基于Pareto最优粒子群算法的STBC-MIMO系统多用户检测

Jianping An, Binbin Xu
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引用次数: 0

摘要

针对空时分组码(STBC)多输入多出(MIMO)系统,提出了一种新的粒子群优化(PSO)多用户检测(MUD)方法。该策略从多目标优化(MO)的角度考虑具有多样性接收的多目标优化(MUD)问题,提出了一种基于Pareto-optimal的pso算法。该方法利用帕累托最优值,有效地挖掘和利用每个接收天线独立的接收信号的信道衰落信息,从而提高启发式搜索最优解的能力。仿真结果表明,该方法具有较好的误码率性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiuser Detection in STBC-MIMO Systems Based on Pareto Optimality Particle Swarm Optimization Algorithm
In this paper, we present a novel particle swarm optimization (PSO) multiuser detection (MUD) approach for multiple-in-multiple-out (MIMO) systems with space-time block code (STBC). The proposed strategy consider the MUD problem with diversity reception from a multiobjective optimization (MO) viewpoint and develop a Pareto-optimal PSO-based (POPSO) algorithm. By taking advantage of the Pareto-optimal values, this approach effectively explores and exploits the channel fading information of received signals that are independent for each receive antenna, and accordingly improves the heuristic search ability to find the optimal solution. The proposed approach is shown to achieve superior bit-error-rate (BER) performance by simulations.
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