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Wireless Personal Communications
Published in: Wireless Personal Communications 4/2016

01-08-2016

Optimizing Power and Rate in Cognitive Radio Networks using Improved Particle Swarm Optimization with Mutation Strategy

Authors: Meiqin Tang, Yalin Xin, Chengnian Long, Xinjiang Wei, Xiaohua Liu

Published in: Wireless Personal Communications | Issue 4/2016

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Abstract

Dynamic spectrum allocation is a main challenge in the design of cognitive radio networks, which enables wireless devices to opportunistically access portions of the spectrum as they become available. Considering this challenge, this paper proposes a nonconvex power and rate management algorithm in cognitive radio networks. We apply an improved particle swarm optimization (PSO) method to deal with this nonconvexity issue directly without any assumption, which is different from prior works. Since PSO sometimes converges around the local optimum solution in the early stage of the searching process, mutation is employed to PSO which can speed up convergence and escape local optimum. We also give the numerical results, which show that the proposed algorithm can achieve higher quality solutions than other population-based optimization techniques.
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Metadata
Title
Optimizing Power and Rate in Cognitive Radio Networks using Improved Particle Swarm Optimization with Mutation Strategy
Authors
Meiqin Tang
Yalin Xin
Chengnian Long
Xinjiang Wei
Xiaohua Liu
Publication date
01-08-2016
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 4/2016
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-016-3303-z

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