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Performance Evaluation of Non-coherent DPSK Signal Detection Algorithms in Massive MIMO Systems

机译:大型MIMO系统中非相干DPSK信号检测算法的性能评估

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In the 5G technology, massive MIMO is a very important share, where the base station is equipped with huge number of antennas. Massive MIMO can significantly improve signal strength, channel rate, power consumption, and throughput. However, there are major signal detection challenges that face the system such as the complexity of channel estimation. Most of the commonly used detection techniques in massive MIMO are coherent detection, which requires complex channel estimation techniques. In this paper, non-coherent detection is used to avoid the complexity of channel estimation in massive MIMO systems by using differential phase shift keying modulation (DPSK). The performance of Differential Detection (DD), sorted Decision Feedback Differential Detection (DFDD), Multiple Symbol Differential Detection (MSDD) and Multiple Symbol Differential Sphere Detection (MSDSD) algorithms for massive MIMO are studied, implemented and compared together along with coherent Minimum Mean Square Error (MMSE) for the same studied massive MIMO system model. Results showed that, MSDSD outperforms DFDD with trade off complexity and time. Nonetheless for channels with high coherence time, the transmission burst length is increased for better performance. However, the complexity and time needed for MSDSD is higher than DFDD.
机译:在5G技术中,大规模的MIMO是一个非常重要的份额,基站配备了大量的天线。大规模的MIMO可以显着提高信号强度,通道速率,功耗和吞吐量。然而,存在面对诸如信道估计的复杂性等系统的主要信号检测挑战。大多数常用的MIMO中的常用检测技术是相干检测,这需要复杂的信道估计技术。在本文中,使用不相干检测来避免通过使用差分相移键控调制(DPSK)来避免大规模MIMO系统中信道估计的复杂性。研究,分类检测(DD),分类判定反馈差分检测(DFDD),多个符号差分检测(MSDD)和多个符号差分球体检测(MSDSD)算法的性能,用于大规模MIMO,并将其实施和比较以及相干最小平均值相同研究的大规模MIMO系统模型的方误差(MMSE)。结果表明,MSDSD优于DFDD,具有折衷复杂性和时间。尽管如此,对于具有高相干时间的通道,传输突发长度增加以获得更好的性能。但是,MSDSD所需的复杂性和时间高于DFDD。

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