DocumentCode :
2607417
Title :
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
Link To Document :
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