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基于进化算法的多用户检测器 被引量:4

Multiuser Detector Based on Evolutionary Algorithm
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摘要 粒子群算法PSO遗传算法(Particle Swarm Optimization)是由Kennedy和Eberhart于1995年提出的一种新的进化算法,PSO能够以一种更简便、快速的方式来完成和遗传算法(GA)一样的功能。本文在PSO算法思想的基础上提出了两种新的多用户检测算法:BEP(Binary Evolution Programming)算法,BPSO(Binary PSO,BPSO)算法。分别基于这两种算法构造了新的多用户检测器。仿真结果表明,这两种新的多用户检测器的抗误码性能比传统多用户检测器和基于遗传算法的多用户检测器都好,并且新的检测器的收敛速度明显比遗传算法检测器快。 A new method named Particle Swarm Optimization (PSO) has been proposed by Kennedy and Eberhart (1995) and it can accomplish the same goal as GA in a new and faster way. In this paper a new binary algorithm, which derives from conventional PSO conception and named BEP algorithm, has been proposed. Then the BEP and Binary PSO (BPSO) have been applied to solve the multiuser detection problems in the CDMA system. The simulation results proved that BEP Detector (BEPD) and BPSO Detector (BPSOD) have better capability against error bit and converge more quickly than Conventional Detector (CD) and GA Detector (GAD).
作者 阎石 吕振肃
出处 《电子与信息学报》 EI CSCD 北大核心 2006年第2期223-227,共5页 Journal of Electronics & Information Technology
关键词 多用户检测 遗传算法 进化规则 粒子群优化算法 MUD, Genetic algorithm, Evolution programming, Particle swarm optimization
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参考文献8

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共引文献4

同被引文献18

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