Spectrum sensing techniques andSpectrum sensing techniques andSpectrum sensing techniques and Spectrum sensing techniques and aspects related to propagationaspects related to propagation

Bologna, 24/01/2012

Valeria Petrini, Ph.D. Studentvpetrini@arces.unibo.it

DEIS/ARCES - Tutor : Prof. Ing. Giovanni Emanuele CorazzaFondazione Ugo Bordoni - Cotutor: Ing. Guido Riva

Outline

• Cognitive Radio• Cognitive Radio • Autonomous WSD and database-assisted WSD

• White Space model in UK (@ Ofcom)

• Applications of Cognitive Radio• Cognitive Approach to Satellite System

• Energy Efficiency in Mobile Radio Systems: a Cognitive approach

• Other work

What is a Cognitive Radio (CR) ?

What is a Cognitive Radio (CR) ? (1)

• Cognitive Radio: a radio or system that senses its operationalelectromagnetic environment and can dynamically andautonomously adjust its radio operating parameters to modifyautonomously adjust its radio operating parameters to modifysystem operation, such as maximize throughput, mitigateinterference, facilitate interoperability and access secondary markets

What is a Cognitive Radio (CR) ? (2)

• The components of the Cognitive Radio network can be classified in two groups:• Primary Network: an existing network infrastructure is generally

referred to as the primary network, which has an exclusive right p y , gto a certain spectrum band

• Secondary Network: does not have license to operate in a desired band Hence the spectrum access is allowed only in andesired band. Hence, the spectrum access is allowed only in an opportunistic manner

• Cognitive Radio Loop• Spectrum Sensing

S t A l i• Spectrum Analysis• Spectrum Management• Spectrum ReconfigurabilitySpectrum Reconfigurability

Autonomous WSD and database-assisted WSD

• Autonomous WSD: performs sensing and radiate only ifit cause no interference to the DTT worst case

• Database-assisted WSD: operates with assistance froma geolocation databasea geolocation database

Estimation of Spectrum Availability for White Space DevicesWhite Space Devices

Estimation of Spectrum Availability for Whit S D i (1)White Space Devices (1)

Th id i i l i d b f l i ERP f• The idea is using a geolocation database for regulating ERP ofWhite Space Device (WSD) which will reuse the broadcastingspectrum (470-790 MHz)

• Before transmitting, a WSD will interrogate a database, called thegeolocation database providing its location and its characteristicsgeolocation database, providing its location and its characteristics,and it will receive a list of channels it may use, as well as on itsmaximum permissible ERP for each of these channels

• The objective of my work is to compute the data required to populatethe geolocation database and use them in order to get somethe geolocation database and use them in order to get somestatistical data

Estimation of Spectrum Availability for Whit S D i (2)White Space Devices (2)

Through the Spectrum Sensing a WSD can control thevariability of the channel

Primary

WSDSpectrum Sensing

WSD Position

Primary Base

Network WSD Position

Primary Base Station

Primary User

Geolocation Database

• Channel• ERP

Estimation of Spectrum Availability for Whit S D i (3)White Space Devices (3)UK Planning Model (UKPM) (1)

• The UK Planning Model was mainly developed to study the digital terrestrialtelevision coverage in the UK

It i d t l l t th t d d i t f i fi ld• It is used to calculate the wanted and interfering fieldstrength distributions to and from each UKtransmitting site

• At the heart of any computer planning method ispropagation prediction which is the prediction of fieldstrength from a transmitter at a receiving locationstrength from a transmitter at a receiving location

• The basis is the prediction of received field strength ata location, taking into account the environment inbetween

Estimation of Spectrum Availability for Whit S D i (4)White Space Devices (4)UK Planning Model (UKPM) (2)

• The UKPM calculates the DTT location probability, q, for every 100 m x 100 m pixelacross the UK

• This is defined as the probability with which wanted and unwanted DTT signal powersmeet the relevant criterion for correct operation of a DTT receivermeet the relevant criterion for correct operation of a DTT receiver

• Specifically, the location probability can be written (in linear domain) as:

K

kkUkUSs ErEEq

1,,min,1 Pr

– Es is the wanted field strength at the DTT receiver– ES,min is the minimum received wanted field strength required for correct operation in a noise-limited environment

K is the number of (co channel and/or adjacent channel) DTT interferers

– K is the number of (co-channel and/or adjacent-channel) DTT interferers– EU,k is the received field strength level of the Kth DTT interferer, and– rU,k is the minimum ratio of wanted DTT field strength to DTT interfere field strength required for correct

operation (DTT-to-DTT protection ratio)

Estimation of Spectrum Availability for Whit S D i (5)White Space Devices (5)UK Planning Model (UKPM) (3)

K

kkUkUSs ErEEq

1,,min,1 Pr

Interferer Signal: Channel n

1PrPr1E

SES U

EUEq

0Pr )/()/( mVdBEmVdBS UE

100 m

100 m

Pixel Wanted Signal: Channel n

100 m

Interferer Signal: Channel n +1 (or n-1 )

• The terms ES(dBµV/m) and UE(dBµV/m) are approximated asGaussian random variables with medians mS(dBµV/m) andmU(dBµV/m), and standard deviations σS(dB) and σU(dB),respectively

Estimation of Spectrum Availability for Whit S D i (6)White Space Devices (6)

Computation of the maximum permissible ERP

WSD

K

kkUkUSs EGfrErEEq )(Pr

1,,min,2

• EWSD is the field strength of WSD

• G is the WSD – DTT receiver coupling gain

(∆f) i th WSD t DTT t ti ti• r(∆f) is the WSD to DTT protection ratio

• X can be modelled as a Gaussian random variable withX r(f )(dB ) GdB EWSD(dB )

• As long as the mean field strength of the interference fromWSD is kept m then the location probability reduction will

mean mx and standard deviation σxX r(f )(dB ) GdB EWSD(dB )

qqq 21

WSD is kept mx then the location probability reduction willbe less than ∆q

• Therefore mx is the maximum permissible mean value forS fthe WSD protected field strength

Cognitive Approach to Satellite System

Cognitive Approach to Satellite System (1)

• White spaces: spectrum holesBl k th t t f hi h l t l f ll d t th• Black spaces: the contents of which are completely full due to thecombined presence of communication and noise

• Gray spaces: spaces that are partially occupied by a signal (they p p p y p y g (given spectrum is partially used)

Secondary Network: Satellite Network Secondary Network: Terrestrial Network

Scenario #1 Satellite Terrestrial

Primary - Broadband Wireless Links

Scenario #2 Satellite Terrestrial

Primary Return Links -

Secondary Forward and Return Links - Secondary - Broadband Wireless

Links

Cognitive Approach to Satellite System (2)

Secondary Network: Terrestrial Network

• A Ground Station transmitting with:• P0 : the transmitted power • G :the antenna gain• G0:the antenna gain

• A geostationary satellite receiving with:G t i• GS: antenna gain

• L: distance between the GS and the satellite

• An interfering network spatially deployed as

• a 2D Poisson Point Process φ with density Assumptions:λint

• each interfering terminal transmits an ERP equal to PI GI

• Interfering links are affected by Rayleighfading

• All cognitive devices are at distance L fromthe satellite

• Path loss α = 2 (free space propagation)

Cognitive Approach to Satellite System (3)

The Interference Model (1)

• Objective: to evaluate the outage probability:the probability that the cognitive device power is higher than a certain threshold, equivalent to:q

ILGGPLGGPTSINRSIIN

S22

200PrPr

• SINR: Signal to Interference plus Noise Ratio• T: SINR threshold above which the useful primary link is still

SIIN

T: SINR threshold above which the useful primary link is still working

• σ2N : AWGN power

The only source of randomness is given by the aggregateinterferenceinterference

Cognitive Approach to Satellite System (4)

Numerical Results (1)• Cognitive devices density λint

• Outage probability

Energy Efficiency in Mobile Radio Systems

Energy Efficiency in Mobile Radio Systems (1)

Diff ll l i di d fi d d ff• Different cellular coverage strategies were studied to find a trade-off to reach the best performance in terms of radio coverage, system throughput and energy efficiency

• Emitted Power Density (EPD) [W/km2]E itt d ( di ) P k f i ff d i• Emitted (radio) Power per square km for a given offered service

• It mainly depends on the RAN (power emitted by the BS’s)• It depends on radio interface technology and planning

Cell size, propagation losses, traffic density, deployment strategy

Energy Efficiency in Mobile Radio Systems (2)

Id l iEPD evaluation in ideal environment

• Ideal environment:• Single cell• Dual-slope quasi-Hata propagation model• Fully analytical model

• Cell border (d=R) evaluation (PSENS = -90dBm) :

PR (dB)PT R Psens

1GTGR

4d0

2Rd0

N

TXα=2

α>2

GTGR d0

EPDPT (R )

d0

h RXb

EPD T ( )Acell (R )

d Log (distance)

Energy Efficiency in Mobile Radio Systems (3)

Theoretical scenario – fixed traffic / cellEPD

(W/Km2)

R [Km]R [Km]

Energy Efficiency in Mobile Radio Systems (4)

S i ” M h lik ”EPD evaluation in simplified urban environment

• Scenario: ” Manhattan-like” • Microcellular and macrocellular cases• Objective: coverage strategy to minimize the EPDObjective: coverage strategy to minimize the EPD• Ray-tracing tool to properly predict propagation

Average buildingheight: 30 m

Energy Efficiency in Mobile Radio Systems (5)

Result: Hybrid Case (Macro cell + Micro cell deployment)

• Idea:• Cell Shape To minimize EPDMICRO

Mi ll L fl• Micro cell Lower floors • Macro cell Higher floors

AB BC C

FF E

DTX

A

A

B

B B

B

C

C

C

C D

D

T t h d !Target coverage reached !

Energy Efficiency in Mobile Radio Systems (6)

Cognitive approachCognitive Networking

To reduce the the network energy consumption,

Networking

Application Layer

the nodes have to be reconfigured in orderoptimize the network in a broader wayTransport Layer

Network Layer Additional communication parameters have to beconsidered:

MAC Layer throughputdelay

Physical Layer

traffic characteristicsfemto cell

Cognitive Radio …

Other Work

Other work

• Applications of Cognitive Radio• Cognitive Approach to Emergency ManagementCognitive Approach to Emergency Management

• Characterisation of WiMAX propagationCharacterisation of WiMAX propagation• Experimental propagation characterization at 3.5 GHz in different

environments (outdoor, indoor and mixed)

• Cross Layer Coding (UL-FEC)• Analysis of a wireless communication system in which channel coding isAnalysis of a wireless communication system in which channel coding is

applied to both physical and upper layer. The splitting of redundancybetween the coding schemes applied to the two layers was studied

Pubblications

• “A study on the energy efficiency of urban cellular radio deployment solutions”, V. Degli Esposti,A study on the energy efficiency of urban cellular radio deployment solutions , V. Degli Esposti,V. Petrini, M. Barbiroli, C. Carciofi, APS-URSI 2012-Chicago (Submitted)

• “A fully reconfigurable approach to Emergency Management”, D.Tarchi, V.Petrini and G.E.Corazza IJARAS Vol 3 No 3Corazza, IJARAS, Vol.3, No 3

• "Cognitive Hybrid Satellite-Terrestrial System”, R.Suffritti, G.E. Corazza, A. Guidotti, V.Petrini,D.Tarchi, A.Vanelli-Coralli, M. Di Renzo, CogART-ISABEL 2011

• "Planning Criteria to Improve Energy Efficiency of Mobile Radio Systems”, M.Barbiroli, C.Carciofi,V.Degli Esposti, P.Grazioso, D.Guiducci, V.Petrini, G.Riva, ICEAA 2011

• "Experimental Characterisation of WiMAX Propagation in Different Environments”, Valeria Petrini,Daniel Robalo, Marina Barbiroli, Claudia Carciofi, Fernando J. Velez, Joao Oliviera, FrancoFuschini, Paolo Grazioso, Eurocon & Conftele 2011

• "Optimizing Cross Layer Coding Redundancy in Slow Fading Channels”, Marco Papaleo, ValeriaPetrini, Rosario Firrincieli, Alessandro Vanelli-Coralli, Giovanni Emanuele Corazza, ASMS/SPSC2010

Credits

• Newcom++ Spring School on "Cognitive Wireless Communication Networks” (21 cdf)Newcom Spring School on Cognitive Wireless Communication Networks (21 cdf)

• Cost2100/Conet/Newcom++ Training School on "Cooperating Objects and Wireless SensorNetworks” (20 cdf)

• COST Action IC0902 :"First International Summer School on Cognitive Wireless Communications”(60 cdf)

• University Course: "Trends in Communications” (30 cdf)

• English Course (30 cdf)

V l i P t i iValeria Petrini

Dipartimento Elettronica Informatica Sistemistica – DEISAd anced Research Center on Electronic S stems for Information and Comm nication Technologies E De Castro ARCESAdvanced Research Center on Electronic Systems for Information and Communication Technologies E. De Castro – ARCES

Fondazione Ugo Bordoni –FUB

valeria.petrini@unibo.itvpetrini@arces.unibo.it

www.unibo.it

Cognitive Approach to Emergency ManagementManagement

Cognitive Approach to Emergency M t (1)Management (1)

E h• Emergency phases:• Prediction and prevention• Efficient handling of emergency activities• Carrying out the operations following a natural disaster

• Basic requirements of an ICT infrastructure:• Resilience/robustness• Self-management• Decision support system• Interconnection/Interoperability• Mobility• Power-efficiencyy• Broadcasting/Multicasting• Security• Localization engineg

Cognitive Approach to Emergency M t (2)Management (2)

DISTRIBUTED COMPUTING INFRUSTRUCTURES U CO U G US UC U

• Autonomic system features:

• Self-Healing• Self-Protection• Self-Configuration• Self-Optimization

Cognitive Approach to Emergency M t (3)Management (3)

EMERGENCY MANAGEMENT LEARNING LOOPG C G G OO