A noble circularly symmetric Gaussian covariance matrix based channel estimation scheme for large-scale MIMO systems

M. Hanif, M. Lee, S. Song
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引用次数: 2

Abstract

With large-scale Multiple-input Multiple-output (MOMO), we think of a system that use antenna arrays with an order of magnitude more elements than in systems being built nowadays, say a hundred antennas or more. As it is known that, the more antennas the transmitter/receiver is equipped with, the more the possible signal paths, the better the performance in terms of data rate and link reliability. However, channel estimation in large-scale MIMO is said to be hampered by the pilot contamination effect, constitute a major reduction for overall system performance. In this paper, we present a novel approach which tackles this problem by enabling a covariance formulation between cells during the channel estimation phase itself, could leads to improver the system performance. Here we present a noble scheme title as large-scale MIMO channel estimation based on circularly symmetric Gaussian covariance matrix. The numerical result shows the significance of proposed scheme.
基于高贵圆对称高斯协方差矩阵的大规模MIMO信道估计方案
对于大规模多输入多输出(MOMO),我们想到的是一个系统,它使用的天线阵列的元素比现在正在建造的系统多一个数量级,比如100个天线或更多。众所周知,发射机/接收机配置的天线越多,可能的信号路径越多,在数据速率和链路可靠性方面的性能也就越好。然而,大规模MIMO中的信道估计受到导频污染效应的阻碍,这是降低系统整体性能的主要原因。在本文中,我们提出了一种新的方法,通过在信道估计阶段本身实现单元之间的协方差公式来解决这个问题,可以提高系统性能。本文提出了一种基于圆对称高斯协方差矩阵的大规模MIMO信道估计方案。数值结果表明了所提方案的意义。
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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