摘要
基于传统遗传算法的多用户检测器易陷入局部最优解且收敛较慢,影响实时性。本文利用混沌优化算法的优势来弥补遗传算法的这一缺陷,使两种算法优势互补,同时采用具有“迁移策略”的并行搜索机制,提出了一种新的次优多用户检测方法———并行混沌遗传混合算法(PCGA),并在同步CDMA系统中对其性能进行了研究。仿真结果表明,我们提出的这种算法能有效克服传统遗传算法易陷入局部极小的问题,计算量小,收敛速度快,在抗干扰与克服“远-近”效应方面均有明显的优势。
The multiuser detector based on conventional genetic algorithms has disadvantages of easily getting into part extremum and slow converging speed. Using the chaos algorithm to make up this disadvantages, and at the same time, using the parallel search mechanism with transfer strategy, a new algorithm for multiuser detection(MUD) parallel chaos genetic algorithm is proposed in this paper. Simulation resuits show that this method can. efficiently overcome the problem of easily getting into part extremum, improve convergence rate and also resist the near- far effect.
出处
《电讯技术》
2005年第6期53-57,共5页
Telecommunication Engineering
基金
国家自然科学基金资助项目(10147201)
广西高校百名中青年学科带头人资助项目(桂教人[2002]467号)
关键词
码分多址
多用户检测
并行混沌遗传混合算法
并行遗传算法
混沌优化算法
Code - division multiple access (CDMA)
Multiuser detection (MUD)
Parallel chaos genetic algorithm
Parallel genetic algorithms
Chaos Optimal Algorithm(COA)