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Max-Min SINR Dependence on Channel Correlation in Line-of-Sight Massive MIMO

机译:视线大规模MIMO中最大-最小SINR对信道相关性的依赖

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Under LoS (line-of-sight) propagation and the assumption of perfect CSI (channel state information), for either MR (maximum-ratio) or ZF (zero-forcing) precoding/decoding, one can readily obtain Massive MIMO (multi-input multi-output) per-user effective SINR for single-cell scenarios. LoS channels are typically less correlated than IID (independent and identically distributed) Rayleigh channels, but the maximum correlation for LoS is typically much greater than for IID Rayleigh. This motivates an investigation of the dependence of max-min SINR on the maximum channel correlation. Perron-Frobenius theory and the classical Fischer inequality are used to establish some rigorous and explicit upper bounds on the effective max-min SINR (signal to interference plus noise ratio) that depend on the maximum channel correlation. These upper bounds provide an accurate description of this dependence relationship, and readily facilitate system performance analyses and scheduler designs without simulations. In high channel correlation environment, ZF can perform substantially better than MR in the downlink but the opposite is true for the uplink.
机译:在LoS(视线)传播和完美CSI(信道状态信息)假设下,对于MR(最大比率)或ZF(迫零)预编码/解码,可以轻松获得Massive MIMO(多输入(多输出)每用户有效单INR情况下的SINR。与IID(独立且分布相同)的瑞利信道相比,LoS信道的相关性通常较低,但是LoS的最大相关性通常比IID瑞利的相关性大得多。这激发了对最大-最小SINR对最大信道相关性的依赖性的研究。使用Perron-Frobenius理论和经典的Fischer不等式来建立有效最大-最小SINR(信号与干扰加噪声比)的严格和明确的上限,该上限取决于最大信道相关性。这些上限提供了这种依赖关系的准确描述,并且无需仿真即可轻松促进系统性能分析和调度程序设计。在高信道相关性环境中,ZF在下行链路上的性能可以比MR好得多,但在上行链路上则相反。

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