摘要
目前亟待解决如何获得认知无线电系统效益最大化问题,而求解最优频谱分配方法是一项关键技术,针对传统粒子群(PSO)算法收敛速度慢、易陷入局部最优解等缺陷,提出一种基于鲶鱼粒子群算法(CE-PSO)的认知无线电频谱分配方法。首先建立认知无线电频谱分配优化的数学模型,然后以用户取得的效益最大化为优化目标,引入"鲶鱼效应",保持粒子群的多样性,通过粒子间信息交流找到空闲频谱最优分配方案,最后采用仿真实验测试CE-PSO算法的有效性。结果表明,CE-PSO算法克服了PSO算法的缺陷,可以快速、准确地寻找到最优频谱分配方案,更好地实现系统效益的最大化,可以满足认知无线电系统的应用需求。
Spectrum allocation is a key technology in cognitive radio systems, and spectrum allocation is used to find the optimal maximum system effi- ciency. Traditional particle swarm optimization （PSO） algorithm has slow convergence, local optimal solution and other defects, so a spectrum allocation method of cognitive radio based on catfish particle swarm optimization algorithm （CE-PSO） is proposed in this paper. Firstly, mathematical model of the cognitive radio spectrum allocation is established, and maximum benefit is taken as the optimization goal, and then the ＂catfish effect＂ is introduced into PSO to keep the diversity of particle swarm to find the optimal spectrum optimal allocation scheme by the information exchange among the particles. The simulation experiment is carried out to test the performance of CE-PSO algorithm. The results show that CE-PSO algorithm overcomes the defects of PSO algorithm, and can quickly and accurately find the optimal spectrum allocation scheme, and can better achieve the maximum system efficiency, so it can meet the application requirements of cognitive radio systems.
出处
《电视技术》
北大核心
2014年第7期145-148,189,共5页
Video Engineering
关键词
认知无线电
频谱分配
粒子群算法
鲶鱼效应
cognitive radio
spectrum allocation
particle swarm optimization algorithm
catfish effect
