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Reduced Complexity Super-Trellis Decoding for Convolutionally Encoded Transmission Over ISI-Channels

2012/07/19 by Fabian Schuh, Schuh, Fabian, Andreas Schenk +3
Computer Science · Mathematics · #FOS: Computer and information sciences #Information Theory (cs.IT) #cs.IT #math.IT

paper · pdf · doi:10.48550/arxiv.1207.4680

6 pages, 8 figures, accepted for ICNC'13. (see also: arXiv:1205.7031)

arxiv created 2012/10/04 · arxiv updated 2012/10/05

Abstract

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.

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