Prefiltering and Trellis-Based Equalization for Sparse ISI Channels

Sparse intersymbol-interference (ISI) channels are encountered in a variety of high-data-rate communication systems. Such channels have a large channel memory length, but only a small number of significant channel coefficients. In this paper, trellis-based equalization of sparse ISI channels is revisited. Due to the large channel memory length, the complexity of maximumlikelihood detection, e.g., by means of the Viterbi algorithm, is normally prohibitive, and efficient equalization with an acceptable complexity-performance trade-off is a demanding task. We investigate a unified approach to tackle general sparse ISI channels: It is shown that the use of a linear filter at the receiver renders the application of standard reduced-state trellis-based equalizer algorithms feasible, without significant loss of optimality. Numerical results verify the efficiency of the proposed receiver structure.