基于二阶统计量的相关信源盲均衡与辨识算法研究

发布时间：2018-05-14 07:26

本文选题：盲均衡 + 盲辨识　；参考：《山东农业大学学报(自然科学版)》2014年05期

【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。
[Abstract]:In this paper, a blind equalization and identification algorithm for correlated sources based on second-order statistics is presented. Using the autocorrelation matrix of received signals, the channel parameter estimation problem is transformed into a eigenvector problem related to the autocorrelation matrix. The simulation results show that the algorithm has a good effect on channel identification and equalization in which the input is a related source. The system identification can be completed with only a short observation data. The second order algorithm can reduce the computational complexity and effectively reduce the inter-symbol interference (ISI).
【作者单位】：内蒙古科技大学包头师范学院;
【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)
【分类号】：TN911.5

【共引文献】