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Analysis on the Empirical Spectral Distribution of Large Sample Covariance Matrix and Applications for Large Antenna Array Processing

机译:大型协方差矩阵的实证光谱分布及大型天线阵列处理的应用分析

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摘要

This paper addresses the asymptotic behavior of a particular type of information-plus-noise-type matrices, where the column and row numbers of the matrices are large and of the same order, while signals have diverged and the time delays of the channel are fixed. We prove that the empirical spectral distribution of the large dimension sample covariance matrix and a well-studied spiked central Wishart matrix converge to the same distribution. As an application, an asymptotic power function is presented for the generalized likelihood ratio statistics for testing the presence of the signal in large array signal processing.
机译:本文解决了特定类型的信息 - 正噪声型矩阵的渐近行为,其中矩阵的列和行数大而且相同的顺序,而信号已经分配,​​并且通道的时间延迟是固定的。我们证明了大维样本协方差矩阵的经验光谱分布和研究得良好的尖刺中心愿望矩阵会聚到相同的分布。作为应用,呈现渐近功率函数用于在大阵列信号处理中测试信号的存在,呈现广义似然比统计。

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