Efficient block implementation of the decision feedback equalizer

Kostas Berberidis, Athanasios A. Rontogiannis, Sergios Theodoridis

Abstract: A new block adaptive decision feedback equalizer is developed. Both the feedforward (FF) and the feedback (FB) filters are updated once every K sample time intervals, with K being the block length. It should be noted that this block adaptation is done in such a way that the resulting filters, and the decisions as well, are identical to those computed by the conventional sample by sample LMS-based decision feedback equalizer (LMS-DFE). The new algorithm offers substantial computational savings as compared to the sample-by-sample LMS-DFE with no loss in performance. The new block DFE turns out to be particularly suitable for applications requiring long equalizers.