Least Squares Superposition Codes of Moderate Dictionary Size, Reliable at Rates up to Capacity
Information Theory
2010-06-21 v1 Machine Learning
math.IT
Statistics Theory
Statistics Theory
Abstract
For the additive white Gaussian noise channel with average codeword power constraint, new coding methods are devised in which the codewords are sparse superpositions, that is, linear combinations of subsets of vectors from a given design, with the possible messages indexed by the choice of subset. Decoding is by least squares, tailored to the assumed form of linear combination. Communication is shown to be reliable with error probability exponentially small for all rates up to the Shannon capacity.
Keywords
Cite
@article{arxiv.1006.3780,
title = {Least Squares Superposition Codes of Moderate Dictionary Size, Reliable at Rates up to Capacity},
author = {Andrew R. Barron and Antony Joseph},
journal= {arXiv preprint arXiv:1006.3780},
year = {2010}
}
Comments
17 pages, 4 figures, journal submission