一种低复杂度天线感知空间协方差矩阵估计方法

Shangbin Wu, Xiaoqing Zhang
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引用次数: 0

摘要

提出了一种低复杂度的天线感知(ALA)协方差矩阵估计方法。在估计过程中,假设在估计器处天线布局是已知的。利用这些信息,估计器找到具有统计上相等的协方差值的天线对,并将其协方差值设为所有这些天线对协方差值的平均值。讨论了均匀线性阵列(ULA)和均匀平面阵列(UPA)的ALA。这种方法利用了协方差矩阵没有完全自由度的优点。然后,将ALA协方差矩阵方法应用于多单元网络。仿真结果表明,该方法在均方误差和下行频谱效率方面比广泛使用的viaQ方法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Low-Complexity Antenna-La-Aware Spatial Covariance Matrix Estimation Method
This paper proposed a low-complexity antenna-la-aware (ALA) covariance matrix estimation method. In the estimation process, antenna layout is assumed known at the estimator. Using this information, the estimator finds antenna pairs with statistically equivalent covariance values and sets their covariance values to the average of covariance values of all these antenna pairs. ALA for both uniform linear array (ULA) and uniform planar array (UPA) is discussed. This method takes the benefit that covariance matrices do not have full degrees of freedom. Then, the proposed ALA covariance matrix method is applied to a multi-cell network. Simulations have demonstrated that the proposed method can provide better performance than the widely used viaQ method, with respect to mean square errors and downlink spectral efficiencies.
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