基于高阶统计量的MIMO系统辨识与均衡算法

基于高阶统计量的MIMO系统辨识与均衡算法

王宏志¹, 孙树宇¹, 何斌², 姚亮¹

1. 长春工业大学计算机科学与工程学院, 长春 130012; 2. 中国科学院长春光学精密机械与物理研究所, 长春 130033

收稿日期:2008-06-23 修回日期:1900-01-01 出版日期:2009-01-26 发布日期:2009-01-26
通讯作者: 何斌

Identification and Equalization Algorithm for MIMO System Based on Higher Order Statistics

WANG Hongzhi¹, SUN Shuyu¹, HE Bin², YAO Liang¹

1. College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China; 2. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

Received:2008-06-23 Revised:1900-01-01 Online:2009-01-26 Published:2009-01-26
Contact: HE Bin

摘要/Abstract

摘要： 将高阶统计量与盲分离的移位阻断SHIBBS算法相结合, 利用高阶统计量能辨识非最小相位系统和SHIBBS算法分离效果与计算量适中的特点, 提出一种在频域内对MIMO系统进行辨识的方法；针对在此解混后的信号存在排序不确定性的问题, 直接在频域上采用互四阶累计量, 从而很好地对信号进行了分离；针对信号的比例模糊问题, 利用LMS自适应的恒模算法（CMA）对排序后信号均衡补偿, 仿真实验证明了此算法的有效性.

关键词: 频域, MIMO系统, 高阶统计量, 辨识与均衡

Abstract: Based on the combination of higher order statistics that can identify non-minimum phase system with shift block method of blind separation (SHIBBS) algorithm which is good in separation and moderate amount of computation, an algorithm was proposed to identify the multi-input and multi-output (MIMO) system in frequency domain; but the received signals are uncertain in permutation, which is solved by means of cross fourth-order statistics and the signals are separated well. To the problem of scale ambiguity, the constant modulus algorithm employing the LMS self-adaptation is used in equalizing and compensating for the sorted signals. Simulations show that the proposed algorithm is feasible and practical.

Key words: frequency domain, MIMO system, higher order statistics, identification and equalization

中图分类号:

TN911.72

王宏志, 孙树宇, 何斌, 姚亮. 基于高阶统计量的MIMO系统辨识与均衡算法[J]. J4, 2009, 47(01): 115-119.

WANG Hongzhi, SUN Shuyu, HE Bin, YAO Liang. Identification and Equalization Algorithm for MIMO System Based on Higher Order Statistics[J]. J4, 2009, 47(01): 115-119.