CRIMNO: criterion with memory nonlinearity for blind equalization

Author

Chen, Yuanjie ; Nikias, Chrysostomos L. ; Proakis, John G.

Author_Institution

Dept. of EE-Syst., Univ. of Southern California, Los Angeles, CA, USA

fYear

1991

fDate

4-6 Nov 1991

Firstpage

694

Lastpage

698

Abstract

A novel criterion with memory nonlinearity (CRIMNO) is introduced for blind equalization problems. The basic idea of CRIMNO is to make use of the fact that the transmitted data are statistically independent of each other. It is shown that CRIMNO may not have local minima if its weights are chosen properly, thereby guaranteeing global convergence. An adaptive weight CRIMNO algorithm is also presented and tested with simulation examples of quadrature amplitude modulation (QAM) signals. It is shown that the adaptive weight CRIMNO algorithm exhibits faster convergence speed than the Godard (1980) algorithm without any significant increase in computational complexity

Keywords

amplitude modulation; signal processing; CRIMNO; QAM; adaptive weight algorithm; blind equalization; computational complexity; convergence speed; global convergence; memory nonlinearity; quadrature amplitude modulation; simulation; statistically independent data; Blind equalizers; Convergence; Cost function; Data communication; Decision feedback equalizers; Fading; Interference; Phase distortion; Quadrature amplitude modulation; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-2470-1

Type

conf

DOI

10.1109/ACSSC.1991.186537

Filename

186537