Dynamic quantization for maximum likelihood sequence detection of PAM signaling

Maximum likelihood sequence detection (MLSD) provides optimum detection for intersymbol interference (ISI) channels subject to additive white Gaussian noise (AWGN). This decoding process dynamically searches the most likely path through the intersymbol interference (ISI) channel trellis, using the Viterbi algorithm (VA). In this paper, we exploit the structure of this trellis and, for an M-point pulse amplitude modulation (PAM) constellation, present a new scheme based on dynamic quantization. This scheme becomes extremely efficient for the single memory unit channel 1+f/sub 1/D, as it achieves optimum MLSD with O(M) computations per decoding step, instead of O(M/sup 2/) for the VA. Generalization to any finite length channel is also possible and conserves good computational efficiency.