Particle swarm optimization based MUD for overloaded MC-CDMA system

M. Choudhry, M. Zubair, I. Qureshi
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引用次数: 2

Abstract

The overloaded CDMA system, in which the number of users is larger than the dimension of signal space experiences a very serious problem of multiple access interference which is the major limiting factor for the channel capacity. In this letter we used multicarrier communication to resolve the problem of overloading. Computational complexity associated with optimum maximum likelihood detector (MLD) in wideband code division multiple access (WCDMA) systems is also addressed by using the particle swarm optimization (PSO) algorithm. In the proposed scheme, large number of users in an overloaded system is divided in groups. A carrier is modulated with the composite signal of each group. The carriers of each group are orthogonal to each other. Detection of individual users in a particular group is accomplished through PSO algorithm. PSO algorithm lowers the search space compared to MLD. Simulation results show that PSO algorithm avoids being trapped in any local minima and gives a much faster convergence compared to MLD. It also performed better than other suboptimal detectors.
基于粒子群优化的MC-CDMA过载系统MUD
在用户数量大于信号空间维数的超载CDMA系统中,多址干扰问题十分严重,是限制信道容量的主要因素。在这封信中,我们使用多载波通信来解决超载问题。利用粒子群优化算法解决了宽带码分多址(WCDMA)系统中最优最大似然检测器(MLD)的计算复杂性。在该方案中,将超载系统中的大量用户进行分组。用每一组的复合信号调制载波。每组的载波彼此正交。通过粒子群算法实现对特定组中的单个用户的检测。与MLD相比,粒子群算法降低了搜索空间。仿真结果表明,粒子群算法避免了陷入局部极小值的问题,收敛速度远快于MLD算法。它也比其他次优检测器表现得更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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