Channel Metrization
Information Theory
2016-02-26 v2 Combinatorics
math.IT
Abstract
We present an algorithm that, given a channel, determines if there is a distance for it such that the maximum likelihood decoder coincides with the minimum distance decoder. We also show that any metric, up to a decoding equivalence, can be isometrically embedded into the hypercube with the Hamming metric, and thus, in terms of decoding, the Hamming metric is universal.
Cite
@article{arxiv.1510.03104,
title = {Channel Metrization},
author = {Rafael G. L. D'Oliveira and Marcelo Firer},
journal= {arXiv preprint arXiv:1510.03104},
year = {2016}
}
Comments
17 pages, 3 figures, presented shorter version at WCC 2015