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。
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.
出处
《无线电通信技术》
2006年第6期30-32,38,共4页
Radio Communications Technology
基金
安徽省高等学校青年教师科研资助计划项目(2005jp1032zd)
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
code division multiple access （CDMA）
muhiuser detection （MUD）
discrete particle swarm optimization algorithm （DPSO）
social cognition theory
