Title
Optimizing Power and Rate in Cognitive Radio Networks using Improved Particle Swarm Optimization with Mutation Strategy.
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.
Year
DOI
Venue
2016
10.1007/s11277-016-3303-z
Wireless Personal Communications
Keywords
Field
DocType
Cognitive radio,Particle swarm optimization (PSO),Nonconvex optimization,Power and rate control
Convergence (routing),Particle swarm optimization,Population,Mathematical optimization,Wireless,Computer science,Local optimum,Multi-swarm optimization,Frequency allocation,Cognitive radio
Journal
Volume
Issue
ISSN
89
4
0929-6212
Citations 
PageRank 
References 
0
0.34
4
Authors
5
Name
Order
Citations
PageRank
Meiqin Tang100.34
Yalin Xin200.34
Chengnian Long324828.71
Xinjiang Wei49511.33
Xiaohua Liu500.34