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A comparative study of heuristic algorithms: GA and UMDA in spatially multiplexed communication systems

机译:空间复用通信系统中启发式算法GA和UMDA的比较研究

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摘要

A performance comparison of genetic algorithm (GA) and the univariate marginal distribution algorithm (UMDA) as decoders in multiple input multiple output (MIMO) communication system is presented in this paper. While the optimal maximum likelihood (ML) decoder using an exhaustive search method is prohibitively complex, simulation results show that the GA and UMDA optimized MIMO detection algorithms result in near optimal bit error rate (BER) performance with significantly reduced computational complexity. The results also suggest that the heuristic based MIMO detection outperforms the vertical bell labs layered space time (VBLAST) detector without severely increasing the detection complexity. The performance of UMDA is found to be superior to that of GA in terms of computational complexity and the BER performance.
机译:提出了遗传算法(GA)和单变量边际分布算法(UMDA)作为多输入多输出(MIMO)通信系统中的解码器的性能比较。尽管使用穷举搜索方法的最佳最大似然(ML)解码器非常复杂,但仿真结果表明,GA和UMDA优化的MIMO检测算法可产生接近最佳的误码率(BER)性能,并显着降低了计算复杂性。结果还表明,基于启发式的MIMO检测在不严重增加检测复杂度的情况下,优于垂直贝尔实验室分层时空(VBLAST)检测器。在计算复杂度和BER性能方面,发现UMDA的性能优于GA。

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