Channel Equalization Using Adaptive Filtering with Averaging

The recent digital transmission systems impose the application of channel equalizers with short training time and high tracking rate. These requirements turn our attention to adaptive algorithms, which converge rapidly. From this point of view the best choice is the recursive least squares (RLS) equalizer. Unfortunately this equalizer has high computational complexity and stability problems. Therefore it is worth investigating a good alternative of the classic RLS equalizer. In this contribution we present such a channel equalizer based on adaptive filtering with averaging (AFA). The main advantages of AFA equalizer could be summarized as follows. It has high convergence rate comparable to that of the RLS equalizer and at the same time low computational complexity and possible robustness in fixed-point implementations.