FP-PSO算法在认知无线电频谱分配上的应用研究

The application research on cognitive radio spectrum allocation based FP-PSO algorithm

针对认知无线电频谱分配时分配率低、用户满意度不高的问题,提出了适应值预测的粒子群优化算法(FPPSO),利用FP-PSO算法优化了认知无线电频谱分配过程,设计的适应值预测方法提高了分配效率的同时满足了实时性要求。实验结果表明:FP-PSO算法在降低部分网络效益的同时,获得了比颜色敏感图着色算法(CSGC)更优的用户满意度、平均分配时间和用户公平性。

As distribution rate and customer satisfaction were not high in the process of the spectrum allocation for cognitive radio, Fitness Prediction of Particle Swarm Optimization （FP-PSO） was proposed , using FP-PSO algorithm to optimize the cognitive radio spectrum allocation process , fitness prediction methods is designed to improve the allocation efficiency while meeting the real-time requirements. The experimental results showed that： FP-PSO algorithm reduced a part of network bandwidth benefit, at the same user satisfaction, allocation efficiency, the average assignment time and the user fairness are better than the color sensitive graph coloring algorithm （CSGC）.