Najam_PresentationFit2011

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Particle Swarm Optimization based Methodology for

Solving Network Selection Problem in

Cognitive Radio Networks

Najam ul Hasan

[email protected] NEtwork Systems Lab

Sejong University

Republic of Korea

December 20, 2011

Co-authors: Waleed Ejaz , Hyung Seok Kim and Jae Hun Kim

Sejong University


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Outline

Abstract

Introduction

Network Selection problem Proposed Technique

Simulation Results

Conclusion

Network selectionin cognitive radio systems

Network selection in cognitive radio systems


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Abstract Cognitive radio prime concern is to access underutilized frequency band

without colliding with primary user.

With spare spectrum in multiple networks, cognitive radio should choosethe best network to access, subject to certain constraints. In cognitive radio system this is referred to as network selection problem.

In this paper, we presented a meta-heuristic algorithm named particle swarm optimization (PSO) fornetwork selection problem.

PSO is a population-based search algorithm based on the social behaviors of bird flocking and fish schooling.

The selection algorithm aims at achieving secondary users specified quality of ser vice at a lower price, subject to the interference constraints ofeach available network with idle channels.

The exper imental results demonstrate the effectiveness ofthe proposed

methods



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Introduction ITodays wireless networks are characterized by a fixed spectrum assi

gnment policy. However a large portion of spectrum is used sporadical

ly and utilization of assigned spectrum ranges from 15% to 85% as ca

n be seen from diagram below.

Medium UseSparse Use

Heavy Use

Amplitude(dBm)

Fixed Spectrum Utilization

Frequency (MHz)



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Assumption

1. M licensed networks.

2. Each licensed network

has Cm channels.

1. All channels are identica

l in term of capacity.

4. A Virtual network operato

r VNO that manages the i

ncoming SUs, collects net

work status info as needed and coordinates with

licensed network to assi

gn SUs to a network.

Network Selection Problem I



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Network Selection Problem IIAssumptions

Each PU can access one and only one (home network) while SUs are able to

use any network with an available channel.

Each PU or SU can use only one channel at a given time.

PUs can use any channel in its home network and has precedence over SUs.

Once a PU has occupied a channel, it remains in that network until it call is

completed.

SU do not change channels except when they collide with the incoming PUs,

in which case they will yield to the PUs and the VNO will reassign the SUs to

a different network.



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Proposed Technique I


___________________________________________________________________

Algorithm: Generalized particle swarm optimization (PSO)

___________________________________________________________________

1. Randomly initialize the position and velocity of each kth particle.

2. Calculate the fitness of each kth particle.

3. Calculate for each kth particle.

4. Calculate for the swarm.

5. Update the velocity of each kth particle using

6. Update the position of each kth particle using

7. Calculate the fitness of each kth particle.8. Update of each kth particle.

9. Update of the swarm.

10. Terminate the algorithm if the stopping condition is reached, otherwise

go to step 5.

____________________________________________________________________

)()( 2211 kkkkknew

k xnbestrcxpbestrcvwv v!

)2(newkk

new

kvxx !

)1(,...,2,1 nk !


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Proposed Technique II

To apply PSO for Network Selection Problem we need to address the following

Encoding of Particles

Fitness Function

Update Velocity and Position of Particles

Repair Process


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Encoding of Particles

Proposed Technique III


3channel

3network

52

SUforselctionNetwork

7networkprimaryeachinchannelsofNumber

5SUsofNumber

5networksPrimaryofNumber

example,For

2

2

!

!

!

!

!

!

ix


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Proposed Technique IVFitness of a Particle:

The fitness function is the reciprocal

of

the sum of the interference incurred by all networks and th

ecost all the SUs have to pay to these network operators.

Updating Velocity and Position of a particle:

The velocity and position are updated

according to (1) and (2). For example,


1.68,1.87)2.5,2.3,(1.2,)v,...,v,(vV iDi2i1i !!

)120,165(24,43,75,Xi !

118,167)(25,41,77,X1i!


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Repair Process:

During updating the particles position, if some constraint is

Violated a repair process is triggered.

In repair process position of the particle is randomly adjus

t

until all constraint gets obeyed.

For example, if the same position is generated for two SUs,

position of one SU is a randomly adjusted.

Proposed Technique V



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Simulation Results ISimulation Parameters:


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Simulation Results II

Average objective function versus number of iterations



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Simulation Results III

Iteration # Avg. Accumulative

Interference

Avg. Accumulative

cost

100 18.21 683.3

500 17.64 665.8

1000 17.34 655.75

1500 17.23 650.65

2000 17.23 645.65

2500 17.23 642.95

3000 17.17 641.20



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Conclusion Inthis paper, a network selection method for SUs of a

cognitive radio network is proposed, which uses particle swarm optimization as the selection algorithm.

The algorithm seeks to assignnetwork to SUs in such away thatthe overall accumulative interference incurredby the primary users of allthe networks and the cost charged by allthe SUs of cognitive radio network are minimal.



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Acknowledgement



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QUESTIONS


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