基于典型相关分析的确定性MIMO信道阶数估计

Marta Arroyo, J. Vía, I. Santamaría
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引用次数: 1

摘要

信道阶数估计是盲信道识别/均衡算法中的关键步骤。提出了一种新的多输入多输出(MIMO)信道阶数估计准则。该方法将盲均衡问题转化为一组嵌套的典型相关分析(CCA)问题,其解由广义特征值(GEV)问题给出。特别地,信道序估计是由连续GEVs的最大广义特征值的多重性得到的。与以往的方法不同,该方法即使在小数据集、彩色信号和头尾项较小的通道情况下也具有良好的性能,并通过一些数值算例进行了说明。
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Deterministic MIMO channel order estimation based on canonical correlation analysis
Channel order estimation is a critical step in blind channel identification/equalization algorithms. In this paper, a new criterion for channel order estimation of multiple-input multiple-output (MIMO) channels is presented. The proposed method relies on the reformulation of the blind equalization problemas a set of nested canonical correlation analysis (CCA) problems, whose solutions are given by a generalized eigenvalue (GEV) problem. In particular, the channel order estimates are obtained from the multiplicity of the largest generalized eigenvalue of the successive GEVs. Unlike previous approaches, the performance of the proposed method is good even in the cases of small data sets, colored signals, and channels with small head and tails terms, which is illustrated by means os some numerical examples.
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