The

secrecy outage probability was investigated for authentic users and unauthentic

users Both users were combined as a pair to the non-uniform distribution of original

and unauthentic users The pair outage probability of genuine users from the secrecy

outage probability restrained NOMA authentic users The derivation for pair outage

probability and the secrecy probability were expressed for calibration The

combined system had been the better security (ElHalawany amp Wu 2018)

The physical layer security was considered problematic in the wireless networks

mainly for keeping the authentic userrsquos data The UAV was acted as the base

station UAV based base station had sent the extensive data to the original users

NOMA with the multi-antenna with mm-Wave frequency band transmission had

enhanced the spectral efficiency The physical layer security was attained by

announcing the space around user locality as the eavesdroppers protected zone

Covering the entire eavesdropper area was considered a resource-consuming way

The shape optimization for the protected location in each UAV base stations

altitudes was introduced The derivations for the secrecy sum rate and the secrecy

outage probability were expressed (Rupasinghe et al 2018)

The vehicular communication system had used cooperative NOMA The secrecy

outage probability was considered in vehicular communication The relay can be

used in both modes (half-duplex and full-duplex) in vehicular communication The

closed derivation for the secrecy outage probability was expressed The security of

the full-duplex NOMA resulted better than that of the half-duplex NOMA The

limitations are that the velocity of the vehicles was not considered Figure 21 is

illustrated the conceptual model of the vehicular communication NOMA system

(Xie et al 2019)

28

Figure 21 Vehicular communication NOMA system

The physical layer security of the uplink NOMA of the large-scale devices was

examined The connection networks had investigated with the approach called

stochastic geometry The new derivation was expressed for the coverage

probability The protected zone restrains eavesdroppers to the authentic users

Efficiency secrecy throughput was examined wiretap channels and the many

original users Constant transmission and variable transmission were collectively

inspected The signal to noise and the movement to interference ratio were derived

drastically (Gomez et al 2017)

The wireless system was executed using Space-Time Block Coding (STBC)

approach in the NOMA of mm-Wave MIMO The technique focused on haphazard

users So the pairing method was introduced mainly for Random Near-Random Far

(RNRF) Here the latent period could be minimized and the RNRF has also been

deduced for the overhead issue The result revealed the systems efficiency with a

proper implementation (Ghavidel et al 2020)

The recent arbitrary beam forming method was proposed in the multiple access

NOMA The pairing had decided to the user places So the evaluation was focused

on the system overhead The result revealed that the proposed work outperformed

29

the existing methods (Aghdam et al 2020) NOMA enhances the reliability of

multi-users transmission The sum rate could be reduced for improving Quality of

Service (QoS) power transmission and signal outage probability The

eavesdropper easily accessed the multi-access systems that cause physical security

during transmission (Z Li et al 2020)

The NOMA had provided spectral efficiency speed transmission of data multiple

networking and less latent period The NOMA utilizes the power domains for

various access Cognitive Radio Networks (CRN) is used to screen illegitimate

users The legitimate users were only permitted in the CRN by the Primary User

Networks (PUN) QoS The cooperative NOMA here implemented with the PUN

and the system performance is enhanced The spectral efficiency can be improved

by the secured transmission The cooperative NOMA was additionally developed

in the CRN with the PLS A new method of cooperative NOMA in the CRN was

examined The PUN technique attains a secure transmission Multiple antennae

were used in this study for reliability and the eavesdropperndashexclusion zone method

is used for better security (B Li et al 2018)

The downlink NOMA for moderate CSI was examined The challenge of the power

domain was rectified by allocating power NOMA The power in NOMA and that

of the OMA was analyzed which resulted in a significantly reduced NOMA (Cui

et al 2016)

Here the users were multiplexed by the power domain So the method was coined

as power domain NOMA The demand arising from the B5G (Beyond 5

Generation) had reached using power domain NOMA Machine learning in the

NOMA was described (Maraqa et al 2020)

The uplink NOMA with the PLS was proposed The uplink NOMA contained a

single base station and multi-users a couple of users combined for NOMA The

known jammer emitted the pseudo-noise to divert the eavesdroppers The study had

suggested the two jammers in the uplink NOMA for secure transmission (N Zhao

et al 2020)

The Intelligent Reflecting Surface (IRS) is designed using downlink NOMA The

multi-access had used the space direction of the beams of closure users The IRS

30

had performed the multi-access for every spatial order by the cell edge users of the

orthogonal beams (Ding amp Poor 2020)

The multi-input single-output NOMA has introduced the technique called Secrecy

Beam Forming (SBF) SBF had utilized the artificial noise for NOMA security

aided users in which the eavesdropperrsquos channels deteriorated The SBFs secure

transmission can be achieved in which high successive interference cancellation is

gained (L Lv et al 2018)

The superposition coding was performed in the transmission pat The successive

interference cancellation was conducted in the receiving position These two

techniques were combined in the novel 5G aided NOMA The basic concepts of

uplink and downlink NOMA were mentioned The dominant condition was

performed in the two user clusters of NOMA The prevailing state had issued the

confirmed spectral efficiency gain in NOMA (Tabassum et al 2016)

The relay scheme in IoT was examined for the secrecy of NOMA This was coined

as relay selection NOMA The base station had transmitted the secret messages to

the two NOMA-aided sensors and eavesdroppers IoT had treated the sensors and

eavesdroppers with different power allocations The expression for certain outage

probability and the strictly positive secure capacity was derived Increasing the

number of the relay would enhance the security in the NOMA-aided IoT The

outage probability for NOMA and OMA were compared The NOMA resulted in

better outage probability in Decode and forward mode (Do et al 2019)

31

Figure 22 RS-NOMA against an external eavesdropper

The NOMA-aided IoT was utilized to fight against the external eavesdropper as

Figure 22 The secured NOMA was proposed The base station sent secret

messages to several authentic destinationsmdashseveral eavesdroppers and unauthentic

users

Nakagami-m fading model was carried out using the multiple antennae in the

channel The security was attained using the max-min transmit antenna selection

scheme Both authentic and unauthentic eavesdroppers were analyzed The closed

derivation for the cumulative distribution of the original user was expressed first

That was compared with the unauthentic user The derivation for the secrecy outage

probability was obtained to identify the level of secrecy performance (Lei et al

2018)

Reconfigurable intelligent surface (RIS) aided NOMA was established for the

secrecy performance The main disadvantage of this model was the chance of using

RIS by the eavesdropper The secret outage probability was derived in this paper

The RIS improved the secrecy of the traditional NOMA The eavesdroppers were

limited from receiving the RIS signal by enhancing the number of intelligent

elements in the RIS A high signal-to-noise ratio was obtained from this experiment

(Liang Yang amp Yuan 2020)

32

The cooperative relaying NOMA was proposed for improving private transmission

in wireless networks Full duplex mode transmitted the jamming signals That

received the required communication at first Secondly the jamming signal

emission was sent by the base station The power allocation for the jamming signal

and information signal was decided on the eavesdropper channel state information

The eavesdropper was jammed by the signal from the first phase with maximum

power Second the derivation of the secrecy outage probability was expressed by

static eavesdropper CSI (Y Cao et al 2020)

The NOMA achieved spectral efficiency and secrecy The security of the multi-

NOMA users was obtained by the successive interference cancellation (SIC)

decoding in the receiving node The conservation of the untrusted NOMA was

concentrated in this study The security can be confirmed by the properly secured

decode processing and allocating power The decoding scheme was implemented

for aiding NOMA users The decoding was performed for enhancing the sum-rate

(Thapar et al 2020) The cognitive radio network in NOMA with the external

eavesdropper was proposed (Mehr et al 2020)

The cooperative NOMA was used in the field of energy harvesting communication

The novel relaying technique was introduced for achieving secrecy The secrecy

outage probability was derived and the derivation was expressed for the three

conditions The first condition was the derivation of CSI with a passive

eavesdropper The second condition was the derivation of CSI with the unauthentic

eavesdropper The third condition was the derivation obtained from the multi-relay

nodes The increased SNR resulted in high security The increase in the number of

users deduced security This was considered a disadvantage (Salem et al 2020)

Satellite communication covered more range of broadcasting So the security

challenge was considered a big difficulty in satellite communication Downlink

NOMA was assessed with an eavesdropper for the examination of secrecy The

paper concentrated on the physical layer security of downlink satellites Here two

methods were proposed The frequency-domain NOMA was considered for gaining

spectral efficiency The multiple user interferences were obtained in the process of

overlapping Introducing a suitable technique can be performed the security for the

number of users The secrecy rate was analyzed for all authentic users (and the

33

eavesdropper) and expressed in the derivation The safety was improved using the

spectral overlap method (Yin et al 2019)

The NOMA was considered as the emerging scheme in the upcoming wireless

networks The secrecy sum rate for the downlink NOMA (with MIMO multiple

inputs multiple outputs) was examined Downlink NOMA had the base station

number of users and the eavesdropper In the limitation of transmit power and

optimal successive interference cancellation the security was expected to enhance

Downlink MIMO NOMA was considered advantageous because of its secrecy

performance and the practical usage of bandwidth The mutual information rate and

the mean square error were causing the secrecy rate optimization to the problem of

biconvex This was rectified through the alternative optimization method and the

second-order cone programming was solved (Tian et al 2017)

Table 21 Comparative analysis

The comparative analysis for the physical layer security was examined in existing

studies

SR

No

Details of Author wise Contribution to NOMA Technology

1 Author (YFeng Yang amp Yan 2017) Secrecy performance in NOMA was

conducted with the help of artificial noise in the full-duplex mode of relaying

Methodology The optimization of the power was calibrated for the source

information and the noise signal The closed derivation for the secrecy outage

probability was expressed

Usage and limitations The physical security was increased

34

2 Author (He Liu Yang amp Lau 2017) NOMA was developed in the constrain

of security

Methodology The secret message had been sent to some users and also to the

eavesdropper The Novel decoding process was conducted for excluding the

unauthentic users The iterative algorithm was used for power optimization

Usage and limitations Transmit power was reduced The quality of service

was availed

3 Author (D Wang et al 2020) The secrecy was performed in the NOMA

The security was developed against the eavesdropper outside

Methodology The channel state information was analyzed for secrecy The

quantization of CSI had performed for secrecy The derivation for the secrecy

and transmission outage probabilities were obtained

Usage and limitations The secrecy rate was enhanced

4 Author (L Lv et al 2020) The physical security of the NOMA was

improved by adding artificial noise jammer and inter-user interference The

mode of full-duplex in the updated version was used in the NOMA

Methodology The eavesdropper can be trapped the superimposed signal from

the source So the secrecy was affected

Usage and limitations The spectrum usage is effective in the NOMA

transmission scheme Numerous connections can be performed in the NOMA

NOMA is considered to be the most advantageous for the upcoming

generation communications The superimposition technique was followed

4 Author (Yue et al 2020) Secrecy performance of the NOMA was developed

with a unique framework

Methodology The eavesdroppers inside the zone and outside the coverage

zone were examined properly in this paper The outage probability for codendash

power domain NOMA was derived

Usage and limitations Safety was acquired for both internal eavesdropper

and external eavesdropper in this scheme

35

5 Author (Guezouli et al 2020) The heterogeneous sensor network of cellular

communication was taken into account

Methodology Unmanned aerial vehicles are utilized the heterogeneous

sensor network of cellular communication

Usage and limitations Extended the life span of the network system The

cost of the hardware components is drastically low The random and the

repeats in the speedy movement The latency is maximized The coverage

period is maximum

6 Author (Yao amp Xu 2019) The security in transmitting a large amount of

information in the wireless network systems are analyzed with unmanned

aerial vehicle UAV

Methodology The numbers of UAVs are arranged in the space The base

station sent the information to the UAV in the space The authentic receivers

have obtained the secured information from the UAV The HPPP

homogeneous Poisson point process is used for distributing the authentic

receiver and eavesdropper in the line of sight

Usage and limitations The increase in the number of safety zone causing the

secured transmission

7 Author (Saacutenchez et al 2020) Physical security can be achieved by the

method of a unique encryption scheme

Methodology The physical layer security of the following schemes is

discussed in this paper mm-wave NOMA massive multi-input multi-output

heterogeneous sensor networks full-duplex mode

Usage and limitations The physical layer security was analyzed for the 5G

supporting technologies Good reliability achieved The less latent obtained

Machine-type communications can be enabled

36

8 Author (Hou et al 2018) The multi-antennas were used in NOMA with

UAV The stochastic geometric approach was examined

Methodology The multi-input multi-output kind of NOMA was utilized In

common the stochastic geometric approach was used for drastically moving

NOMA

Usage and limitations The maximum signal-to-noise ratio was obtained in

this scheme Power optimization was achieved The path loss is less Good

spectral efficiency was obtained

9 Author (Miao et al 2020) The broadcast type of communication was

performed The less weighed three-dimensional space for 5G communication

was analyzed

Methodology Both the performances of multicast and broadcast were

enabled UAV-assisted 5G communication systems are emerging in the

upcoming wireless networks

Usage and limitations Better flexibility in the network Continuous mobility

One lined line of sight

10 Author (Majhi amp Mitra 2020) The secure communication in cognitive radio

by NOMA was propounded

Methodology The antenna strategy of giving minimum outage probability

was concluded from this study

Usage and limitations The limitation is that more spectral efficiency causes

security issues

11 Author (X Zhao amp Sun 2020) Secure communication of the physical layer

in Visible light NOMA Communication was proposed

Methodology Energy optimization in security constrain was propounded for

achieving overall performance

Usage and limitations It is difficult to find optimal results because energy

optimization is the nonconvex issue

37

12 Author (Tuan amp Hong 2020) Secure communication in simultaneous

wireless information and power transfer NOMA was remitted

Methodology Eavesdropper is used for security purposes between the user

and base station using energy relays Known jammer is used for secure

transmission For energy efficiency storing and transferring were propounded

Usage and limitations Jamming requires extra power allocation

13 Author (Vaezi et al 2019) NOMA for 5G in mmWave MIMO cooperative

and cognitive were analyzed in this study

Methodology SWIFT NOMA is useful for weak receivers

MIMO using more antenna

Usage and limitations multi-antenna utilization cause high power

consumption

14 Author (Vaezi et al 2019) Mobile edge computing NOMA was proposed to

optimize power

Methodology Minimum latency and less power consumption

Usage and limitations Transfer power allocation must be calibrated

15 Author (Faraji-Biregani amp Fotohi 2020) Security in UAV communication

was proposed by introducing mobile agents

Methodology Malicious user of UAV was identified

Usage and limitations Three-phase power is essential

16 Author (G Zhang et al 2019) Secure communication in 5G UAV was

propounded by joint trajectory carrying out in physical layer

Methodology Power optimization was proposed for security

Usage and limitations Security in the physical layer was achieved by

optimization of trajectory

17 Author (Fotohi et al 2020) Agent-based self-protection was propounded in

UAN for secure communication

Methodology This method imitates the immune system of human beings

Less cost

Usage and limitations Energy is not optimized properly This approach

needs to consider other malicious attackers

38

18 Author (Shang Liu Ma amp Fan 2019) Vehicle to everything approach was

propounded for security in a UAV

Methodology Security of vehicle to the vehicle was proposed by considering

eavesdroppers active and passive attacks

Usage and limitations High price

19 Author (Kantor et al 2017) The flight path was calibrated in a UAV

Methodology Security performance was achieved by encryption as well as

anonymization

Usage and limitations High in cost and hardware structure occupies more

place

23 Research Methodology

The NOMA-based cellular architecture for UAV communication has been

considered here as reference network architecture Rayleigh fading has been

assumed as a channel characteristic The performance parameters for PHY layer

security are (1) Pair Outage probability (Pair OP) between two users trusted near

user designated as U1 and untrusted far user designated as U2) and (02) Secrecy

Outage Probability (SOP) of trusted near user designated as U1 The aim is to

achieve optimal Pair OP for the given constrained SOP of User U1 so that network

resources can be efficiently allocated to both users without compromising the

secrecy of trusted User U1

The mathematical analysis from reference literature (ElHalawany et al 2018) has

verified and supported the joint optimization of the Pair OP and SOP for the given

power allocation factor in NOMA This research work is extended as providing

more efficient resource allocation using the POMDP algorithm in a given scenario

First the varying distance of untrusted user U2 from BS as a critical selection

parameter that affects Pair OP amp SOP of user U1 and U2 both has been simulated

and the feasible and infeasible pairing of both users have been analyzed The

optimal power allocation factor for feasible pairing as the constrained problem is

optimized by opting for POMDP as a resource allocation algorithm wherein the

SOP of user U1 is strictly maintained for given CSI POMDP provides optimum

39

power allocation factor for trusted and untrusted users pairing as shown in the

proposed flow of POMDP algorithm is used to model a variety of real-world

sequential decision-making problems After the BS has been set up the distance

between the BS and the user is calculated and if space is less than 200m it is

defined as a trusted user While if the range is more than 200m it is described as

untrusted users In the case of trusted users the channel state information (CSI) is

provided to the proposed algorithm POMDP for reliable and efficient resource

allocation

24 Summary

UAVs play a central role in providing network service recovery in a disaster-

stricken region enhancing public safety networks or handling other emergencies

when Ultra-Reliable Low-Latency Communication is required In particular UAV-

assisted communication can be regarded as an important complement to the 5G

cellular networks Surveyed literature related to UAV communications published

over the past several years emphasized the cybersecurity and channel modeling for

UAV communications etc Security is one of the critical issues in communications

Modern communication networks are based on the layered architecture from the

physical layer up to the application layer A great deal of effort has been made to

develop the cryptographic protocols above the physical layer However the

physical layer is not as robust as that in wired communications The physical layer

in wireless communication is more complex than the counterpart in other

communication paradigms The concerns come from not only the noises but also

many types of fading Recently there has been an influential interest in studying

the security issues in the physical layer Security is highlighted as another

challenge and the implementation of physical layer security techniques is seen as

a difficult task PHY security in NOMA systems under the presence of external

eavesdroppers or untrusted relay nodes Upcoming 5G networks for unpredicted or

crisis (disaster management) the placement of terrestrial substructures is

economically infeasible and challenging due to high operational expenditure as well

as sophisticated and volatile environments

To address such novel issues intelligent heterogeneous architecture by leverage

UAV has been well-thought-out to be a promising novel model For advancing the

40

performance of the UAV 5G communication system physical layer techniques are

of many effects as they have impacted the applications of UAVs Security of

NOMA-based UAV communication network has been scrutinized for optimization

as physical layer security

41

CHAPTER-3

SYSTEM MODEL FOR NOMA-UAV

COMMUNICATION

31 NOMA-UAV System Secured Communication for 5G
















311 The basic scheme of NOMA

The NOMA system allowed several users to be served simultaneously by the

transmitter To transfer a linear combination of different signals towards the

recipient the system of proportional representation superposition coding (SC) The

transformed signal is provided through

σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)

Where 119927119948 represents the transmit power assigned toward user k th

119930119948 indicates the normalized message used for user k th

42

The instantaneous total converses power is σ 119927119948119922119948=1 The received signal at user kth

and the eavesdropper are offered through

119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)

Where 119951119948 and 119951119942 indicated the zero-mean Additive White Gaussian Noise

(AWGN) at user k th with variance 1205901198962 and the zero mean AWGN at eavesdropper

with variance 1206481199422 respectively We assume that the noise variances at all the users

are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902

As per NOMAs process the SIC is followed by all users to decrypt the message to

the same decoding order Notice that it is not known what the optimal decoding

order is for the NOMA method that corresponds to secrecy

Therefore the mth message to be encoded to the user might not be the mth message

to the user As such we also have to add the π variable For example if 120587(1) =

3 then the first message to be decoded for the SIC is the message for the user 120645(119947)

forall j lt k before decoding its letter to remove the inter-user interference successively

Then the user 120645(119948) denotes its message while treating the news for all the user

120645(119946)foralli gt k as the interferences The received Signal-to-interference-plus ndashnoise

ratio (SINRs) at user 120587(119896) k lt K and user 120587(119870) to decode their messages are

respectively given by

119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43

Also the acknowledged SINR at user 120587(119898) to decrypt the message 120633120645(119948) 119896 lt

119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)

Similarly the acknowledged SINRs by the eavesdropper of the message 120575119896 119896 lt

119870 and the message 120575119896 are respectively given by

119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘

Notice that here expressions for the obtained SINRs at eavesdropper overestimate

the skill of eavesdropper Here a worst-case inference from the viewpoint of

legitimate users is made That is the messages have already been decrypted by the

eavesdropper for all users π (j) forall j lt k before attempting to decrypt the message

for the user π (k)

The presumption also assumes that the decrypting order and power distribution are

understood by the eavesdropper The eavesdropper may or may not recognize the

decoding order of the users and the allocation of power may or may not recognize

the messages for all users π (j) forall j lt k before attempting to decode messages for

users π (k) However since the eavesdropper has been unable to alert the authorized

customers of its capacity and the current CSI the approved user would be unable

to know the eavesdroppers details Therefore we have to pursue the worst-case

scenario for the permissible users point of view due to the liberality required by the

safety reports It highlights that the worst-case assumption in the study and design

of transmission schemes with secrecy requirements has been generally adopted

The proposed study has been evaluated using performance measures Here we

analyze NOMA with downlink and uplink networks suggested by SINR and Sum

44

Rate survey High SNR is then simulated to contrast the OMA and NOMA

processes

312 Downlink of NOMA

The Downlink of the NOMA network on the transmitter side is described in Figure

31 SIC method is supposed to be carried out successively on the receiver side of

each user until another signal is restored The coefficients of users are owed in an

inversely proportional manner based on their available bandwidth

Figure 31 Downlink NOMA network

A consumer with a poor available bandwidth has a transmission capacity of a

higher range than a consumer with strong available bandwidth As a consequence

the consumer with the higher power assumes the signals of other users to be noisy

and automatically restores the signal without conducting any SIC operation The

receiver of each consumer detects indications that are stronger than those of the

desired signal These impulses are then deducted from the power and this process

continues until the signal has been calculated Both users decrypt their signaling by

considering other users with lower correlations The signal is calculated as

45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)

Where Xi is the user ithrsquos information through unit energy

Ps is the capacity of transmission at the BS

ti is the coefficient of power assigned for user i

Although without the need for lack of generality the channel profits are expected

to be graded as ȁℎ1ȁ2 le ȁℎ2ȁ2 le ⋯ ȁℎ119871ȁ2

Where 119945119923 is the coefficient of the channel of the user Lth

The received signal of the Lth user is calculated as

1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)

Where n1 is zero mean Complex Gaussian noise with a variance of 1206482SINR

analysis with the equation (2) the SNR of Lth user to identify the user 119895 le 1with

119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)

Where 120632 = 1198751199041205902ൗ represents the SNR

Sum rate analysis After identifying the SINR of the downlink the sum rate will

also be done quickly

The NOMAs downlink data rate of Lth user can be calculated as

1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA

The Uplink NOMA is depicted in Figure 32 where each user sends a signal to the

BS SIC iterations are supported to classify the signals of mobile users If both

channels are identical and BS sends the coefficients of power allocation to mobile

users the received signal can be interpreted as a synchronous uplink to the NOMA

46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)

Where hi is the coefficient of the channel for the ith user

119927119961119946 is the extreme transmission capacity supposed to be general to all users

N is zero-mean Gaussian noise with a variance of 1206482

Figure 32 Uplink NOMA

Analysis of SINR The BS decrypts the signals of the users as per the coefficients

of the users and the SINR for the Lth user can be defined as

119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)

Where 120574 = 1198751205902ൗ indicates SNR

Analysis of Sum rate The sum rate of uplink NOMA when 120632 minus infin can be

computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47

314 Comparison of NOMA and OMA

The attainable data rate of the Lth user of OMA intended for both uplink as well as

the downlink is estimated as

119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)

Just for convenience two users should evaluate the summation of uplink rates for

NOMA and OMA The use of both the uplink rate of NOMA and OMA at high

SNR can be calculated as---

119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)

equation (7) and (8) it is seen that 119877119904119906119898119874119872119860 le 119877119904119906119898

119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

119925119926119924119912 shows that NOMA performed better than OMA in

terms of sum rate in both downlinks as well as uplink of two user networks

The sum rate will be calculated after the SNR as the formulation is shown In this

proposed work multiple users are propagated to the process of NOMA and here a

comparison of NOMA as well OMA has been defined The NOMA uplink and

downlink using the OFDMA method for the

32 PLS performance metrics in NOMA -UAV communication

This chapter mainly describes the proposed work to examine the availability of the

outage probability of the pair below an authorized user According to the decryption

of SIC availability and spectrum sharing the unauthorized user can function as an

eavesdropper and obtain an outage probability (OP) for all situations with the

Secrecy Outage Probability (SOP)

321 SOP and OP - two user and multi-user NOMA system

NOMA system has the capability for assigning multiple data over the transmission

signal through high-level coding (Shim amp An 2018) Thus it contains spectrum

efficiency when opposed to OMA But this has a limitation in security As an

48

instance if the eavesdropper is reached then it obtains multiple user data in the

interference of the NOMA signal Thus the security issues are more significant in

this system Here PLS is an available method to rectify the attack intended for

malicious users (Dai et al 2015)

Additionally data should be transmitted confidentially if the root and eavesdropper

networks can be evaluated and the recipient can decrypt the received text At the

same time the eavesdropper is not able to solve the text that has been interrupted

PLS is at the cutting edge of wireless communication security technology to prevent

eavesdropping attacks The SOP is described as the likelihood that the near users

attainable device confidentiality capability will fall under the predefined target

confidentiality rate as set out in (Shim et al 2017)

Through SOP we can calculate the level of protection of the device As an example

the low-secret OP system makes the system more stable in terms of security than

the high SOP system To boost the efficiency of the PLS CSI-based opportunistic

scheduling links to a scheduled destination in a particular time slot It has been

documented as an enticing scheduling scheme (Long Yang et al 2016) because the

various wireless channel has been exploited Opportunistic scheduling is also

considered to be one of the strategies used to increase the confidentiality efficiency

of the NOMA method

322 System Model

Suppose a multi-user NOMA system of downlink containing BS a selection of K

nearer users as N= 119873119894ȁ12 119870 and a range of M far users as F=

119865119895ȁ12 119872 and an eavesdropper E as displayed in Figure 33 More

specifically nearer users should make active use of the SIC methodology to

distinguish far user F Both the legitimate and illegitimate receivers are furnished

through a single antenna and operate in a half-duplex manner

49

Figure 33 Multi-two user architecture of NOMA system (Shim amp An 2018)

Here 119945119935119936 and ȁ119945119935119936ȁ2

Where X120598ሼ119878ሽ 119884120598119873 cup ሼ119864ሽ represent the channel coefficient and the corresponding

channel gain of the X-Y value

Taking into consideration that each wireless channel for Rayleigh block fading 119945119935119936

can be incorporated as an independently distributed random Gaussian variable with

zero mean and affirmative ℷ119935119936 Variance The outcome of channel gain ȁ119945119935119936ȁ2is an

exponential variable randomly through the Probability Density Function (PDF)

119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)

Especially the average channel profit can be represented as

ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)

When 120027 is the attenuation of the received signal 119941119935119936 signifies the distance among

X and Y 1199410 indicates the space and 120656 is the exponent of the path loss It is believed

that the source is entirely familiar with the CSI of both legitimate users and

eavesdroppers

50

323 Partially Observable Markov Decision Process-POMDP

Figure 34 Flow Diagram of the proposed system

The proposed overflow is shown in Figure 34 After the BS has been set up the

distance between the BS and the user is calculated and if space is less than 200m

it is defined as a trusted user While if the range is more than 200m it is described

as untrusted users In the event of untrusted users the channel state information is

accessible to the POMDP accompanied by the allocation of resources The study

was carried out after the machine operation Here a NOMA-oriented cellular setup

provided with a BS at the Centre and two users was described in Figure 35

51

Figure 35 Near and Far User

The adjacent user has a high level of security confirmation needed to protect the

layer since the low-security clearance user is situated at a distance away from the

BS P is specified as the highest level of transmitting power In this chapter it is

presumed that all DNS servers are furnished utilizing an individual antenna and all

channels are supposed to be individually static identical to the Rayleigh

dissemination concerning distribution

119862119873(0 120575119898

minus120572

212059601 2Τ

)

In which 120633119950 is the range between the BS and the nodes 119932119950 Here the path-loss

exponent and constant are defined as 120630 and 1206540 Furthermore BS is assumed to

have predicted the position of the user so that a better CSI can be obtained at BS

that is elaborate in user pairing

The BS transmits the superimposed mixture

119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)

In which 1199561 and 1199562 are the unit of power signals received by users 1199321 and 1199322

respectively t is the power allocation coefficient for the adjacent user

1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)

Where 1199451119886119899119889 1199452 the channel profit link with the fading of small scale since the

BS to the user 1199321 and 1199322 respectively The additional Gaussian noise with variance

52

is denoted 1199511 119886119899119889 1199512 and zero mean 119894119904 119889119890119899119900119905119890119889119886119904 (1199250) and it is assumed

that the BS conveyed SNR is 120646 = 1199271199250

ൗ

In the NOMA technique additional users with more power may decode their signal

by recognizing the adjacent signal as noise without decoding the adjacent user

message In the previous equation 1198801 is supposed to first solve a weak signal by

decoding its own SIC signal1198802 which is an unauthenticated user attempted to

decrypt the nearer user text after decrypting the adjacent usage text after decoding

its own SIC message The following equation has therefore been achieved

11987811986811987311987721 =

(1minus119905)ȁℎ1ȁ2

119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951

indicates the SINR ratio of user mth that was decoded by 119932119951 for

119898 119899 isin ሼ119894 2ሽ and the channels gain followed an exponential distribution with the

parameter 120649119950=120654120782120633119950minus120630

324 Problem formulation

As a result the BS could achieve and provide better communication for users who

are vulnerable to security threats from unauthenticated users the proposed

framework identified two kinds of QoS energy efficiency that could be considered

essential for addressing the problem In a particular study a pair of OPs was

specified to check the reliability at which the attainable data rate for users is equal

to or greater than the threshold of minimum reach The following issue aimed at

reducing the pair OP to an SOP factor intended for the user 119932120783 that is provided by

Where 1199270is Outage Probability- (OP)

1199271 is Secrecy Outage probability user U1 119930119926119927(119932120783) and

120631 the permissible SOP threshold

53


System

331 The Pair OP Calculation

Through Shannons capacity formula and assuming 119914120783119957119945 119886119899119889 119914120784

119957119945 as the

threshold capacities of users 119932120783 119886119899119889 119932120784 respectively the combination of OP

could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)

Case 1empty1 gt empty2 for having the limitation of the allocation of power factor (t)

required to be satisfied (tgt120649120783

120649120783+120649120784+120649120783120649120784) and for this case 119928120784 could be attained as

follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)

Case 2 empty1 lt empty2 Like case 1 it was stated that the opposite constraint depends

on

t gt 1206491

1206491+1206492+12064911206492 and 1199282 can be evaluated as follows

119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54

Table 31 List of parameters

Parameters Description

N Number of nearer users

M Number of far users

E Eavesdropper

ℎ119909119910 Channel coefficient between 119909119905ℎchannel and 119910119905ℎ users

119889119883119884 The distance among x and y

1198890 Space

120598 An exponent of the path loss

ℒ Attenuation of the received signal

120575119898 the range between the BS and the nodes

1205960 Path loss constant

120572 Path loss exponent

1199041 1199042 Unit of power signals received by users 1198801 and 1198802

T Power allocation factor for the adjacent user

ℎ1119886119899119889ℎ2 Channel coefficient of 1198801 and 1198802with the fading of small

scale

11989911198861198991198891198992 Gaussian noise variance

1198730 Zero mean for Gaussian noise

120588 Signal to noise ratio

119878119868119873119877119898119899

Signal to interference noise ratio of users n and m channels

55

120591119898 Exponential distribution parameters

1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)

120573 The permissible SOP threshold

Table 31 depicts the list of parameters used in the proposed methodology which

are useful for assigning and the values are assigned based on the parameters given

for the experimental evaluation as well This chapter concludes with the basic and

the actual flow of the proposed method to know more about the work in the

simulation process

332 Pseudo-code for the proposed algorithm

Algorithm I

Step 1 Estimate Rayleigh distribution

119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where

120633119950 is the distance between nodes 119932119950 and the BS

120630 is the path-loss exponent and

120654119952 is the path-loss constant

Step 2 The BS broadcasts the superimposed mixture and input signal as follows

119909119905 = ξ1199051199041 + ξ1 minus 1199051199042

Where 119956120783 and 119956120784 are the unit power signals received by users 119932120783 and 119932120784

respectively 119957 is the Power allocation coefficient for the near user

Step 3 The received signal is as follows

1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56

119945120783 and 119945120784 are the channel gain associated with the

small-scale fading from the BS to users 119932120783 and 119932120784 respectively

1199511 and 1199512 are the additive white Gaussian noise with zero mean and variance

119925120782

Step 4 the BS transmit signal-to-noise ratio (SNR)

120646 = 119927119925120782

Step 5 Signal-to-Interference-plus-Noise-Ratio (SINR) for the two users 119932120783

decodes the signal of the weak user first then decodes its own signal after using

SIC 119932120784 is an untrusted user and tries to decode the near user message after

decoding its own message using SIC

11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951

is the signal-to-interference-plus-noise-ratio (SINR)

of user 119950th decoded by 119932119951 for 119898 119899120598ሼ119894 2ሽ and ȁ119945119950ȁ2 is the

channels gain of 119932119950

Algorithm II

Partially observable Markov decision process

Step 1 Prediction of the maximum capacity of channel with respect to the data rate

119955119943 = 119877(119878119909119863)

S is denoted as states

Let D be the channel characteristics which are considering here as actions

Reward function R

Step 2 The agent receives an observation 119900120598120118which depends on the new state of

the environment 119930prime and on the just taken action 119941 with probability

119926(119952ȁ119956prime 119941)

Step 3 Reward earned at time t is expressed as

57

119903119891119905 = 119877(119878119909119863)119905

Step 4 reward function on belief states

119919 is the belief states over POMDP states

119919119943 is the belief state transition function

119955119943 = 119877(119867119909119863)

Step 5 The reward function is updated based on the belief MDP the agent only

cares about which action will yield the largest expected immediate reward ie the

maximum capacity channel

119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891

119875119903(ℎprimeȁℎ 119889 119900) = ቄ1119894119891119905ℎ119890119887119890119897119894119890119891119906119901119889119886119905119890119908119894119905ℎ119886119903119892119906119898119890119899119905119904ℎ 119889 119900119903119890119905119906119903119899119904ℎprime

0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY

The NOMA-UAV communication framework has been proposed in this research

work and the Physical Layer security aspect has been focused on for optimization

The PLS performance metrics selected are SOP amp Pair OP in the proposed system

model The POMDP framework is general enough to model a variety of real-world

sequential decision-making problems Applications include robot navigation

problems machine maintenance and planning under uncertainty in general Here

we have adopted the User pairing POMDP algorithm for resource allocation in two

users amp multi-user NOMA-UAV communication networks The proposed study has

been evaluated using performance measures by varying distances of trusted amp

untrusted users from the base station as well as for varying SINR conditions The

simulation results and outcomes are discussed in a further chapter

58

CHAPTER 4

RESULT AND DISCUSSION

41 PERFORMANCE MEASURES OF SECURED NOMA-

UAV COMMUNICATION MODEL

Drones or UAV-based communication technology has been thoroughly studied and

adopted by the 3GPP standard UAV systems have been envisaged to form an

integral part of future wireless communication applications due to their dynamic

flexible and flying nature Due to their ability to reach higher altitudes they usually

have dominant LOS channels with the ground nodes This capability can be used to

provide confidentiality to the legitimate receivers against the eavesdroppers This

can be done by deploying UAVs to launch more effective jamming signal attacks

to terrestrial eavesdroppers The conventional cooperative jamming schemes make

an assumption that the locations of terrestrial jammers are fixed which might

compromise the secrecy of the system if the jammers are located far away from the

eavesdroppers and is also not practical as it makes an assumption of perfect CSI of

the jammer to eavesdropper channel

Here in the proposed scenario of the NOMA-UAV communication network two

key PHY layer security metrics SOP amp Pair Outage Probability have been jointly

optimized for a more effective power allocation factor for NOMA cellular

architecture The varying channel characteristics have been analyzed to achieve the

desired SOP with the constrained threshold minimum target secrecy rate for the

two-user scenario POMDP Algorithm iteratively provides the optimized SINR that

has been used to keep trusted users in pair with the untrusted user with minimum

achievable outage probability

The proposed NOMA-UAV System model has been simulated in MATLAB 2019b

version with mainly Communications System Toolbox Optimization Toolbox RF

Toolbox Signal Processing Toolbox Statistics and Machine Learning Toolbox

The simulation has been carried out for two-user pair to achieve desired secrecy

target rate and feasible pairing between trusted user amp untrusted user(eves-dropper)

59

The optimal-outage performance of minimized pair OP subjected to SOP constraint

has been solved by both dynamic programming optimization and POMDP

optimization approaches

The simulation of the proposed framework for the UAV-NOMA communication

network has been carried out and discussed in two parts two user models and a

multi-user model as below mentioned discussion The base station is deployed at

the center of a cell of radius 1000 m There are two users in the system under

consideration The channel between two nodes in the system suffers both the small-

scale fading and path loss effect Small-scale fading follows the exponential

distribution with the mean value 1 The noise signal of all channels has a Gaussian

distribution with 0 mean and variance 1 The path loss exponent α and the path loss

constant PLo are set to 2 and 01 respectively We assume a normalized bandwidth

of 1 Hz The SOP constraint threshold is assumed 01 and the target secrecy rate is

001 The power allocation coefficient is 015 and the BS transmitted SINR is

assumed 15dB for the proposed model As per the NOMA transmission scheme

SINR has been obtained for User 1 amp User 2 both for SIC decoding POMDP

algorithm optimally tunes the SINR value for User 1 amp User 2 that is considered to

select optimal power allocation coefficient for both trusted and untrusted users with

respective SOP of User1

42 Numerical results and Discussion

Table 41 Simulation Parameters

Parameters Values

Untrusted user Distance (d2) 200-1000 (300 700)

BS transmit signal-to-noise ratio (SNR) (120588) in dB 15

Sop constraint constant threshold (β) 01

Power allocation factor (t) 015

Trusted User distance (d1) 2-

60

Cell Radius (rd) 1000 meters

Path loss exponent (α) 2

Path loss constant (PLo) 01

Normalized bandwidth in Hz 1

Target secrecy rate (Rs) 001

No of Bits 100

Pair Outage Probability (P0) 05250

SINR 5319 15305 5162

10247

421 Feasible amp Infeasible pairing of trusted amp Untrusted users

In this section the CSI value broadcasted by Base Station is assumed 15 dB initially

and for varying channel conditions various SINR values of 120646 = minus20 minus10 20 dB

is described with target secrecy rate 0005 and 001 for power allocation coefficient

015 and User 1 distance at 200m is shown in the Figure 41 below

Figure 41 Impact on Sop with increase distance between BS and user U2

61

Varying target secrecy rate threshold from 0005 to 001 the obtained result in

Figure 42 revealed that the 1199321 is a gradually reducing function for the distance of

untrusted user d2 that implies that the increasing value of d2 leads to the

improvement of the SOP of 1198801

Figure42 Impact on Sop with increase distance between BS and user U2

Since the offered constant threshold 120656 in SOP limit1199322 which should be located at

a larger space when compared with a value of threshold to attain the SOP of 1199321

apart from that it is expected the high target secrecy rate maximizes the SOP of 1199321

Here in below figure the power allocation coefficient has been varied from 0 to 1

with threshold value of t and the desired t_sop for feasible pairing

Figure 43 Feasible pairing t Vs pair OP

62

Pair OP in case of rising 1199322 untrusted user in d2 for different BS transfer the SNR

where t= 015 and d1=200mThe infeasible pairing of SOP (1199321) and the OP pair

by the enhanced allocation of the power (t) d1 (200m) d2 (300m) 120646 = 15 dB and

120656 = 0

Figure 44 shows the identical plotting of data by adjusting the unauthenticated

level of the user through converting it to a BS closer distance (d2=300m) Accuracy

is compared and checked with the full spectrum of numerical simulations The

result has shown that the effectiveness is based on a comparative study of the two

consumers of the BS

Figure 44 Infeasible pairing t Vs pair OP

422 The Secrecy Outage Probability amp Pair Outage Probability

Feasible paring in the SOP of pair OP and 1199321 with the improved power allocation

factor t in which d2=700m d1=200m 120646 = 15119889119861 and The result described that

the OP and SOP of the user 1199321 with increased for two various distances of the 1199322

untrusted user The simulation result approves the convex nature 120656 = 0 1of the OP

and the SOP is sequentially decreased depending on t Generally when it enhances

the power owed to the weak user text reduces that develop the ability of 1198802 for

discerning the superior positioned signals therefore enhancing the SOP of 1198801

63

Figure 45 Secrecy outage probability

Figure 46 Pair outage probability

423 SNR versus Strictly Positive Secrecy Rate

Figure 47 proved that the potential for confidentiality is superior to the existing

techniques The proposed application for pre-coding improves the efficiency of the

device The transmission power of the system is the power needed for the

transmission of particular data

64

Figure 47 SNR versus Strictly positive secrecy rate

If there is a growth in the number of users there is a risk of inference in the

transmission of data and thus the reliability of the data rate may be affected Based

on these cases the efficiency of the antenna power to be withheld and occupy the

data determined


In the case of multi-users scenario when there are more than two users then the

allocation of an optimized resource block to all users is the key parameter to achieve

desired outage efficiency because strong users require higher SNR for higher data

rates and weak users are allocated minimum threshold SNR for lower data rate

requirements to maintain suitable pairing OP and SOP balance

Figure 48 Power radiated by per MMBs antenna

65

So the POMDP policy optimization has shown better performance over the

dynamic programming approach particularly when more users are active (a greater

number of antennas as in Figure 48 the overall radiated power per BS antenna in

downlink has been considerably reduced

43 CONCLUSION AND SCOPE OF FUTURE WORK

431 Conclusion

Starting with LTE (4G) OFDMA has replaced WCDMA with mobile cellular

communications and will also be used during advanced 5G while Non-Orthogonal

Multiple Access (NOMA) has recently been recognized as a groundbreaking PHY

technology in UAV communication NOMA scheme is used in place to increase the

effective use of small resources such as in UAV communication where the data rate

is very low and critical decision making is of utmost importance

The critical need for UAV communication is a secure PHY layer for mission-

critical applications and as NOMA doesnrsquot promise high security the proposed

research work has been carried out to enhance the insecurities of NOMA-UAV

communication In this proposed research work the probabilities of confidential

outage (SOP) and OP were investigated in the two-user NOMA system Here BS is

required to pair a trusted or permissible user with other untrusted users due to the

unequal distribution of untrusted and trusted users in the cell The SIC is then

applied to the receiver side intended for decoding the message signals The Pair OP

of both users has been analyzed for varying Target Secrecy Rate (Rs) of the trusted

user U1 which provides constraint threshold of the SOP of U1

By varying the distance of Untrusted users from BS the optimal distance and power

allocation factor for the feasible pairing of trusted and untrusted users without

compromising the secrecy outage probability of U1 has been achieved in simulation

results

POMDP has provided the optimal power allocation as a resource allocation

algorithm in the dynamically changing environment of two user NOMA cases

where the distance between BS and untrusted user varies significantly The

performance of secure NOMA-UAV is affected critically by (SOP of User 1) which

66

should be optimally selected to maintain the proposed Pair OP between both users

and the simulation results have supported this optimal outage performance Thus

NOMA-UAV architecture has the potential of providing a secure PHY layer for

mission-critical applications by opting for suitable decision-making resource

algorithm POMDP

431 Scope of Future Work

Furthermore the multiuser scenario with the increased number of Untrusted users

can be analytically verified and simulated in the same direction for NOMA-UAV

communication to improve transmission security and reliability In addition more

adaptive and efficient Resource allocation algorithms for NOMA-UAV networks

with secured performance in real-time applications should be investigated

1

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Rashid A Sharma D Lone T A Gupta S amp Gupta S K (2019) Secure

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11

PUBLICATIONS

Pankaj PatelJournal of Engineering Research and Application wwwijeracom

ISSN 2248-9622 Vol 9Issue 4 (Series -IV) April 2019 pp 49-54

wwwijeracom DOI 1097909622- 090404495449|P a g e

Migration from 4g LTE to Advanced PHY Techniques for

Unmanned Aerial Vehicle (UAV) Communication

Pankaj Patel PHD StudentGujarat Technological UniversityGujarat India

ABSTRACT

UAV (unmanned aerial vehicles) with their high mobility and low cost have found a wide range of applications

during the past few decades Historically UAVs have been primarily used in the military mainly deployed in

hostile territory to reduce pilot losses With continuous cost reduction and device miniaturization small UAVs

are now more easily accessible to the public hence numerous new applications in the civilian and commercial

domains have emerged For the sake of boosting resilience against faults natural disasters and unexpected

traffic the Unmanned Aerial Vehicle (UAV) assisted wireless communication systems can provide a unique

opportunity to cater for such demands in a timely fashion without relying on the overly-engineered cellular

network However for UAV-assisted communication issues of capacity coverage and energy efficiency are

considered of paramount importance Starting with LTE (4G) Orthogonal Frequency Division Multiple Access

(OFDMA) has replaced WCDMA for cellular mobile communications and it will also be employed in advanced

5G yet Non-orthogonal multiple access (NOMA) has been recently recognized as a promising PHY technique

to significantly improve the spectral efficiency of mobile communication networks In this paper we provide an

overview of UAV-aided wireless communications by introducing the basic networking architecture

highlighting the key design considerations as well as the new opportunities to be exploited

Keywords LTE (4G) Non-orthogonal multiple access (NOMA) Unmanned Aerial Vehicle (UAV) Wireless

communication

----------------------------------------------------------------------------------------------------------------------------- ---------

Date Of Submission 26-04-2019 Date Of Acceptance 06-05-2019

----------------------------------------------------------------------------------------------------------------------------- ----------

I INTRODUCTION The use of unmanned aerial vehicles

(UAVs) will grow rapidly in the next decade These

remotely piloted or preprogrammed aircraft are

envisioned for applications in numerous civil

settings including industrial monitoring scientific

data gathering agriculture public safety and search

and rescue Many other applications - presently

unforeseen - will inevitably also arise These

vehicles also known as the unfortunate misnomer of

drones must be integrated into the national

airspace system and into the airspace worldwide A

natural concern in the use of UAV is safety and this

has direct implications for the control and non-

payload communication systems that must be used

to operate it efficiently Similarly navigation and

surveillance functions must be made more reliable

and more accurate Because of these factors many

UAV research development testing and

standardization efforts are underway by

governments industries and academia Despite the

fact that piloted civil aircraft have been flying safely

for decades UAV presents distinct new challenges

in the form of different flight profiles eg low-

elevation flights and more high-dynamic maneuvers

wider required bandwidths eg for video and

different ground site characteristics such as locations

in cluttered areas and lower elevation antennas

In this paper first the evolution of radio

technologies considered in UAV wireless

communication is reviewed in literature survey and

the significant work in the area is highlighted along

with the newest challenges The reminder of this

paper is organized as follows

The promising technology NOMA and its

variants are discussed in section three In Section

four the system model and assumptions are

presented and in section five the comparative

analysis of NOMA with existing popular technology

OFDMA (OMA) is given with simulation

persormance analysis At last the work is concluded

in section five

II LITERATURE SURVEY Drones variously known as unmanned

aerial vehicles (UAVs) unmanned aerial systems

(UAS) or remotely piloted aircraft system (RPAS)

are used in several parts of the world for surveying

and aerial mapping disaster management work

monitoring crop production and infrastructure

activities besides commercial photography and

courier delivery The viability of UAV as a

multipurpose research vehiclehas driven great

RESEARCH ARTICLE OPEN ACCESS




interest since recent decades[1] The

basictechnology building blocks responsible for the

current advancesinclude airframes propulsion

systems payloadssafety or protection systems

launch and recovery dataprocessor ground control

station navigation and guidanceand autonomous

flight controllers The following briefsurvey is

focused on the area of navigation guidance

andcontrol of UAVs Various control design for

UAVs has beenproposed ranging from linear to

nonlinear synthesis timeinvariant to parameter

varying and conventional PID tointelligent control

approaches The developed controllershave been

implemented for different aerial platforms

airship(blimp) fixed-wing UAV small scale

helicopteruad-rotors and MAV Wireless

communication systems that include unmanned

aerial vehicles promise to provide cost-effective

wireless connectivity for devices without

infrastructure coverage Compared to terrestrial

communications or those based on high-altitude

platforms on-demand wireless systems with low-

altitude UAVs are in general faster to deploy more

flexibly reconfigured and likely to have better

communication channels due to the presence of

short-range line-of-sight links However the

utilization of highly mobile and energy-constrained

UAVs for wireless communications also introduces

many new challenges In India for the regulation

and safety purpose in commercial and survilence

applications the policy guideliens also introduced

as below

Table 1UAV communication Policy Guidelines for

commercial and surveillance purpose

III MIGRATION FROM 4G LTE TO 5G The fruitful deployment of UAV based

communicationsystems for 4G and beyond future

wireless networks is highlyinvolved in finding joint

solutions to challenge of ubiquitousconnectivity with

both a multitude of devices in a spectralefficient way

as well as with energy-efficient transmissionand

operation of the UAV-BS for maximized and

armonizedcoverage and capacity [2][3] It should be

noted that suitableenergy efficiency for the UAV-

assisted ommunication systemachieves paramount

importance in the overall performance ofthe system

Efficient energy consumption results in

enhancedairtime for the communication system

improving bitsJoulesfor a given energy level

Furthermore coverage and capacityof an aerial cell

are attributed to many factors such as

thetransmission power antenna gains UAV

altitude deploymentenvironment and prominently

radio access technology [4]

4G is the fourth generation of broadband

cellular network technology succeeding 3G and

besides the popular techniques in 3G4G ie

TDMAWCDMAOFDMA a new radio access

technology NOMA is also developed by researchers

to be used in communication networks due to its

capability in increasing the system capacity

Recently non-orthogonality based system designs

are developed to be used in communication

networks and have gained significant attention of

researchers Hence multiple access (MA) techniques

can now be fundamentally categorized as orthogonal

multiple access (OMA) and non-orthogonal

multiple access (NOMA) In OMA each user can

exploit orthogonalcommunication resources either

within a specific time slot frequency band or code in

order to avoid multiple access interference The

previous generations of networks have employed

OMA schemes such as frequency division multiple

access (FDMA) of first generation (1G)time

division multiple access (TDMA) of 2G code

division multiple access (CDMA) of 3G and

orthogonal frequency division multiple access

(OFDMA) of 4G

In NOMA multiple userscan utilize non-

orthogonal resources concurrently by yielding a high

spectral efficiency while allowing some degree of

multiple access interference at receivers Recently

NOMA reputations have climbedsharply as a

fundamental solution to the challenges

encompassingthe next generation wireless networks

[5][6]NOMA has been proved to exhibit improved

spectral efficiencybalanced and air access as

compared to OMAtechnologies[6] with the ability

to cater for multipledevices in the same frequency

time or code resource thusproviding efficient access

to massive connected devices Furthermore NOMA

is also instrumental in reducingthe interference by

employing orthogonal resources as inOrthogonal

Frequency Division Multiple Access

(OFDMA)[7][17] or by sharing a single beam

between multiple users forintra-cluster access and

using NOMA for inter-cluster access[18]Current




studies have focused on provisioning Air to

Ground(A2G) communication services mainly

through placement optimization under various

viewpoints in literature The performance of UAV

based communication systems hasalso been

addressed for the underlaid Device to Device(D2D)

deployment scenario This work assumed

interferenceraised by D2D network nodes without

considering the presenceof terrestrial BS

Additionally there have been a fewstudies

discussing the performance of NOMA for UAV

basedcommunication system[8] A NOMA enabled

fixedwingUAV deployment was proposed in [8] to

support coveragefor ground users situated outside

BS offloaded location

In general NOMA schemes can be

classified into two types power-domain

multiplexing andcode-domain multiplexing In

power-domain multiplexing different users are

allocated[7][8][9][6][5][1][10] differentpower

coefficients according to their channel conditions in

order to achieve a high systemperformance In

particular multiple usersrsquo information signals are

superimposed at the transmitterside At the receiver

side successive interference cancellation (SIC) is

applied for decoding thesignals one by one until the

desired userrsquos signal is obtained providing a good

trade-offbetween the throughput of the system and

the user fairness In code-domain multiplexing

different users are allocated different codes and

multiplexed over the same time-frequencyresources

such as multi-user shared access (MUSA) sparse

code multiple access (SCMA) and low-density

spreading (LDS) In addition to power-domain

multiplexing and codedomain multiplexing there are

other NOMA schemes such as pattern division

multiple access(PDMA) and bit division

multiplexing (BDM) Although code-domain

multiplexinghas a potential to enhance spectral

efficiency it requires a high transmission bandwidth

andis not easily applicable to the current systems

On the other hand power-domain multiplexinghas a

simple implementation as considerable changes are

not required on the existing networksAlso it does

not require additional bandwidth in order to improve

spectral efficiency Inthis paper the prime focusis on

the power-domain NOMAAlthough OMA

techniques can achieve a good system performance

even with simple receiversbecause of no mutual

interference among users in an ideal setting they

still do not have theability to address the emerging

challenges due to the increasing demands in future

networks andbeyond

The superiority of NOMA over OMA can

besummarized as follows

_ Spectral efficiency and throughput In OMA such

as in OFDMA a specific frequencyresource is

assigned to each user even it experiences a good or

bad channel conditionthus the overall system suffers

from low spectral efficiency and throughput In

contrary inNOMA the same frequency resource is

assigned to multiple mobile users with good and

bad channel conditions at the same time Hence the

resource assigned for the weak user isalso used by

the strong user and the interference can be mitigated

through SIC processesat usersrsquo receivers Therefore

the probability of having improved spectral

efficiency and ahigh throughput will be considerably

increased

_ User fairness low latency and massive

connectivity In OMA for example in OFDMAwith

scheduling the user with a good channel condition

has a higher priority to be servedwhile the user with

a bad channel condition has to wait to access which

leads to a fairnessproblem and high latency This

approach cannot support massive connectivity

HoweverNOMA can serve multiple users with

different channel conditions simultaneously

thereforeit can provide improved user fairness lower

latency and higher massive connectivity

_ Compatibility NOMA is also compatible

with the current and future communication

systemssince it does not require significant

modifications on the existing architecture For

exampleNOMA has been included in third

generation partnership project long-term

evolutionadvanced (3GPP LTE Release 13)

Figure 1Pictorial comparison of NOMA Vs OMA

Although NOMA has many features that

may support next generationsit has some limitations

that should be addressed in order to exploit its full

advantage set Thoselimitations can be pointed out

as follows In NOMA since each user requires to

decode thesignals of some users before decoding its

own signal the receiver computational

complexitywill be increased when compared to

OMA leading to a longer delay Moreover

informationof channel gains of all users should be

fed back to the base station (BS) but this results in

asignificant channel state information (CSI)

feedback overhead Furthermore if any errors

occurduring SIC processes at any user then the error

probability of successive decoding will beincreased

As a result the number of users should be reduced to




avoid such error propagationAnother reason for

restricting the number of users is that considerable

channel gain differencesamong users with different

channel conditions are needed to have a better

network performance

IV NOMA UPLINK AND DOWNLINK

SCENERIO SIMULATION ANALYSIS In this section an overview of NOMA in

downlink and uplink networks is introduced

throughsignal-to-interference-and-noise ratio (SINR)

and sum rate analyses Then high signal-to-

noiseratio (SNR) analysis has been conducted in

order to compare the performances of OMA

andNOMA techniques[10]

A Downlink NOMA Network

At the transmitter side of downlink NOMA

network as shown in Fig 2 the BS transmits

thecombined signal which is a superposition of the

desired signals of multiple users with different

allocated power coefficients to all mobile users At

the receiver of each user SIC process isassumed to

be performed successively until userrsquos signal is

recovered Power coefficients ofusers are allocated

according to their channel conditions in an inversely

proportional mannerThe user with a bad channel

condition is allocated higher transmission power

than the one which has a good channel condition

Thus since the user with the highest transmission

power considers the signals of other users as noise

and recovers its signal immediately without

performing anySIC process However other users

need to perform SIC processes In SIC each userrsquos

receiverfirst detects the signals that are stronger than

its own desired signal Next those signals

aresubtracted from the received signal and this

process continues until the related userrsquos own signal

is determined Finally each user decodes its own

signal by treating other users with lower

powercoefficients as noise The transmitted signal at

the BS can be written as

s = aiPsxi

L

i=1

where xi is the information of user i (Ui)

with unit energy Ps is the transmission power atthe

BS and ai is the power coefficient allocated for user

i subjected to ai = 1Li=1 and a1gea2gehellip geaL since

without loss of generality the channel gains are

assumed to be ordered as h1 2 le h2 2 le⋯ hL 2 where hL is the channel coefficient of Lth

user based on NOMAconcept The received signal

at lth user can be expressed as follows

y1 = hls + nl = hl aiPsxi + nlL

i=1

where nlis zero mean complex additive Gaussian

noise with a variance of σ2

(1) SINR analysis By using (2) the instantaneous

SINR of the lth user to detect the jth user jle l

with jne L can be written as

SINRl = alγ hl 2

γ hl 2 aiLi=l+1 + 1

Where γ = Psσ2 denotes the SNR

(2) Sum rate analysis After finding the SINR

expressions of downlink NOMA the sumrate

analysis can easily be done The downlink

NOMA achievable data rate of lth user can

beexpressed as

RlNOMA-d

= log2 1 + SINRl = log2(1 +alγhl2γhl2 i=l+1Lai+1

B Uplink NOMA Network

In uplink NOMA network as depicted in

Fig 3 each mobile user transmits its signal to the

BS At the BS SIC iterations are carried out in order

to detect the signals of mobile users By assuming

that downlink and uplink channels are reciprocal and

the BS transmits power allocation coefficients to

mobile users the received signal at the BS for

synchronous uplink NOMA can be expressed as

r = hi aiPxi + n

L

i=1

where hi is the channel coefficient of the ith

user Pxi is the maximum transmission power

assumed to be common for all users and n is zero

mean complex additive Gaussian noise with a

variance of σ2

Figure 2Downlink NOMA network




Figure 3 Uplink NOMA network

1) SINR analysis The BS decodes the signals of

users orderly according to power coefficientsof

users and then the SINR for lth user l ne 1 can

be given by

SINRl =alγ hl 2

γ ai hi 2 + 1lminus1i=1

where γ =P

σ2

2) Sum rate analysis The sum rate of uplink

NOMA when γ minus infincan be written as

Rsum NOMA-u asymp log2(γ hl 2L

l=1

C Comparing NOMA and OMA

The achievable data rate of the lth user of OMA for

both uplink and downlink can be expressed

RsumOMA = αl log2(1 +

βlγ hl 2

αl)L

l=1

For the sake of simplicity sum rates of

uplink NOMA and OMA can be compared for

twousers Then using both the sum rate of uplink

NOMA and OMA at high SNR can beexpressed

respectively as

RsumNOMAasymp log2 γ h1 2 + γ h2 2

Here we notice ROMA

sumle RNOMA

sum

Fig shows that NOMA outperforms OMA in terms

of sum rate in both downlink and uplinkof two

user networks

V SIMULATION RESULTS

The Comparative analysis of modelling

Downlink and Uplink NOMA in comparison with

OMA is simulated and findings are presented that

shows superiority of NOMA over OMA with better

spectral efficiency for simulation parameters taken

as power allocation coefficients a1=06 a2=04 and

channel responses h1 2

=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK

Figure 5 NOMA DOWNLINK

VI CONCLUSION This paper investigated an account of

NOMArsquos applicability for UAV-assisted

communication systems NOMA schemes are

proposed to improve the efficient usage of limited

network sources OMA based approaches that use

time frequency or code domain in an orthogonal

manner cannot effectively utilize radio resources

limiting the number of users that can be served

simultaneously In order to overcome such

drawbacks and to increase the multiple access

efficiency NOMA technique has been recently

proposed Accordingly users are separated in the

power domain Such a power domain based multiple

access scheme provides effective throughput

improvements depending on the channel conditions

The crucial need of UAV communication of

optimum utilization of available licensed spectrum

bandwidth is considered here and simulation results

taken presented that NOMA performs better than

OMA while fulfilling individual user-rate constraint

for both users The research work can be further

carried out investigating joint power and phase




allocation of UAV nodes deployment for efficient

operations

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[15] P F a K B L Y Dong High-speed railway

wireless communications efficiency vs fairness

IEEE Transactions on Vehicular Technology vol

63 no 2 pp 925-930 march 2014

[16] T R a Z H Z Chang Queueing game for

spectrum access in cognitive radio networks

IEEE Communications Letters vol 19 no 11 pp

2017-2020 June 2015

[17] Z C L T R a Z H F I Yun Hu Service

Provisioning and User Association for

Heterogeneous Wireless Railway Networks IEEE

Transactions on Communications 2017

[18] H S W Tianti Chen Optimal Scheduling for

Wireless On-Demand Data Packet Delivery to

High-Speed Trains IEEE Transactions on

Vehicular Technology vol 64 no 9 pp 4101 -

4112 september 2015

Pankaj Patel Migration from 4g LTE to Advanced PHY Techniques for Unmanned Aerial

Vehicle Communication International Journal of Engineering Research and Applications

(IJERA) Vol 09 No04 2019 pp 49-54

INTERNATIONAL JOURNAL OF SCIENTIFIC amp TECHNOLOGY RESEARCH VOLUME 9 ISSUE 04 APRIL 2020 ISSN 2277-8616

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Improving Of Physical Layer Insecurity Of The

Non Orthogonal Multiple Access System

Pankaj M Patel Prof Dr Chetan B Bhatt

Abstract The key aspect of the NOMA (power domain non orthogonal) is the user possibility for decoding the messages belonging to another pair users

on similar resources The method interprets a security threat especially in the case where the base station serves the users with various security

clearance or untrusted users The main aspect of NOMA is to serve the multiple users upon the similar radio resources at the minimal inter user

interference expense The system not only permits the serving of particular users with high efficient bandwidth but also permits the scheduling more type

of users than the timely available users In this study we investigated the secrecy outage probability (SOP) and OP in the both two user and multi user

NOMA system where the BS is supposed to pair a trusted or legitimate user with other untrusted users because of the un even distribution of the

untrusted and trusted users in the cell SIC the successive interference cancellation was then implemented at the receiver side for decoding the

message signals With the application of NOMA concept the study investigated the pair outage behavior under the SOP constraints on the trusted users

In specific the SOP and OP of the concerned U1 were obtained in the closed type of expressions The study also provided the understanding the

possibility of obtaining an optimal outage efficiency for pairing under the SOP constraints With certain numerical simulations the study verified the

effectiveness of the analytical derivations with respect to various scenarios

Index Terms NOMA Secrecy outage Probability Successive Interference Cancellation bandwidth channel state information etc

mdashmdashmdashmdashmdashmdashmdashmdashmdashmdash mdashmdashmdashmdashmdashmdashmdashmdashmdashmdash

1 INTRODUCTION The physical layer security and non-orthogonal multiple

access was regarded as the encouraging techniques for the

processing of wireless communication network systems Today

the combination of the two significant communication methods

was studied to guarantee a spectral efficient and secure

wireless transmission Most of the prevailing works

predominantly concentrated on the optimization and efficiency

of the PLS in the existence of untrusted relay nodes and

external eavesdroppers(Arafa et al 2019a)But there occurs a

gap in the theoretical studies to describe the ease of obtaining

the enhanced efficiency in the existence of untrusted users

Recently the network traffic amount have greatly enhanced

particularly with the updated growth in IoT applications in

future To rectify the huge traffic demand upcoming wireless

networks must deliver a best spectral effectiveness and large

connectivity (Sun et al 2018) NOMA is regarded as the best

technology in which various NOMA technique exhibit similar

concept of providing several users at the similar frequency and

time The famous NOMA types are code domain and power

domain that provided enhanced efficiency when compared

with the existing techniques The paper adopted the power

domain on the basis of super position coding (transmitter side)

at the SIC (receiver side) Hence the users could possess the

key for the messages of other users and thereby utilize SIC for

removing the interference (Cao et al 2019) (Zhao et al

2018) Hence various NOMA methods was proposed for

allowing the adjacent users to perform as a relay for improving

the efficiency of the weak users through the resending of

decoded data in a next time slot The weak user could utilize

the MRC technique to integrate the information achieved in

different time slots In addition obtaining a secured

communication is a crucial problem over the vulnerable

wireless networks to security threats mainly because of the

broadcasted transmission nature

The study investigated the secrecy performance and outage

with the untrusted user(Furqan et al 2019) The main aspect

of the study is to analyze the feasibility of achieving the OP of

the pair under a trusted user Because of the decoding facility

and spectrum sharing of SIC the untrusted user could perform

as a eavesdropper

Figure 1 Representation of Base station

Figure 1 depicts the representation of base station The main

aim of the proposed system defined as

bull To investigate the outage probability of the proposed

system

bull To investigate the SOP of the proposed system

bull To derive the accurate expression of the outage

probability for all kind of scenarios and closed form of

expressions for few special cases and verifying them

numerically for yielding a better outage efficiency

2 RELATED WORKS This section describes the different existing techniques and

methods related as our proposed system (Cao et al

2019)suggested two kinds of relay selection process denoted

as AF (amplify and forward) and DF (decode and forward) on

the basis of AORS and DORS for achieving secure and

reliable NOMA systems under the untrusted users The study

derived the accurate and asymptotic closed form of the SOP

expressions and the PSCP obtained by the two methods and

investigated the optimized feature of the two methods The

____________________________________

bull PANKAJ M PATEL is currently pursuing PHD program in Electronics

amp Communication in Gujarat Technological University E-mail

pankajmphd24gmailcom


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complete analysis and the simulation results represented that

both the AORS and DORS characteristically outperformed the

benchmark system apart from obtaining the similar SOP and

the required PSCP at very high Signal to noise ratio (Zhang et

al 2018)Investigated the power allocation and joint subcarrier

issue for NOMA ndashAF two-way relay networks with restrictions

The study focused to optimize the obtainable secrecy

efficiency by designing jointly the SC task power allocation

and user pair scheduling The paper suggested a SCAS-1

technique by assuming the appropriate information about the

channel state information in the relay station followed by the

formulation of SCAS-2The secured power allocation issue is

structured as a convex programming issue and then resolved

by in-depth point techniques The results of simulation

explained that the efficiency of the suggested SSPA algorithms

with and without CJ respectively (Arafa et al

2019b)Considered a downlink system where the base station

is connecting with two appropriate users in two various

scenarios in the unsecured environments which are the

presence of the eavesdropper and untrusted relay

communication In the first process several trusted

cooperative relays is engaged for assisting with the base

station transmission and protect the corresponding signals

from the eavesdropper Several relay methods are framed and

investigated for the following process which are forward and

decode cooperative jamming and AFFor all the technique

secured beam forming signals were formulated at the relays

for maximizing the obtainable secret rate areas For the next

process with untrusted relay the obtained secrecy rate areas

obtained for two various relay schemes which are AF and CF

under two various operation modes In the first process the

prescribed users will receive the signals from the untrusted

relay and the base station for decoding the messages The

study depicted that the efficient relay scheme is highly

dependent on the parameters of the system especially the

nodal distance and the secrecy rate area (Sun et al

2018)Studied the algorithm for resource allocation for MISO

systems where the full duplex BS serve several half duplex

downlink and uplink users on the similar subcarrier The

allocation of the resource have been optimized for maximizing

the weight system output whereas the leakage of information

was restricted and an artificial noise was induced for granting

secured communication with respect to potential

eavesdroppers The study formulated a novel non-convex

optimization issue by considering the imperfect CSI of the

channels and requirements of QoS of legitimate users The

simulation results stated the efficiency of the optimal algorithm

was related to the suboptimal algorithm Apart from that the

suggested MISO NOMA technique not only guarantee uplink

and downlink communication purpose for security but delivers

a characteristic rate of system secrecy when compared with

the conventional MISO and other two baseline methods

(Dang et al 2017)Analysed the outage efficiency of various

multicarrier relay selection techniques for 2 hop OFDM system

in Poisson relay fields The study concentrated on DF relay

systems with more selection schemes The accurate

expressions for the OP are provided in integrals generally

Apart from that asymptomatic derivatives for OP in the SNR

region in the fixed circle area are predicted for both relay

selection techniques in closed forms Consequently several

significant factors that are linked to the cooperative network

were examined comprising OP ratio of two selection

techniques diversity and subcarrier optimization output In

conclusion a structure to analyze the OP of OFDM with

spatially random relay have been constructed that could be

easily altered for analyzing same case with various forwarding

protocols channel conditions and location distributors (Dang

et al 2018)Proposed a full duplex OFDM ndashD2D system in two

hop network where DF relays help the transmission from DUE

transmitter to DUE receiver The study also investigated the

OP issue by integrating the transmit power within the DUE

relays and transmitter and to deliver a suboptimal solution that

can improve the outage performance The investigations are

validated by Monte Carlo simulations These results described

could furnish an insight into full duplex OFDM system and

guides for the application in the next generation network

(Kokshoorn et al 2016) suggested a robust channel algorithm

for mmWave systems on the basis of novel overlapped pattern

design With the use of finite measurements the study

depicted that this decreased measurements was found ENR of

25 dB to obtain the similar PEEFor the appropriate channel

with quickly altering channel information the price might be

acceptable for improving the speed of estimation The study

also proposed a robust channel estimation algorithm where

the additional calculations are carried out when expecting

more estimation error The study depicted that the channel

could be measured more effectively resulting in noteworthy

gains upto 6 dB when comparing with the existing algorithm

(Ali et al 2016) described the variations in the principles of

downlink and uplink NOMA transmissions in a wireless

system The study formulated a maximization issue in a cell

like the user clustering and power allocations Because of the

integral nature of the formulated programming issue the study

solved the issue in to steps which are grouping of users into

clusters and then to optimize the corresponding power

allocations The study proposed a sub optimal scheme that

exploited the gain variations in NOMA groups and clusters into

multiple and single clusters for enhancing the sum-throughput

The results compared the efficiency of OMA and NOMA in

different network scenarios (Lv et al 2017) investigated a

MCR-NOMA where the multicast user functions as relays to

enhance the efficiency of both secondary and primary

networks On the basis of the available CSI three various

secondary user schedule techniques for processing MCR-

NOMA were depicted For evaluating the system efficiency the

study derived the closed form of expressions of OP and order

of diversity for both the networks It has been described that

more spatial temporal diversity could be obtained by using the

CSI for scheduling of the secondary user (Liu et al 2016)

considered a MIMO ndashNOMA scenario for investigating a

dynamic clustering issue in an logical perspective To resolve

the problem of optimization issue three algorithms named top

down A and B bottom up were suggested for realizing various

complexity tradeoff and worst user throughput The study

noted that the top down B algorithm could obtain a better

tradeoff between throughput and complexity amongst the

applied procedures (Fianu and Davis 2018) investigated

three various rules of allocation and demonstrated the optimal

policy as an available inventory function The study also

provided the country level estimation of requirements that are

not met and the determination of the probability distribution

linked with the total undeserved counties The study have

been done for depicting the policy of allocation with respect to

effectiveness and equity (Hou et al 2018) studied the socio


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graphical impact on the mobile video services and thereby

suggested a CTMDP on the basis of resource allocation

technique by considering social graphs as the constraints

With the use of relative value an optimized policy could be

achieved that aimed at increasing the reward regarding the

average system The simulation depicted that the suggested

CTMDP obtained an increased efficiency against the state of

art methods

3 PROPOSED WORK

Fig 2 Proposed flow depicting the overall mechanism

The proposed(Interference mitigation using POMDP) overall flow

is depicted in the figure 2 After setting up of the base station the

distance between the base station and the user was determined

and if the distance is less than 200 meters it is decided as trusted

users and if it is greater than 200 m it is defined as untrusted

users In case of untrusted users the channel state information is

subjected to POMDP (Partially observable Markov Decision

Process) followed by resource allocation The performance

analysis have been done after the system The work considered

a NOMA oriented cellular setup provided with a base station at

the centre and two users as shown in the figure 2 The adjacent

(near) user possess high level of security clearance that is

required for securing with physical layer from the low

securityuntrusted clearance user (U2) that is located at a faraway

distance from the base station P is defined as the maximum

transmit power level (base station)In this paper it is assumed that

all the network nodes are installed with single antenna and further

all the channels are considered to be identical independently

quasi static with Rayleigh distribution with respect to distribution

119862119873(0 120575 frasl

120596 frasl

) In which 120575 is the distance in-between the BS

and nodes 119880 Here path-loss exponent and path-loss constant is

represented as 120572 and 120596 In addition it is assumed that base

station predicted the user location so that a better CSI is

obtainable at base station that is involved in pairing the users

The base station transmits the superimposed mixture

119909 = radic119905 119904 + radic1 minus 119905 119904

In which 119904 119904 are the unit power signals received by users 119880 and

119880 respectively 119905 is the power

allocation coefficient for the adjacent user

119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899

where ℎ ℎ - the channel gain linked with the

small-scale fading from the base station to users 119880 and 119880

respectively 119899 and 119899 are the extra white Gaussian noise with

variance and zero mean 1198730 and it is assumed that 120588 = 1198751198730 is

the BS convey signal-to-noise ratio (SNR) In NOMA technique

farther user that possess more power

could decode its own signal by considering the adjacent signal as

a noise without decoding the adjacent user message In the

preceding equation it is assumed that U1 first decode the weak

signal followed by decoding its own signal with SICU2 which is

the untrusted user attempted to decode the near user message

after the decoding of the adjacent user messages after the

process of decoding its own message with SICHence the

following equation have been achieved

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+

where 119878119868119873119877 represented the signal-to-interference-plus-noise-

ratio of user 119898 that was decoded by 119880 for 119898119899120598119894 2+ and the

channels gain of 119880 denoted by |ℎ |

followed an exponential distribution

with the parameter 120577 = 120596 120575

Problem Formulation

Hence the base station should achieve and serve a better

communication for the users who are susceptible to security

threat from untrusted user the proposed system defined two

kinds of QoS efficiency measures that could be regarded to be

important for framing the issue In specific the study defined a pair

of OP to check the reliability of the QoS satisfaction In general

the pair OP is stated as the probability in which the obtainable

data rates dor the users equal to or greater than the least target

threshold The next metric also called as the SOP is the

probability that the non negative secrecy capacity obtained by the

trusted user is more than the threshold value

The following issue aimed at reducing the pair OP subjected to a

SOP factor for the user U1 that is provided by

min

119875

0 lt 119905 lt 05

119878119874119875 le 120573

in which 119875 119878119874119875 and 120573 are the pair OP SOP(119880 ) and the

permissible SOP threshold

4 PERFORMANCE ANALYSIS

Derivation of the Pair OP

With the use of Shannonrsquos capacity formula and considering

119862 and 119862

as the threshold capacities of users 119880 and

user 119880 respectively the OP of the pair could be provided

by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


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119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601

For having 120601 gt 120601 the constraint on

the power allocation factor (t) needs to be satisfied

(119905 gt

) and for this case 119876 could be obtained as

follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601

Like case 1 it was stated that opposite constraint on

a as (119905 lt

) and

119876 can be derived as follows

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

The OP of the NOMA pair

119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

Derivation of SOP of 119880

With Shannonrsquos capacity formula the secrecy rate of

user 119880 was provided by

119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))

119878119862 is the non-negative secrecy capacity of 119880 Provided the

secrecy capacity in the SOP of 119880 is

119878119874119875 = 1 minus 120584119890

119860 =

120584 =

119879 - the user 119880 secrecy target rate

Theorem 1

Outage-optimal power allocation factor

119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591

The minimum power allocation factor (119886 )

119905 =

(

)

The optimal OP of the NOMA pair under the SOP constraint

=

( )

( ( ))119890

( )

That is lt 0whih meant that the U1 (SOP) is a reducing function

Of t that results in the optimal power allocation factor that is

greater than 119905 for the satisfaction of secrecy constraining

factorPartially observable Markov decision process S is

represented as statesLet D is the channel features which is

consider here as actions the conditional transition probability

between states is regarded as T Reward function R is

calculated as the prediction of maximum capacity channel with

respect to data rate r = R(S x D) the agent receives an

observation o ϵ 120118 o isin Ω display style oin Omega that

depended on the new environment state S and on the just

took action d with the probability O(o|s d)

Reward received at time t is conveyed as r = R(S x D)

H is the belief states over POMDP states


119903 = 119877(119867 x 119863) is the reward function on the belief states

119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =

1 if the belief update with arguments h d o returns h 0 otherwise

The reward function is updated on the basis of the belief MDP

r (h d) = sum h(s) R(s d) isin

the agent focus on the largest expected immediate rewardin

other words the maximum capacity channel The section

analyse the accuracy of the analytical derivations under

various settings

Figure 3 The feasible pairing

The SOP of U1 with the increasing untrusted user U2 and

distance (d2) for several BS transmits Signal to Noise Ratio

at 120588 = minus20minus1020 119889119861is depicted in with a=005 and 01 and

d1=200m is depicted in the figure The results stated that the

U1(SOP) is a gradually reducing function as per d2 that

implies that the increasing value of d2 leads to the

improvement of the SOP of U1 Since the provided constant

threshold ϵ in SOP restraint U2must be situated at a larger

space when compared with threshold value to obtain the SOP

of U1 Apart from that it is normal that the high the target

secrecy rate rises the SOP of U1


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Figure 4 The Secrecy outage probability

Feasible Pairing in th SOP of pair OP and U1 with the

enhanced power allocation factor (a) in which d2 = 700 m d1

= 200 m 120588 = 15 dB and ϵ = 01 The results depicted that the

the pair OP and SOP of user U1 with increased a for two (d2)

various distances of the (U2) untrusted user The results

approve the convex nature of the pair OP and the SOP curve

is gradually decreasing on the basis of a Generally during the

increase in a the power assigned to the weak user message

decreases that minimize the ability of U2 for discriminating the

superior positioned signals thereby improving the SOP of U1

Figure 5 The Pair outage probability

Pair OP in case of rising U2 untrusted user in distance (d2)

for different base station transfer the signal to noise ratio(120588 =

5 15 25 dB) where a = 015 and d1 = 200 m

Figure 6The infeasible pairing of secrecy outage

probability of the pair OP and U1

The infeasible pairing of SOP (U1) and the pair outage

probability with the enhanced allocation of the power ad1(200

m)d2(300 m)120588 = 15dB and ϵ = 0

The figure 6 depicted that the

The figure 6 shows the similar plotting of the data by altering

the untrusted user location by transferring it to a BS closer

distance (d2 = 300 m) It also depicted that the U1 SOP

constraint of is disrupted at a because the SOP is more than ϵ

The accuracy is well-matched and verified with all range of

numerical simulation The results noticed that the efficiency is

based on the comparative locations of the two user with the

base station

Figure 7 The figure 7 depicts that SNR versus strictly

positive secrecy rate

The observed graph proves that the secrecy capacity

outperforms the existing techniques The proposed precoding

application increases the performance of the system The

transmission power of the system is the power required to

transmit a particular data When there is an increase in the

number of users there is the possibility of inference in the data

transmission and hence the efficiency of the data rate may be

affected Depending on these instances the efficiency of the

antenna capacity to withheld and accommodate the data

determined

Figure 8 The power radiated by BS antenna

In the figure 8with respect to the simulation setup the

precoding methods are performed based on the radiated

power per BS antenna is depicted The results observed the

better efficiency of the proposed system The proposed proves

to be better when compared with existing linear precoding

methods in the prescribed three metrics thereby stating that

MRT may be utilized for the the examination of the secrecy

capacity Our proposed technique spends less radiatated

power thereby increasing the overall capacity of the system

5 CONCLUSION The NOMA system decodes the messages of other user pairs

on the similar resources thereby promoting user possibility

The technique interprests a security threat in which the BS

serves the untrusted users The study analysed the SOP and

OP in both multi user and two user NOMA system in which the


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base station pairs the trusted user in closed type of

expressions The proposed (Interference mitigation using

POMDP) also enable the understanding of possibility of

achieving outage optimal efficiency to pair under SOP

constraints The numerical verifications verified the efficiency

of the analytical derivations

6 REFERENCES [1] ALI M S TABASSUM H amp HOSSAIN E 2016

Dynamic user clustering and power allocation for

uplink and downlink non-orthogonal multiple access

(NOMA) systems IEEE access 4 6325-6343

[2] ARAFA A SHIN W VAEZI M amp POOR H V

2019a Secure relaying in non-orthogonal multiple

access Trusted and untrusted scenarios IEEE

Transactions on Information Forensics and Security

15 210-222


2019b Secure relaying in non-orthogonal multiple



[4] CAO K WANG B DING H LI T amp GONG F

2019 Optimal Relay Selection for Secure NOMA

Systems under Untrusted Users IEEE Transactions

on Vehicular Technology

[5] DANG S CHEN G amp COON J P 2018

Multicarrier relay selection for full-duplex relay-

assisted OFDM D2D systems IEEE Transactions on

Vehicular Technology 67 7204-7218

[6] DANG S COON J P amp CHEN G 2017 Outage

performance of two-hop OFDM systems with

spatially random decode-and-forward relays IEEE

Access 5 27514-27524

[7] FIANU S amp DAVIS L B 2018 A Markov decision

process model for equitable distribution of supplies

under uncertainty European Journal of Operational

Research 264 1101-1115

[8] FURQAN H M HAMAMREH J amp ARSLAN H

2019 Physical Layer Security for NOMA

Requirements Merits Challenges and

Recommendations arXiv preprint arXiv190505064

[9] HOU L ZHENG K CHATZIMISIOS P amp FENG Y

2018 A Continuous-Time Markov decision process-

based resource allocation scheme in vehicular cloud

for mobile video services Computer

Communications 118 140-147

[10] KOKSHOORN M CHEN H WANG P LI Y amp

VUCETIC B 2016 Millimeter wave MIMO channel

estimation using overlapped beam patterns and rate

adaptation IEEE Transactions on Signal Processing

65 601-616

[11] LIU Y ELKASHLAN M DING Z amp

KARAGIANNIDIS G K 2016 Fairness of user

clustering in MIMO non-orthogonal multiple access

systems IEEE Communications Letters 20 1465-

1468

[12] LV L CHEN J NI Q amp DING Z 2017 Design of

cooperative non-orthogonal multicast cognitive

multiple access for 5G systems User scheduling and

performance analysis IEEE Transactions on


[13] SUN Y NG D W K ZHU J amp SCHOBER R

2018 Robust and secure resource allocation for full-

duplex MISO multicarrier NOMA systems IEEE

Transactions on Communications 66 4119-4137

[14] ZHANG H YANG N LONG K PAN M

KARAGIANNIDIS G K amp LEUNG V C 2018

Secure communications in NOMA system

Subcarrier assignment and power allocation IEEE

Journal on Selected Areas in Communications 36

1441-1452

[15] ZHAO T LI G ZHANG G amp ZHANG C-X

Security-Enhanced User Pairing for MISO-NOMA

Downlink Transmission 2018 IEEE Global

Communications Conference (GLOBECOM) 2018

IEEE 1-6

copyPankaj Manubhai Patel

DECLARATION













Place Ahmedabad

CERTIFICATE












Place Ahmedabad







the MPhil Course)







(PH001)


(Core Subject)

(PH002)

BC BB























Place Ahmedabad



Place Ahmedabad

132



Submitted 2021-09-22 091500

Submitted by


Similarity 1




Fetched 2021-09-22 0916001




2


Fetched 2019-11-28 1244286



Fetched 2020-11-03 060445

1


1

















the thesis













license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6

DECLARATION













Place Ahmedabad

CERTIFICATE












Place Ahmedabad







the MPhil Course)







(PH001)


(Core Subject)

(PH002)

BC BB























Place Ahmedabad



Place Ahmedabad

132



Submitted 2021-09-22 091500

Submitted by


Similarity 1




Fetched 2021-09-22 0916001




2


Fetched 2019-11-28 1244286



Fetched 2020-11-03 060445

1


1

















the thesis













license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6

CERTIFICATE












Place Ahmedabad







the MPhil Course)







(PH001)


(Core Subject)

(PH002)

BC BB























Place Ahmedabad



Place Ahmedabad

132



Submitted 2021-09-22 091500

Submitted by


Similarity 1




Fetched 2021-09-22 0916001




2


Fetched 2019-11-28 1244286



Fetched 2020-11-03 060445

1


1

















the thesis













license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6







the MPhil Course)







(PH001)


(Core Subject)

(PH002)

BC BB























Place Ahmedabad



Place Ahmedabad

132



Submitted 2021-09-22 091500

Submitted by


Similarity 1




Fetched 2021-09-22 0916001




2


Fetched 2019-11-28 1244286



Fetched 2020-11-03 060445

1


1

















the thesis













license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6





















Place Ahmedabad



Place Ahmedabad

132



Submitted 2021-09-22 091500

Submitted by


Similarity 1




Fetched 2021-09-22 0916001




2


Fetched 2019-11-28 1244286



Fetched 2020-11-03 060445

1


1

















the thesis













license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6

132



Submitted 2021-09-22 091500

Submitted by


Similarity 1




Fetched 2021-09-22 0916001




2


Fetched 2019-11-28 1244286



Fetched 2020-11-03 060445

1


1

















the thesis













license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6

















the thesis













license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6



license





Place Ahmedabad



Place Ahmedabad

Seal

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6

i

ABSTRACT


























ii





iii

Acknowledgment






















vi



5G Fifth Generation

A2G Air to Ground



BS Base Station



CR Cognitive Radio







FR Floating Relay







vi





MI Mobile Internet




















vi









vii

List of Figures

Figure Title Page

No



6


architecture

8



















viii

List of Tables

Table Title Page

No



13




ix

Table of Content

Sr

No

Title Page

No

I Abstract I




V List of tables V

1 Introduction 1






122 Tyews of UAVs 8







communication

16






17 Motivation 19




x




24 Summary 39









322 System Model 48




System

53



34 Summary 57



model

58



users

60


probability

62



64


431 Conclusion 65

432 Future scope 66

xi

5 References 67

8

Publications 78

1

CHAPTER -1

INTRODUCTION




























2














(UMTS) technology

















3


15bpsHz and 30bpsHz






networking





















4

































5
































6













2019)


disaster control





7































8








122 Types of UAVs



eavesdroppers



architecture






9



















BSs










10
















missions













impairment

11






























12


















13








(Kumar et al 2014)








layer in WSN



al 2014)


of the texts




14



node


2013)













hopping













15





















16








Wang et al 2019)


Communication


















17










maximized







1513 Compatibility






are as follows








18





















19

17 Motivation































20
































21










applications




















22








23

CHAPTER 2

LITERATURE REVIEW





























24

























random ROR scheme









25






























Feng et al 2018)



26




























et al 2017)




27


(Qin et al 2016)



























(Xie et al 2019)

28



















29




















et al 2016)









et al 2020)



30






















31





users







2018)








32

































33















studies

SR

No








34


of security





was availed























35








period is maximum



aerial vehicle UAV
















36





NOMA






was analyzed











security issues







37












consumption


optimize power















Less cost



38








anonymization


place





















39








allocation

24 Summary
























40





41

CHAPTER-3


COMMUNICATION






















σ ඥ119875119896 119878119896119870119896 =1 -------------------------------------- (1)



42



119910119896 = ℎ119896 σ ඥ119875119896 119878119896119870119896=1 + 119899119896 -------------------------- (2)

119910119890 = ℎ119890 σ ඥ119875119896 119878119896119870119896=1 + 119899119890 -------------------------- (3)




are identical

ie 12059012 = ⋯ = 120590119896

2 = 1205901198902












119878119868119873119877120587119896=

120574120587(119896)119875120587(119896)

1+120574120587(119896) σ 119875120587(119894)119896119894=119896+1

119896 lt 119870 --------------------(4)

119878119868119873119877120587119870= 120574120587(119870)119875120587(119870) --------------------------------------(5)

Were 120574120587(119896) =หℎ120587(119896)ห

2

1205901199062

൘

43


119898 le 119870 is given by

119878119868119873119877120587119896=

120574120587(119898)119875120587(119896)

1+120574120587(119898) σ 119875120587(119894)119896119894=119896+1

kltmle 119870 --------------(6)



119878119868119873119877120587macr

119896=

120574119890119875120587(119896)

1+120574119890 σ 119875120587(119894)119896119894=119896+1

klt119870 ----------------- ------(7)

119878119868119873119877120587macr

119896=

ȁℎ119890ȁ2119875120587(119896)

1205901198902 = 120574119890119875120587(119896) klt119870 ---------------------(8)

Where 120574119890=ȁℎ119890ȁ2

1205901198902൘





for the user π (k)













44


processes















45

119904 = σ 119886119894119875119904119883119894119871119894=1 -----------------------------------------------(1)








1199101 = ℎ119897119904 + 119899119897 = ℎ119897 σ ξ119886119894119875119904119883119894119871119894=1 + 119899119897 -----------------------------(2)



119895 ne 1

119878119868119873119877119871 = 1198861120574 ȁℎ1ȁ2120574ȁℎ1ȁ2൘ σ 119886119894 + 1119871

119894=119871+1 ------------------------(3)





1198771119873119874119872119860minus119889 = 1198971199001198922(1 + 119878119868119873119877119871) --------------------(4)

313 Uplink of NOMA





46

119955 = σ ℎ119894ඥ119886119894119875119909119894119871119894=1 +n ----------------------------------(5)







119878119868119873119877119871 = 119886119897120574ȁℎ119897ȁ2120574 σ 119886119894ȁℎ119894ȁ2 + 1119897minus1

119894=1൘ ----------------------------(6)



computed as

119877119904119906119898119873119874119872119860minus119906 asymp 1198971199001198922(120574 σ ȁℎ119897ȁ119871

119894=1 2 ------------------------ (7)

47




119877119904119906119898119874119872119860 = σ 120572 1198971199001198922120574(1 +

120573119897ȁℎ119897ȁ2

120572119897119871119894=1 ) --------------------------(8)




119877119904119906119898119873119874119872119860 asymp 1198971199001198922(120574 ȁℎ1ȁ2 + 120574ȁℎ2ȁ2 ------------------------- (9)


119873119874119872119860

Here we note 119929119956119958119950119926119924119912 le 119929119956119958119950

















48



















of the NOMA method

322 System Model







49


Here 119945119935119936 and ȁ119945119935119936ȁ2







119891ȁℎ119883119884ȁ2(119911) = ቀ1

ℷ119883119884ൗ ቁ 119890119909119901 (minus 119911

ℷ119883119884ൗ )

if zge 0 119900119905ℎ119890119903119908119894119904119890119891ȁℎ119883119884ȁ2(119911) = 0 -----------------(1)


ℷ119883119884= ൬119889119883119884

1198890൘ ൰

minus휀

ℒ ------------------(2)




eavesdroppers

50










51








119862119873(0 120575119898

minus120572

212059601 2Τ

)






119909119905 = ඥ1199051199041 + ඥ1 minus 1199051199042 ------------------------------- (3)



1199031 = ℎ1119909119905ξ119875 + 1198991 ------------------------------- (4)

1199032 = ℎ2119909119905ξ119875 + 1198992 ----------------------------------(5)



52



ൗ







11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2 ----------------(6)

11987811986811987311987722 =


119905ȁℎ1ȁ2+1120588 and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2 ----------------(7)

119879119900119905119886119897119904119894119899119903 = 11987811986811987311987721 1198781198681198731198771

1 119878119868119873119877221198781198681198731198771

2 -----------------(8)

Where 119930119920119925119929119950119951



parameter 120649119950=120654120782120633119950minus120630












53


System



119957119945 as the


could be offered by

119927119954 = 120783 minus 119928120783119961119928120784 in which 120649119950 = 120784119940119950119957119945

119950 isin ሼ119946 120784ሽ -------------(9)

empty120783 =120649120784

120646(120783+119957+120649120784119957) empty120784 =120649120783

120646119957

119928120783 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ 120782 lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 ------------------------(10)




follows

119928120784 = ൝119942119961119953 ቀ

minusempty120783

120649120784ቁ

120649120783

120649120783+120649120784+120649120783120649120784lt 119957 lt

120783

120783+119955120784

120782 119952119957119945119942119955119960119946119956119942 --------------(11)


on

t gt 1206491


119928120784 = ൝119942119961119953 ቀ

minusempty120784

120649120783ቁ 120782 lt

120649120783

120649120783+120649120784+120649120783120649120784

120782 119952119957119945119942119955119960119946119956119942 ---------------------(12)

54





E Eavesdropper



1198890 Space









scale




119878119868119873119877119898119899


55


1198750 Pair of OP

1198781198741198751 119878119874119875(1198801)






simulation process


Algorithm I


119862119873(0 120575119898minus120572 2Τ

1205961199001 2Τ

) where





119909119905 = ξ1199051199041 + ξ1 minus 1199051199042




1199031 = ℎ1119909119905ξ119875 + 1198991

1199032 = ℎ2119909119905ξ119875 + 1198992 where

56




119925120782


120646 = 119927119925120782





11987811986811987311987721 =


119905ȁℎ1ȁ2+1120588ൗ and 1198781198681198731198771

1 = 119905120588ȁℎ1ȁ2

11987811986811987311987722 =


119905ȁℎ2ȁ2+1120588ൗ and 1198781198681198731198771

2 = 119905120588ȁℎ2ȁ2

119879119900119905119886119897119904119894119899119903 = ሼ11987811986811987311987721 1198781198681198731198771

1 11987811986811987311987722 1198781198681198731198771

2ሽ

where 119930119920119925119929119950119951




Algorithm II



119955119943 = 119877(119878119909119863)



Reward function R



119926(119952ȁ119956prime 119941)


57

119903119891119905 = 119877(119878119909119863)119905




119955119943 = 119877(119867119909119863)




119861119891 ቀℎ 119889 ℎprimeቁ = 119875119903 (

119900120598120118

ℎprimeȁℎ 119889 119900) 119875119903(119900ȁ119889 ℎ) 119861119891


0119900119905ℎ119890119903119908119894119904119890

119903119891(ℎ 119889) = σ ℎ(119904)119877(119904 119889)119904isin119878

34 SUMMARY












58

CHAPTER 4





























59






















Parameters Values






60






No of Bits 100


SINR 5319 15305 5162

10247







61












62




120656 = 0





consumers of the BS










63








64





data determined








65






431 Conclusion




















results





66





algorithm POMDP







1

References
















series






Technology 69(2) 1942-1955






2













Research 264 1101-1115
















Supercomputing 1-28



6(2) 1731-1740

3










Systems 33(9) e4392






















4



















Technology














Access 5 17450-17464

5




























Network






6






Sons









Broadcasting












4202







7








Computers















57(10) 98-103



Computing 2018



Sensors 17(2) 377



26(5) 40-47

8



35862




















Sensors 20(4) 1047










9












310-313








27(4) 8-15



115568-115573









10














54(5) 36-42









20(5) 930-933



Technology 69(4) 3994-4005



6 34004-34017



11

PUBLICATIONS







ABSTRACT
















communication

----------------------------------------------------------------------------------------------------------------------------- ---------


----------------------------------------------------------------------------------------------------------------------------- ----------









































in section five













































as below













































(OFDMA) of 4G











































































networks andbeyond
















increased











































network performance



































s = aiPsxi

L

i=1










i=1






SINRl = alγ hl 2







beexpressed as

RlNOMA-d











r = hi aiPxi + n

L

i=1





variance of σ2









be given by

SINRl =alγ hl 2


where γ =P

σ2




l=1





βlγ hl 2

αl)L

l=1





respectively as


Here we notice ROMA

sumle RNOMA

sum



user networks









=0 DB h22=20 DB

parameters

Figure 4NOMA UPLINK




























operations




access 2018


























2016







2017











2003





31 no 07 pp 1258-1267 july 2013







63 no 2 pp 925-930 march 2014




2017-2020 June 2015









4112 september 2015



(IJERA) Vol 09 No04 2019 pp 49-54


2528

IJSTRcopy2020

wwwijstrorg
























































as a eavesdropper





system















____________________________________





2529

IJSTRcopy2020

wwwijstrorg






























































































































2530

IJSTRcopy2020

wwwijstrorg








art methods

3 PROPOSED WORK





















119862119873(0 120575 frasl

120596 frasl











119903 = ℎ 119909 radic119875 + 119899

119903 = ℎ 119909 radic119875 + 119899















119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119878119868119873119877 =

( )| |

| | frasl and 119878119868119873119877

= 119905 120588 |ℎ |

119879119900119905119886119897 = 119878119868119873119877 119878119868119873119877

119878119868119873119877 119878119868119873119877

+






Problem Formulation














min

119875

0 lt 119905 lt 05

119878119874119875 le 120573






119862 and 119862



by

119875 = 1 minus 119876 119909119876

in which

120591 = 2

119898 120598 119894 2+

120601 =

( )

120601 =


2531

IJSTRcopy2020

wwwijstrorg

119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 1 120601 gt 120601



(119905 gt


follows

119876 = exp (

)

lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890

Case 2 120601 lt 120601


a as (119905 lt

) and


119876 = exp (

) 0 lt 119905 lt

0 119900119905ℎ119890119903119908119894119904119890


119875 = 1 minus 119891(119905)119896 (119905)

lt 119905 lt

1 minus 119891(119905)119896 (119905) 0 lt 119905 lt

in which

119891(119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901

(

( ))

119896 (119905) = 119890119909119901




119878119862 = 119869 minus 119869

119869 = log (1 + 119879119900119905119886119897 (r (1)))

119869 = log (1 + 119879119900119905119886119897 (r (2)))



119878119874119875 = 1 minus 120584119890

119860 =

120584 =


Theorem 1


119905 = radic

( )

In which 119908 =

119908 =

119911 = 1 + 120591


119905 =

(

)


=

( )

( ( ))119890

( )

















119861 (ℎ 119889 ℎ ) = sum Pr ( 120118 ℎ |ℎ 119889 119900) Pr(119900|119889 ℎ)

Pr(h |h d o) =







various settings














2532

IJSTRcopy2020

wwwijstrorg















5 15 25 dB) where a = 015 and d1 = 200 m





m)d2(300 m)120588 = 15dB and ϵ = 0









base station












determined

















2533

IJSTRcopy2020

wwwijstrorg















15 210-222
















Access 5 27514-27524




Research 264 1101-1115














65 601-616





1468















1441-1452





IEEE 1-6

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