A gradient-based optimum block adaptation ICA technique for interference suppression in highly dynamic communication channels

Abstract

The fast fixed-point independent component analysis (ICA) algorithm has been widely used in various applications because of its fast convergence and superior performance. However, in a highly dynamic environment, real-time adaptation is necessary to track the variations of the mixing matrix. In this scenario, the gradient-based online learning algorithm performs better, but its convergence is slow, and depends on a proper choice of convergence factor. This paper develops a gradient-based optimum block adaptive ICA algorithm(OBA/ICA) that combines the advantages of the two algorithms.Simulation results for telecommunication applications indicate that the resulting performance is superior under time-varying conditions, which is particularly useful in mobile communications. Copyright © 2006 Hindawi Publishing Corporation. All right reserved.