Diversity Assisted Block PIC for synchronous CI/MC-CDMA uplink system using Genetic Algorithms

S. Maity, S. Hati, S. Maity
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引用次数: 9

Abstract

This paper investigates the scope of genetic algorithms (GA) for performance improvement in multiuser detection through the realization of an efficient block parallel interference cancellation (PIC) technique in a synchronous carrier interferometry/MC-CDMA (multicarrier-code division multiple access) uplink system. Simulation is carried out on frequency selective Rayleigh fading channel and antenna diversity is applied at base station (BS). Weight factors for diversity implementation are calculated based on the value of SIR (signal to interference ratio) of individual antenna system. GA is used to partition different users into groups of different blocks namely very strong, strong, weak and very weak based on the normalized magnitudes of their decision variables. We have reported the performance of the GA based block PIC system of four block, three block and two block with conventional PIC. A significant improvement in performance and capacity is seen with GA based block PIC relative to conventional PIC at the cost of slight increase in computation complexity. Simulation results show that BER is reduced as the number of users are divided into more number of blocks and the optimal partitioning of the blocks obtained by using GA.
基于遗传算法的分集辅助块PIC同步CI/MC-CDMA上行系统
本文通过在同步载波干涉/多载波码分多址(MC-CDMA)上行系统中实现有效的块并行干扰消除(PIC)技术,研究了遗传算法(GA)在多用户检测中的性能改进范围。对频率选择性瑞利衰落信道进行了仿真,并在基站中应用了天线分集。分集实现的权重因子是根据单个天线系统的信干扰比(SIR)值来计算的。遗传算法根据用户决策变量的归一化大小,将不同的用户划分为非常强、强、弱和非常弱的不同块组。我们报道了基于遗传算法的四块、三块和两块块PIC系统与传统PIC的性能。与传统PIC相比,基于遗传算法的块PIC在性能和容量方面有了显着改善,但代价是计算复杂性略有增加。仿真结果表明,利用遗传算法将用户数量划分为更多的块,并对块进行最优划分,可以降低误码率。
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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