Fast Sparse Superposition Codes have Exponentially Small Error Probability for R < C

Antony Joseph; Andrew Barron

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arXiv · 1207.2406

Fast Sparse Superposition Codes have Exponentially Small Error Probability for R < C

Antony Joseph·Andrew Barron

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Abstract

For the additive white Gaussian noise channel with average codeword power constraint, sparse superposition codes are developed. These codes are based on the statistical high-dimensional regression framework. The paper [IEEE Trans. Inform. Theory 55 (2012), 2541 - 2557] investigated decoding using the optimal maximum-likelihood decoding scheme. Here a fast decoding algorithm, called adaptive successive decoder, is developed. For any rate R less than the capacity C communication is shown to be reliable with exponentially small error probability.

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Antony Joseph, Andrew Barron. 2012-07-10. Fast Sparse Superposition Codes have Exponentially Small Error Probability for R < C. https://arxiv.org/abs/1207.2406

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