Toward Fast Reliable Communication at Rates Near Capacity with Gaussian Noise
Information Theory
2010-06-22 v1 Machine Learning
math.IT
Statistics Theory
Statistics Theory
Abstract
For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by the choice of subset. A feasible decoding algorithm is presented. Communication is reliable with error probability exponentially small for all rates below the Shannon capacity.
Keywords
Cite
@article{arxiv.1006.3870,
title = {Toward Fast Reliable Communication at Rates Near Capacity with Gaussian Noise},
author = {Andrew R Barron and Antony Joseph},
journal= {arXiv preprint arXiv:1006.3870},
year = {2010}
}
Comments
5 pages, 4 figures, conference submission