MC-CDMA系统中基于粒子群算法的多用户检测

提出了一种频率选择性信道下使用多天线分集接收的多载波码分多址(MC-CDMA)系统中基于粒子群算法(PSO)的多用户检测(MUD).当采用多天线分集接收时,各个天线接收的信号经历了相互独立的衰落,导致不同天线分支对应的匹配度函数相互独立.为解决多天线分集接收的多目标优化问题,提出了虚拟Pareto前端的概念,并使粒子按照Pareto优化准则进行速度和位置更新.仿真结果表明,所提方案获得了增强的开发和探索能力,其性能优于常规粒子群算法和多目标遗传算法.

PSO-based multiuser detection for MC-CDMA systems

A particle swarm optimization(PSO) based multiuser detection(MUD) is proposed for the receive-diversity-aided multi-carrier code-division multiple-access(MC-CDMA) systems in frequency-selective fading channel.Due to the receive-diversity,the signals received at the different antennas are faded independently,resulting in an independent cost function for each antenna.To resolve the multi-objective dilemma when choosing one signal estimation for multiple receive antenna-branches,the virtual Pareto front is introduced,and each particle updates it's velocity and position in a Pareto optimal way.Simulations show that the proposed scheme has the enhanced capabilities of exploration and exploitation and has better performance than the conventional PSO and multi-objective genetic algorithm.