Minimizing the detection error of cognitive radio networks using particle swarm optimization

El-Saleh, A. A. and Ismail, M. and Manesh, M. R. and Zavareh, S. A. R. T. and Akbari, M. (2012) Minimizing the detection error of cognitive radio networks using particle swarm optimization. In: 2012 International Conference on Computer and Communication Engineering (ICCCE). IEEE Xplore, pp. 877-881. ISBN 978-1-4673-0478-8

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Abstract

Weighting the coefficients vector is the principal factor influencing the detection performance of cognitive radio networks that uses soft-detection fusion (SDF) based cooperative spectrum sensing. Maximal ratio combining- (MRC-), equal gain combining- (EGC-) and continuous genetic algorithm- (CGA-) based SDF are well suited for optimizing the detection performance and thus ensure safe access of spectrum by CR users. However the mentioned methods suffer from slow convergence and/or sub-optimality. In this paper, the use of particle swarm optimization (PSO) algorithm under MINI-MAX criterion is proposed to optimize the weighting coefficients vector so that the total probability of decision error is minimized. The performance of the PSO-based proposed method is examined and compared with GA-based technique as well as other conventional SDF schemes through computer simulations. Numerical results confirm the effectiveness of the proposed method.

Item Type: Book Section
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 07 Feb 2014 02:01
Last Modified: 07 Feb 2014 02:01
URI: http://shdl.mmu.edu.my/id/eprint/5105

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