Decision Feedback Equalizers Using Radial Basis Function Networks

Abstract

Decision feedback equalizers (DFE)s are used extensively in practical communication systems. They are more powerful than linear equalizers especially for severe inter-symbol interference (ISI) channels with deep frequency null. In this paper, radial basis function (RBF) network is used to implement DFE. Advantages and problems of this system are discussed and its results are then compared with DFE using multilayer perception net (MLP). Results indicate that the implemented system outperforms both the least-mean square (LMS) algorithm and MLP given the same signal-to-noise ratio. Keywords: Nonlinear equalization, neural networks, radial basis function, decision feedback equalizers, ISI channels