基于差分进化算法的认知用户有效吞吐量优化  

Optimization of cognitive users-effective throughput based on differential evolution algorithm

作　　者：毕晓君[1] 薄萍萍 

机构地区：[1]哈尔滨工程大学信息与通信工程学院,哈尔滨150001

出　　处：《计算机应用研究》2012年第5期1877-1879,共3页Application Research of Computers

摘　　要：针对目前研究感知时间和有效吞吐量权衡问题的方法存在收敛速度慢、不能满足实时性要求的问题,提出一种基于差分进化算法的有效吞吐量优化方法,利用差分进化算法参数少、操作算子简单、全局搜索能力强和收敛速度快等优点,保证了在固定帧长下快速寻找到最优感知时间,使认知用户吞吐量达到最大。实验仿真结果表明,在同等条件下,提出的差分进化算法处理吞吐量优化问题时能达到接近理论值的精度,且收敛速度较快。According to the problem of the slow convergence speed and the requirements of real-time unable to be met in the method of the study about the balance of perception of time and the effective throughput,this paper put forward a differential evolution algorithm to optimize effective throughput.This method achieved the purpose that optimal perceptual time could be quickly found and cognitive user throughput reached the maximum in the fixed frame length by using the advantages of differential evolution algorithm with fewer parameters,simple operation operators,the global searching ability and fast convergence.The experimental result shows that under the same conditions,the effective throughput is close to the theoretical precision value and the algorithm＇s convergence speed is faster because of the use of differential evolution algorithm.

关 键 词：认知无线电 感知时间 有效吞吐量 差分进化算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]