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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.

preprint2012arXivOpen access
Fabian SchuhAndreas SchenkJohannes B. Huber
math.ITInformation Theory
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Fabian SchuhAndreas SchenkJohannes B. Huber

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