Vector neural networks for digital satellite communications

Abstract

Conventional techniques used for identification and equalization of nonlinear M-ary PSK digital satellite channels are based on linear or nonlinear filtering devices (e.g. tapped delay line equalizers, Volterra series approaches). This paper uses a new technique based on the vector neural network (VNN) and Kohonen (1989) self organizing feature map. We have used a VNN for adaptive equalization and identification of the satellite channel. The decision process is performed by a Kohonen map.