On center locating in RBF network equalization in the GSM system

In this paper we have studied methods for center locating in radial basis function (RBF) network equalization in the GSM (Global System for Mobile Communications) environment. Here, equalization is considered as a classification problem, where the idea is to map the received complex-valued signal into desired binary values using RBF network equalizer. Two techniques for the RBF center locating have been studied. The first one applies a nearest-neighbor type clustering procedure and the second one uses estimated channel coefficients for computing the possible center locations. These methods are studied in terms of bit error rates and computational efficiency. Performance comparisons are made to a previously studied RBF network, which considers each received training sequence vector as a center and also to a Viterbi equalizer.