EURASIP Journal on Applied Signal Processing 
Volume 2003 (2003), Issue 8, Pages 740-747
doi:10.1155/S1110865703303014

Blind Search for Optimal Wiener Equalizers Using an Artificial Immune Network Model

Romis Ribeiro de Faissol Attux,1 Murilo Bellezoni Loiola,1 Ricardo Suyama,1 Leandro Nunes de Castro,2 Fernando José Von Zuben,2 and João Marcos Travassos Romano1

 1DSPCOM, DECOM, FEEC, State University of Campinas, C.P. 6101, Campinas Cep 13083-970, SP, Brazil
2DCA, FEEC, State University of Campinas, C.P. 6101, Campinas Cep 13083-970, SP, Brazil
Received 28 June 2002; Revised 1 December 2002

Abstract

This work proposes a framework to determine the optimal Wiener equalizer by using an artificial immune network model together with the constant modulus (CM) cost function. This study was primarily motivated by recent theoretical results concerning the CM criterion and its relation to the Wiener approach. The proposed immune-based technique was tested under different channel models and filter orders, and benchmarked against a procedure using a genetic algorithm with niching. The results demonstrated that the proposed strategy has a clear superiority when compared with the more traditional technique. The proposed algorithm presents interesting features from the perspective of multimodal search, being capable of determining the optimal Wiener equalizer in most runs for all tested channels.