Maximum-likelihood Soft-decision Decoding for Binary Linear Block Codes Based on Their Supercodes
Abstract
Based on the notion of supercodes, we propose a two-phase maximum-likelihood soft-decision decoding (tpMLSD) algorithm for binary linear block codes in this work. The first phase applies the Viterbi algorithm backwardly to a trellis derived from the parity-check matrix of the supercode of the linear block code. Using the information retained from the first phase, the second phase employs the priority-first search algorithm to the trellis corresponding to the linear block code itself, which guarantees finding the ML decision. Simulations on Reed-Muller codes show that the proposed two-phase scheme is an order of magnitude more efficient in average decoding complexity than the recursive maximum-likelihood decoding (RMLD) [1] when the signal-to-noise ratio per information bit is 4.5 dB.
Cite
@article{arxiv.1408.1310,
title = {Maximum-likelihood Soft-decision Decoding for Binary Linear Block Codes Based on Their Supercodes},
author = {Yunghsiang S. Han and Hung-Ta Pai and Po-Ning Chen and Ting-Yi Wu},
journal= {arXiv preprint arXiv:1408.1310},
year = {2014}
}
Comments
5 pages, 1 table