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

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• 作者：Meiqin Tang ; Yalin Xin ; Chengnian Long ; Xinjiang Wei…
• 刊名：Wireless Personal Communications
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：89
• 期：4
• 页码：1027-1043
• 全文大小：912 KB
• 刊物类别：Engineering
• 刊物主题：Electronic and Computer Engineering
  Signal,Image and Speech Processing
  Processor Architectures
  
• 出版者：Springer Netherlands
• ISSN：1572-834X
• 卷排序：89

文摘

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.KeywordsCognitive radioParticle swarm optimization (PSO)Nonconvex optimizationPower and rate control