Generalized Optimal Step-Size for Blind Multichannel LMS System Identification

Author

Gaubitch, Nikolay D. ; Hasan, Md Kamrul ; Naylor, Patrick A.

Author_Institution

Dept. of Electr. & Electron. Eng., Imperial Coll.

Volume

13

Issue

10

fYear

2006

Firstpage

624

Lastpage

627

Abstract

The choice of step-size in adaptive blind channel identification using the multichannel least mean squares (MCLMS) algorithm is critical and controls its convergence rate, stability, and sensitivity to noise. In this letter, we derive the expression for an optimal step-size in the Wiener sense and investigate its properties. An implementation technique for the Wiener solution of the self-adaptive step-size is presented, and it is shown that significant performance improvements are obtained compared to existing approaches in the presence of noise

Keywords

Wiener filters; adaptive filters; blind equalisers; channel estimation; convergence of numerical methods; least mean squares methods; MCLMS algorithm; Wiener solution; adaptive blind channel identification; convergence rate; generalized optimal step-size; multichannel least mean square system; sensitivity; stability; Adaptive control; Blind equalizers; Deconvolution; Least squares approximation; Programmable control; Sensor arrays; Sensor systems; Speech; System identification; Working environment noise; Blind channel identification (BCI); Wiener step-size; multichannel least mean square (MCLMS) algorithm;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2006.876341

Filename

1703543