A family of predictive constant modulus algorithms for blind equalization

Author

Barbosa, L.M.J. ; Mota, J.C.M. ; Cavalcanti, F.R.P.

Author_Institution

Fed. Univ. of Ceara, Fortaleza, Brazil

fYear

2000

fDate

2000

Firstpage

260

Lastpage

265

Abstract

In this work we present a family of predictive constant modulus algorithms that performs blind equalization with some advantages over the CMA/FIR conventional technique. The LMS-like algorithm of the family (PCMA) was originally presented by Cavalcanti and Mota (1997). In this paper we present two new algorithms based in the same approach: the normalized PCMA (NPCMA) and the recursive PCMA (RPCMA). The choice of one of these algorithms depends on a compromise between performance and complexity, as usual. Simulation results confirm that PCMA-based algorithms perform better than conventional FIR equalizers in terms of steady-state error. Moreover, the proposed NPCMA and RPCMA provides increased convergence speed when compared to the original PCMA

Keywords

adaptive equalisers; adaptive filters; autoregressive moving average processes; blind equalisers; convergence of numerical methods; least mean squares methods; prediction theory; recursive filters; LMS-like algorithm; blind equalization; complexity; convergence speed; filters; normalized PCMA; performance; predictive constant modulus algorithms; recursive PCMA; simulation; steady-state error; Adaptive algorithm; Adaptive filters; Blind equalizers; Convergence; Finite impulse response filter; IIR filters; Prediction algorithms; Stability; Steady-state; Transversal filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000. AS-SPCC. The IEEE 2000

Conference_Location

Lake Louise, Alta.

Print_ISBN

0-7803-5800-7

Type

conf

DOI

10.1109/ASSPCC.2000.882482

Filename

882482