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Uplink Massive MIMO for Channels with Spatial Correlation

机译:具有空间相关性的信道的上行链路大规模MIMO

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A massive MIMO system entails a large number of base station antennas M serving a much smaller number of users. This leads to large gains in spectral and energy efficiency compared with other technologies. As the number of antennas M grows, the performance of such systems gets limited by pilot contamination interference. Large Scale Fading Precoding/Postcoding (LSFP) was proposed for mitigation of pilot contamination, and it was shown that in channels without spatial correlation (uncorrelated base station antennas) LSFP leads to large spectral-efficiency gains. It was recently proven that if a channel has spatial correlation, then one can use this correlation to drastically reduce the pilot contamination interference in the asymptotic regime as M → ∞. In this work, we analyze the performance of Uplink (UL) transmission of massive MIMO systems with finitely many antennas M for channels with spatial correlation. We extend the idea of LSFP to correlated channel models and derive SINR expressions that depend only on slow fading channel components for such systems with and without LSFP. These simple expressions lead us to simple algorithms for transmit power optimization. As a result, we obtain a multi-fold increase in data transmission rates.
机译:大规模的MIMO系统需要为大量用户服务的大量基站天线M。与其他技术相比,这可以大大提高频谱效率和能效。随着天线M的数量的增加,这种系统的性能受到飞行员污染干扰的限制。提出了大规模衰落预编码/后编码(LSFP)以减轻导频污染,并且研究表明,在没有空间相关性的信道(不相关的基站天线)中,LSFP会导致较大的频谱效率增益。最近证明,如果一个信道具有空间相关性,则可以使用这种相关性来极大地减少渐近状态下M→∞的导频污染干扰。在这项工作中,我们分析了具有空间相关性信道的,具有有限多个天线M的大规模MIMO系统的上行链路(UL)传输性能。我们将LSFP的概念扩展到相关的信道模型,并得出SINR表达式,该表达式仅依赖于具有和不具有LSFP的此类系统的慢衰落信道分量。这些简单的表达式使我们找到了用于发射功率优化的简单算法。结果,我们获得了数据传输速率的多倍增长。

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