Effect of spatial correlation on blind source separation in MIMO systems

A. Cole-Rhodes, Ermias Shiferaw, F. Moazzami
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Abstract

In this work, we investigate the effect of spatial correlation in MIMO channels on the performance of multistage CMA+AMA blind equalization and signal separation method. A modified Constant Modulus Algorithm (CMA), which minimizes a linear combination of the CMA and Alphabet Matched Algorithm (AMA) is used as the blind equalizer for blocks of QAM signals. It has been shown that a multistage CMA+AMA equalizer with a blind channel estimator among stages successfully equalizes and separates multiple data signals when the channel model used is that of identically and independently distributed (iid) Rayleigh fading. In this paper a different channel model from work of H.Bolcskei is adopted to investigate the effectiveness of multistage CMA+AMA equalizer and the channel estimator on the channels which are spatially correlated. The performance of the multistage equalization and estimation scheme is compared with uncorrelated iid channels versus transmit and/or receive correlated channels and presented in terms of symbol error rate (SER) and mean square error MSE) for the signals and for the channel estimate.
空间相关对MIMO系统盲源分离的影响
在这项工作中,我们研究了MIMO信道中空间相关性对多级CMA+AMA盲均衡和信号分离方法性能的影响。一种改进的恒模算法(CMA),它最小化了CMA和字母表匹配算法(AMA)的线性组合,被用作QAM信号块的盲均衡器。研究表明,当信道模型为同独立分布瑞利衰落时,多级CMA+AMA均衡器在各级间采用盲信道估计器,能够成功地均衡和分离多个数据信号。本文采用不同于H.Bolcskei的信道模型,研究了多级CMA+AMA均衡器和信道估计器对空间相关信道的有效性。将多级均衡和估计方案的性能与不相关的iid信道与发送和/或接收相关信道进行比较,并以信号和信道估计的符号错误率(SER)和均方误差(MSE)表示。
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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