基于独立分量分析的大规模MIMO盲导净化

Ebrahim Amiri, R. Müller, W. Gerstacker
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引用次数: 8

摘要

研究了一个具有先导污染的大规模多输入多输出系统。为了改进信道估计,提出了一种基于复独立分量分析(cICA)的盲数据辅助估计方法,以互信息率作为对比函数。该方法首先通过子空间投影抑制干扰和噪声,然后对上行数据进行盲提取。最后,根据目标小区中所有用户的上行数据估计,得到信道的最小二乘估计。仿真结果证实:1)导频污染效应随着接收天线数量和数据长度的增加而衰减;2)在考虑的场景下,所提出的方法优于基于峰度的cICA和纯子空间投影。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind Pilot Decontamination in Massive MIMO by Independent Component Analysis
A massive multiple-input multiple-output system with pilot contamination is considered. In order to improve channel estimation we propose a blind data-aided method based on complex independent component analysis (cICA) with the aid of mutual information rate as contrast function. In this approach, interference and the noise are first suppressed by subspace projection, then the uplink data is extracted blindly. Finally, based on the estimated uplink data of all the users in the cell of interest, the least square estimate of the channel is obtained. Simulation results confirm that 1) the pilot contamination effect decays, as the number of receive antennas and the data length increase; and 2) that the proposed approach outperforms both kurtosis-based cICA and pure subspace projection for the considered scenarios.
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