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Simplified MMSE Detectors for Turbo Receiver in BICM MIMO Systems

Simplified MMSE Detectors for Turbo Receiver in BICM MIMO Systems

作     者:韩娟 唐超 王秋菊 朱子元 唐杉 

作者机构:Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences Beijing Sylincom Technologies Co. Ltd. School of Instrumentation Science and Opto-Electronics Engineering Beihang University Beijing Science and Technology Information Center 

出 版 物:《Journal of Computer Science & Technology》 (计算机科学技术学报(英文版))

年 卷 期:2013年第28卷第3期

页      面:445-453页

核心收录:

学科分类:0810[工学-信息与通信工程] 08[工学] 081001[工学-通信与信息系统] 

基  金:supported by the Major Project of the Beijing Natural Science Foundation under Grant No. 4110001 the National Science and Technology Major Project of China under Grant No. 2012ZX03001021-003 

主  题:bit interleaved coded modulation multiple-input multiple-output ordered soft parallel interference cancellation soft parallel interference cancellation simplified minimum mean square error, turbo receiver 

摘      要:In this article, two methods adopting simplified minimum mean square error (MMSE) filter with soft parallel interference cancellation (SPIC) are discussed for turbo receivers in bit interleaved coded modulation (BICM) multiple-input multiple-output (MIMO) systems. The proposed methods are utilized in the non-first iterative process of turbo receiver to suppress residual interference and noise. By modeling the components of residual interference after SPIC plus the noise as uncorrelated Gaussian random variables, the matrix inverse for weighting vector of conventional MMSE becomes unnecessary. Thus the complexity can be greatly reduced with only slight performance deterioration. By introducing optimal ordering to SPIC, performance gap between simplified MMSE and conventional MMSE further narrows. Monte Carlo simulation results confirm that the proposed algorithms can achieve almost the same performance as the conventional MMSE SPIC in various MIMO configurations, but with much lower computational complexity.

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