Blind equalization using RBF and HOS

Abstract

This paper discusses a blind equalization technique for FIR channel system, that might be minimum phase or not, in digital communication. The proposed techniques consist of two parts. One is to estimate the original channel coefficients based on fourth-order cumulants of the channel output, the other is to employ RBF neural network to model an inverse system for the original channel. Here, the estimated channel is used as a reference system to train the RBF neural network. The proposed RBF equalizer provides fast and easy learning, due to the structural efficiency and excellent recognition-capability of RBF neural network. Throughout the simulation studies, it was found that the proposed blind RBF equalizer performed favorably better than the blind MLP equalizer, while requiring the relatively smaller computation steps in training. © Springer-Verlag 2003.