MOBILITY IN COGNITIVE

RADIO NETWORKS [Cognitive Radio - Assignment (1)

Prepared by:

1- Nassr Alden Mohamed Mohamed Ismail

2- Hossam Taha Mohamed Hassan

Contents Introduction ............................................................................................................................................ 2

Handoff in Cognitive Radio Networks ..................................................................................................... 2

Handoff process in cognitive radio ..................................................................................................... 2

Handoff Performance Metrics ............................................................................................................ 3

Handoff strategy ................................................................................................................................. 3

1- Non-Handoff Strategy ............................................................................................................. 3

2- Pure Reactive Handoff ............................................................................................................ 3

3- Pure Proactive Handoff ........................................................................................................... 4

4- Hybrid Handoff Strategy ......................................................................................................... 4

Which handoff strategy is the best? ................................................................................................... 4

Spectrum Prediction in Cognitive Radio Networks ................................................................................. 5

Research Challenges in Cognitive Radio Mobility ................................................................................... 5

Basic parameters: ............................................................................................................................... 6

Protocol parameters ........................................................................................................................... 7

Procedure of protocol: ........................................................................................................................ 7

Protocol Results .................................................................................................................................. 8

References .............................................................................................................................................. 9

Introduction Radio spectrum is considered one of the most

valuable resources for each country. Current

communication systems can utilize a limited portion

of spectrum bands. According to Ericsson mobility

report 2015 Error! Reference source not found.], the

data traffic growth rate was around 55% from Q4

2013 to Q4 2014 as shown in Figure 1. With scarcity

of spectrum resources, new methods that could

utilize spectrum more efficient than current fixed

assignment scheme should be used.

Cognitive Radio (CR) was one of the concepts

introduced to enhance spectral efficiency by allowing

non-licensed users to utilize spectrum holes. This will

utilize the spectrum more efficiently because the

licensed users will not use the spectrum all the time in

all places. Currently, FCC allowed unlicensed users to use white spaces in TV spectrum bands [2].

There is no free launch! Although cognitive radio techniques can enhance the efficiency of

spectrum utilization, it has a lot of challenges that should be solved to be able to produce commercial

communication systems. One of the main challenges in cognitive radio is spectrum and user mobility.

In classical communication systems, handover occurs to ensure call continuity during user mobility.

This is done by switching the call to a new channel governed by the base station which the user is

moving in its direction. This could be done through hard or soft handover. In hard handover, the

connection is released from base station and new connection is established on the other base station

and the call continues on the new channel (e.g. GSM). In soft handover, the new connection is

established and the call will be served by both base station in overlapping area. When the signal

received from old base station becomes weak, the connection with it will be received and the new

base station will be the only one serving the user (e.g. UMTS handover). This type of handover occurs

due to user mobility.

In Cognitive radio, in addition to user mobility, there is another type of mobility event called

Spectrum mobility. This event occurs when a primary licensed user activity is detected on the

spectrum band used by secondary unlicensed user. In this case, the secondary user should change

its working frequency band to another non-used band to avoid making interference to primary user.

Both type of mobility events should be considered while developing mobility management schemes

in cognitive radio networks.

In this report, handoff types and strategies in cognitive radio networks, spectrum prediction

and give an example for mobility in LTE cognitive radio system.

Handoff in Cognitive Radio Networks

Handoff process in cognitive radio In classical cellular networks, the handover occurs mainly due to user mobility. This type of handoff

still exists in cognitive radio networks when CR user moves. In addition, primary user activity adds new

type of mobility events called spectrum mobility which forces the secondary user (SU) to handoff into

another available spectrum hole (SH). In CR networks, the handoff process consists of two steps:

a. Evaluation phase: in this phase, the SU will monitor the occurrence of handoff triggering

event (user mobility or spectrum mobility)

Figure 1 Voice and Data Traffic Growth Rate

b. Link Maintenance Phase: in this phase, the SU will stop transmission to avoid interference

with primary user. The SU will search for another spectrum hole and continue transmission

there.

Handoff Performance Metrics The following metrics could be used:

1- Number of handoffs during one session

2- Probability that link will be maintained when the SU leaves an spectrum hole due to PU activity

3- Handoff latency

4- Average amount of data transferred between two SU

SU will be concerned about link reliability. On the other hand, primary user will be concerned about

the handoff delay to minimize SU interference affecting PU.

Handoff strategy Selecting the best handoff strategy is one of the main issues in designing spectrum mobility in CR

networks. The handoff strategy could be one of the following [6]:

1- Non-Handoff Strategy In non-handoff strategy, when PU activity is detected, SU will stop his transmission until

primary user finishes his activity. After that, SU will use the channel again and continue

transmission as shown in Figure 2.

Figure 2 Non-Handoff Strategy

2- Pure Reactive Handoff In this type of handoff, the user will not take any decision until PU is detected. After detection,

the SU will search for available spectrum hole then handoff take place and SU continue

transmission on the new band. This strategy will give the most accurate handover because the

sensing of new channel is occurs on demand. On the other hand, the handoff latency of this

system is high which is not good from PU perspective. Figure 3 shows the pure reactive

handoff.

Figure 3 Pure Reactive Handoff

3- Pure Proactive Handoff Primary user activity is not 100% random because it is related to human activity. This relation

makes it predictable which could be used to take some decisions proactively. In this case,

when SU predicts that PU activity will occur, it starts the handoff before actual transmission

of primary user which minimize the interference from PU perspective. On the other hand, it

will also minimize the handoff latency because everything could be planned before. In

addition, number of handoffs could be minimized because we can know the expected number

of handoffs from the stochastic model. The only condition to achieve these advantages is

building an accurate PU arrival model which is not an easy task by the way. More details about

modeling the PU activity will be mentioned in the next section.

Figure 4 Pure Proactive Handoff

4- Hybrid Handoff Strategy This strategy provides a good compromise between proactive and reactive strategies. It

minimizes the handoff latency because the sensing time is reduced by proactive planning. On

the other hand, it will not take the decision to handoff until the mobility event occurs as shown

in Figure 5.

Figure 5 Hybrid Handoff Strategy

Which handoff strategy is the best? This question doesnt have single answer because the answer depends on the nature of system, QoS

requirements and user behavior. For example, if the PU activity period is usually small, the non-

handoff strategy can give good results. When the PU model is modeled accurately, the proactive

strategy can give ideal performance. But generally speaking, hybrid handover strategy can give

acceptable performance in many cases. Comparison between the four handoff strategies is shown in

Strategy Non-handoff Proactive Reactive Hybrid

Main Idea Stay and wait Proactive sensing Proactive action

Reactive sensing

Proactive sensing

Reactive action

Reactive action

Advantages Very low PU interference

Fastest response Smart target

channel selection

Accurate target channel

selection

Fast response

Disadvantages Very high SU interference

Outdated target channel selection

High computational requirement

Slow response Outdated target channel

selection

Handoff latency

Unpredictably high latency

Very low latency Medium latency

Low latency

Dependency PU activity Backup channel relevancy

Accurate PU traffic model

Spectrum sensing

Backup channel relevancy

Best suited environment

Short data transmission PU

network

Well-modeled PU network

General PU network

General PU network

Table 1 Comparison between handoff strategies

Spectrum Prediction in Cognitive Radio Networks Spectrum prediction is used in cognitive radio to overcome the current sensing problems like latency

and SU collisions [5]. Using prediction, the SU can skip some channels from sensing that is expected

to be busy and focus only on the probable idle channels. Many techniques are used in spectrum

prediction including:

1- Hidden Markov Model Based Prediction

2- Multilayer Perceptron Neural Network Based Prediction

3- Bayesian Inference based Prediction

4- Moving Average Based Prediction

5- Autoregressive Model Based Prediction

6- Static Neighbor Graph Based Prediction

Research Challenges in Cognitive Radio Mobility The following topics are research areas:

1- Adaptive Spectrum Handoff Strategy: as mentioned before, each strategy is suitable for

certain application/system model. If an adaptive strategy that varies according to spectrum

characteristics was developed, it will give the ultimate performance.

2- Cross-Layer Link Maintenance Protocols: next section shows an example for cross-layer

protocol for spectrum mobility.

3- Energy efficiency

A cross-layer protocol of spectrum mobility and handover in cognitive

LTE networks

As shown in [4], the main protocol proposed in this case is a mobility spectrum and handover in CR-

LTE networks. SU needs to leave its current frequency band and move to another one if the PU

reclaimed the band. This protocol classifies the SUs served by a specific eNodeB into two types as

shown in Figure 6:

1. A SU that locates close to center of the cell, it is covered by only one eNodeB.

2. A SU that locates close to cell border, it is in the overlapped area between two adjacent

eNodeBs.

Figure 6 System Model

When a PU needs to reclaim the spectrum band, the PU that is using this band has to act according to

its location in the cell. For first case, the SU will perform spectrum mobility to another idle band in the

same cell. But, in second case, the SU has to decide to perform spectrum mobility to an idle band in

the same cell or handover to an idle in the adjacent cell. The decision to perform spectrum mobility in

first case or spectrum mobility/handover in second case depends on some parameters and

assumptions that are mentioned in the following.

Basic parameters LTE band is divided into small units, each is called resource block (RB) which has

width=180kHz. This is the smallest unit in LTE.

Empty (idle) spaces in the frequency band are called spectrum holes (SH). Each SH is formed

from one or more RB(s). Figure 7 illustrates the concept of resources blocks (RB) and spectrum

holes (SH) that may consists of one or more RBs. PU may need single or many RBs according

to the required data rate.

Figure 7 Resource blocks and spectrum holes

Then, the protocol some other parameters to formulate its concept and idea. These parameters are

shown in details in the following section.

Protocol parameters mi is an accumulated value that is increased by 1 for each PU accesses and uses mi RB within

a determined period.

Dt is the remaining data size that SU still needs to transmit. In this protocol, the selected SH is

chosen based on this size.

SNR received by the SU device. With the knowledge of the available SHs and received SNR, SU

can calculate the reachable transmission rate in each SH from Shannon formula.

Then, SU can calculate Pu for different sensed SHs. Pu is defined as the probability that the

RB(s) are unoccupied (idle) during the transmission process of SU.

Consequently, SU can calculate the required time to complete the pending transmission. This

remaining time is denoted by (treq) or called minimum transmission time.

Procedure of protocol 1. The SU senses the spectrum band surrounding it and collects information about them. These

information includes: signal power, resources blocks, usage of resources blocks (). Once a PU

needs to reclaim the resources blocks, then the SU will go to step 2.

2. Apply analysis and calculations on the collected data to take the decision based on the

obtained results. The main objective of this step is to calculate expected transmission time

(treq) for available SHs to determine which one is suitable for spectrum mobility or handover.

The SU has a remaining data that is not transmitted yet with size dt MB. Then, there are two

possibilities in this case:

a. SU is not in overlapped area: in this case SU will calculate different values for SNR for

available SHs in the same cell. Then, it calculate the maximum transmission rate (Ri) with

the knowledge of SNRi for SHi, number of RBs in it (mi) and remaining data size (dt).

Finally, SU can calculate the required time to transmit the remaining data (treq).

= log2(1 + )

=

Finally, SU calculates the probability of spectrum hole SHi unoccupied by PUs within the

time period of treq. This probability is denoted by Pu (SHi,treq). This probability

represents a prediction if the idle SHi is unoccupied by any Pus during the required

service time treq. This probability is modeled by a Poisson distribution, where the general

formula of Poisson is:

(, ) =()

!

Where k represents how many times that PU will need the SH during the service time

treq. Then, it is required to have k=0. T represents period, it will be set to treq. Hence,

Pu for a SH that is consists of mi RBs is given by the following formula:

(, ) = (0, )

=1=

=1

b. SU is in overlapped area: in this scenario the SU is located between two eNodeBs: the

old one which is already serving him and a new adjacent cell. Then, the previously

mentioned procedure is applied by SU for both cells to decide whether to perform

spectrum mobility or handover to the adjacent cell. Initially, SNR and SNR are calculated

for serving and adjacent cells respectively. Then, from the calculated values SNR and

SNR, and with the knowledge of the remaining data size dt and number of RBs in each

SH, SU can calculate the required transmission time: treq and treq for old and new cells

respectively. Finally, calculate the probability for the SHs to be idle during the two

different required service times.

(, ) = (0, )

=1=

=1

(, ) = (0, )

=1=

=1

3. Make the decision. There are two possible scenarios in this step:

a. If the SU is not in the overlapped area: based on the collected information and applied

analysis in previous two steps, SU will decide which SH will be the target one within the

same serving cell. SU will calculate the required time to perform the spectrum mobility

process, this time includes switching to the other frequency, transmission of remaining

data, and probable time if transmission is corrupted again with arrival of a new PU. This

time is calculated from the formula:

() =

(, ) + 1 ((, )) 2

Where, TL2H is the layer-2 switching delay time.

b. If the SU is in the overlapped area: based on the collected information and applied

analysis in previous two steps, SU will decide to do spectrum mobility within the same

cell or handover to the adjacent cell. SU will calculate the required time to perform the

spectrum mobility process and to perform the handover process. This time includes

switching to the other frequency, transmission of remaining data, and probable time if

transmission is corrupted again with arrival of a new PU. This time is calculated from

the formula:

() = 3 +

(, ) + 1 ((, )) 2

Where, TL3H is the layer-3 handover delay time.

After that, the SU perform a comparison between both cases and then take the decision.

If the required time to perform the spectrum mobility < the required time to perform

the handover, then SU will do spectrum mobility, otherwise, handover to the adjacent

cell.

Protocol Results Performance effect can be shown in different metrics such as data throughput, total transmission

time, end-to-end delay, and number of spectrum mobility event. Figure 8 shows the effect of

probability of SH to be idle during required service time for different number of RBs that form SHs on

the total transmission time. It is clear that factor of SH size has a good effect and reduced total

transmission time.

Figure 8 effect of probability of SH to be idle during required service time

Another performance metric can be introduces. It is end-to-end delay vs. number of Pus and vs.

number of SHs. Figure 9 shows that the proposed scheme gives better performance than the common

max idle time scheme.

Figure 9 End to end delay performance

Conclusion

In this report, handoff types and strategies in cognitive radio networks were discussed briefly showing

that each strategy can be suitable for certain spectrum characteristics. The role of spectrum prediction

in enhancing the spectrum sensing latency was explained. Some challenges and research areas in

mobility were discussed. And finally, cross layer protocol for spectrum mobility in LTE systems was

discussed in details.

References [1] Ericsson Mobility Report 2015, MOBILE WORLD CONGRESS EDITION, February 2015 [2] J. Sachs, I. Maric, and A. Goldsmith, Cognitive Cellular Systems within the TV Spectrum, Proc. IEEE Symp. New Frontiers in Dynamic Spectrum (DySPAN 10), Apr. 2010. [3] L. Won-Yeol, I. F. Akyildiz, "Spectrum-aware mobility management in cognitive radio cellular networks", IEEE Transactions on Mobile Computing, vol. 11, no. 4, 2012, pp. 529-542.

[4] Y. Chen , C. Cho , I. You , H. Chao . A cross-layer protocol of spectrum mobility and handover in cognitive LTE networks. Simulation Modelling Pract. and Theory , 8 , 1723 1744 [5] X. Xing, T. Jing, W. Cheng, Y. Huo, and X. Cheng, "Spectrum prediction in cognitive radio networks," Wireless Communications, IEEE, vol. 20, no. 2, pp. 90-96, 2013. [6] Christian, I. , Sangman Moh, Ilyong Chung, et al. Spectrum Mobility in Cognitive Radio Networks. Communications Magazine, IEEE. 2012, Vol. 50, No. 6, pp114~121