首页 | 本学科首页   官方微博 | 高级检索  
     

基于Social Cognition粒子群算法多用户检测
引用本文:许耀华,胡艳军.基于Social Cognition粒子群算法多用户检测[J].无线电通信技术,2006,32(6):30-32,38.
作者姓名:许耀华  胡艳军
作者单位:安徽大学电子科学与技术学院,安徽,合肥,230039
基金项目:安徽省高校青年教师科研项目
摘    要:最优多用户检测方法具有最优性能,但复杂度高,利用优化算法求解可以降低实现复杂度。粒子群算法是一种简单有效的新型群智能优化算法,研究了一种Socialcognition模型简化粒子群算法,并应用于大用户量CDMA多用户检测问题,主要考虑降低算法复杂度,提高算法的实现效率。分析及仿真表明该方法在系统用户数量较大时具有较好性能。

关 键 词:码分多址  多用户检测  离散粒子群优化算法  社会认知理论
文章编号:1003-3114(2006)06-30-3
收稿时间:2006-01-16
修稿时间:2006-01-16

Social cognition particle swarm optimization algorithm for multiuser detector in CDMA communication system
XU Yao-hua,HU Yan-jun.Social cognition particle swarm optimization algorithm for multiuser detector in CDMA communication system[J].Radio Communications Technology,2006,32(6):30-32,38.
Authors:XU Yao-hua  HU Yan-jun
Affiliation:School of Electronic Science and Technology, Anhui University, Hefei Anhui 230039, China
Abstract:The optimal multiuser detector has the best performance but it has very high computation complexity. Particle swarm optimization algorithm is based on swarm intelligence, and has the properties of rapid convergence and simple rules. The paper studies a social cognition type of discrete particle swarm optimization algorithm for the multi-user detection.The complexity decreasing and search quality and efficiency improvement are mainly considered. The analysis and simulation results show that it has better performance when the number of system users is higher.
Keywords:code division multiple access (CDMA)  multiuser detection (MUD)  discrete particle swarm optimization algorithm (DPSO)  social cognition theory
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号