Abstract
Application of artificial neural network (ANN) structures to the problem of channel equalization in a digital communication system has been considered in this paper. The difficulties associated with channel nonlinearities can be overcome by equalizers employing ANN. Because of nonlinear processing of signals in an ANN, it is capable of producing arbitrarily complex decision regions. For this reason, the ANN has been utilized for the channel equalization problem. A scheme based on a functional link ANN (FLANN) has been proposed for this task. The performance of the proposed network along with two other ANN structures has been compared with the conventional LMS based channel equalizer. Effect of eigenvalue ratio of the input correlation matrix on the performance of the equalizers has been studied. From the simulation results, it is observed that the performance of the proposed FLANN based equalizer outperforms the other two in terms of bit-error rate (BER) and attainable MSB level over a wide range of eigenvalue spread, signal to noise ratio and channel nonlinearities.
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