Blind adaptive identification of 2-channel systems using bias-compensated RLS algorithm

被引：6

作者：

Jia, Lijuan ^{[1
]}

Lou, Jian ^{[1
]}

Yang, Zijiang ^{[2
]}

机构：

[1] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China

[2] Ibaraki Univ, Dept Intelligent Syst Engn, Hitachi, Ibaraki 3168511, Japan

来源：

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING | 2018年 / 32卷 / 02期

关键词：

bias compensation; blind adaptive identification; recursive least squares; SIMO system; FIR SYSTEMS; EQUALIZATION; SUBSPACE; TRANSMISSION;

D O I：

10.1002/acs.2842

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper studies the problem of blind adaptive identification, which focuses on how to obtain the consistent estimation of channel characteristics when only the output signal of each transmission channel is available. To solve this problem, traditional algorithms usually construct a single-input-multiple-output system resorting to the technique of antenna array or time oversampling. However, they simply suppose that the noise of each channel is known a priori or balanced, which cannot always be satisfied in practice. Therefore, considering the practical situation where the noise of each transmission channel is both unknown and unbalanced, a bias-compensated recursive least-squares algorithm is proposed, which can estimate the unbalanced noises in real time and obtain the consistent estimation of channel characteristics. Simulation results illustrate the good performance of the proposed algorithm under different signal-to-noise-ratio conditions.

引用

页码：301 / 315

页数：15

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