Communications equalization using non-linear adaptive networks

The author describes how the equalization process may be viewed as a classification problem and describes how an optimum nonlinear classification strategy is formed. One solution to this classification problem is provided which allows classification on a symbol by symbol basis with an improved bit error rate performance relative to the linear system. A nonlinear structure can provide a near optimum decision boundary but one which still does not approach the performance of maximum-likelihood sequence estimation (MLSE). The various performance and complexity issues raised in the deployment of such nonlinear adaptive systems are examined. The development of a multichannel adaptive solution in this single channel temporal case provides a possible parallel to the MLSE solution.<
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