Adaptive error constrained LMS algorithms and its blind equalization method

Author

Choi, Sooyong ; Ko, Kyunbyoung ; Hong, Daesik

Author_Institution

Dept. of Electr. & Electron. Eng., Yonsei Univ., Seoul, South Korea

Volume

6

fYear

2001

fDate

2001

Firstpage

3331

Abstract

In this paper, the adaptive error constrained least mean square (AECLMS) algorithm is proposed through the extension and generalization of the noise constrained LMS (NCLMS) algorithm and its performance analysis is presented. By using a constrained optimization technique, the assumption that the noise variance is known is eliminated. Therefore, the proposed constrained optimization method can be easily applied to blind equalization methods. The proposed constrained method is also applied to the constant modulus criterion. The proposed method can accelerates the convergence speed of the conventional steepest descent-type training procedure by several times

Keywords

adaptive equalisers; blind equalisers; convergence of numerical methods; least mean squares methods; optimisation; AECLMS algorithm; NCLMS algorithm; adaptive error constrained least mean square algorithm; blind equalization; constant modulus criterion; constrained optimization; convergence speed; descent-type training procedure; noise constrained LMS algorithm; performance analysis; Blind equalizers; Convergence; Cost function; Finite impulse response filter; Least squares approximation; Optimization methods; Performance analysis; Signal processing algorithms; Signal to noise ratio; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-7206-9

Type

conf

DOI

10.1109/GLOCOM.2001.966303

Filename

966303