基于二阶统计量的相关信源盲均衡与辨识算法研究  

Blind Equalization and Identification Algorithm on Correlated Input Signal Based on Second Order Statistics

作　　者：陈静[1] 

机构地区：[1]内蒙古科技大学包头师范学院,内蒙古包头014030

出　　处：《山东农业大学学报（自然科学版）》2014年第5期755-760,共6页Journal of Shandong Agricultural University：Natural Science Edition

基　　金：国家自然基金(61163025);包头师范学院青年科学基金(BSYKJ2011-24);包头师院教改课题(BSJG13Y034)

摘　　要：本文给出了一种基于二阶统计量的相关信源盲均衡与辨识算法,应用接收信号的自相关矩阵将信道参数估计问题转化为与自相关矩阵有关的特征向量求解问题。仿真结果表明该算法对输入为相关信源的信道辨识与均衡具有较好的效果,只用较短的观察数据就可以完成系统的辨识,二阶算法运算量明显减小,且有效地降低了码间干扰。In this paper, we centered on the correlated input signal implementation of blind equalization algorithm based on the second-order statistics. The estimation of channel parameters could be transferred into solving feature vector by using the self-correlation matrix of the receiving signal. The emulation showed that this algorithm which used little data exhibited better equalization and identification results for the correlated input signal, and effectively decreased the effect of ISI .

关 键 词：盲均衡 盲辨识 过采样 前向线性预测误差 二阶统计量 

分 类 号：TN911.72[电子电信—通信与信息系统]