典型相关分析的改进型RLS盲均衡算法研究

本文介绍了一种适用于单输入多输出(SIMO)系统中的自适应盲均衡算法——典型相关分析的递归最小二乘自适应盲均衡(CCA-RLS),并在此基础上提出了一种改进算法——典型相关分析的可变遗忘因子递归最小二乘自适应盲均衡(CCA-MRLS)。CCA-MRLS盲均衡算法把典型相关分析(CCA)与MRLS算法结合在一起应用于SIMO系统中,不同于其他基于二阶统计量(SOS)算法,它能够在获得最佳均衡器的同时还能够得到系统的最佳联合输出。仿真结果表明,提出的CCA-MRLS算法与CCA-RLS相比,具有更低的残留码间干扰和更快的收敛速度。

Research on the Blind Equalization Algorithm of Modified RLS Based on Canonical Correlation Analysis

In this paper,a new blind equalization algorithm suitable for single-input multiple-output(SIMO) systems is introduced based on a recursive least squares algorithm and canonical correlation analysis(CCA-RLS),and a modified recursive least squares algorithm with a variable forgetting factor based on canonical correlation analysis(CCA-MRLS) is proposed.Combining CCA with MRLS,the CCA-MRLS algorithm is applied to the SIMO systems.Unlike other approaches,the CCA-RLS obtains simultaneously the optimal equalizers...