Reduced Complexity Super-Trellis Decoding for Convolutionally Encoded   Transmission Over ISI-Channels
  In this paper we propose a matched encoding (ME) scheme for convolutionally encoded transmission over intersymbol interference (usually called ISI) channels. A novel trellis description enables to perform equalization and decoding jointly, i.e., enables efficient super-trellis decoding. By means of this matched non-linear trellis description we can significantly reduce the number of states needed for the receiver-side Viterbi algorithm to perform maximum-likelihood sequence estimation. Further complexity reduction is achieved using the concept of reduced-state sequence estimation. 
Fabian Schuh, Andreas Schenk, and Johannes B. Huber
cs.IT math.IT