A novel cluster based MLSE equalizer for 2-PAM signaling scheme

In this paper a new cluster based Maximum Likelihood Sequence Equalizer is presented. The novelty of the algorithm consists of a novel technique for the estimation of all the centers around which the received observations are clustered. For a channel of order L and a 2-PAM signaling scheme, only L of the cluster centers need to be estimated, and the rest 2^L - L clusters are subsequently obtained via simple operations. This has a two fold advantage compared to previously proposed cluster based algorithms. It reduces dramatically the computational complexity as well as the required length of the training sequence. The method is compared with the standard LMS based MLSE and the Bayesian RBF equalizer. The results are very favorable for the new technique, both from a computational as well as performance point of view.