Matched Decoding for Punctured Convolutional Encoded Transmission Over ISI-Channels

Abstract

Matched decoding is a technique that enables the efficient maximum-likelihood sequence estimation of convolutionally encoded PAM-transmission over ISI-channels. Recently, we have shown that the super-trellis of encoder and channel can be described with significantly fewer states without loss in Euclidean distance, by introducing a non-linear representation of the trellis. This paper extends the matched decoding concept to punctured convolutional codes and introduces a time-variant, non-linear trellis description.