Sparse Superposition Codes with Binomial Dictionary are Capacity-Achieving with Maximum Likelihood Decoding

It is known that sparse superposition codes asymptotically achieve the channel capacity over the additive white Gaussian noise channel with both maximum likelihood decoding and efficient decoding (Joseph and Barron in 2012, 2014). Takeishi et al. (in 2014, 2019) demonstrated that these codes can also asymptotically achieve the channel capacity with maximum likelihood decoding when the dictionary is drawn from a Bernoulli distribution. In this paper, we extend these results by showing that the dictionary distribution can be naturally generalized to the binomial distribution.

Publication Details

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ArXiv.org
Published
2025-04-19
Primary Topic
Error Correcting Code Techniques
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article
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article

Sparse Superposition Codes with Binomial Dictionary are Capacity-Achieving with Maximum Likelihood Decoding

ArXiv.org
Error Correcting Code Techniques
article

Sparse Superposition Codes with Binomial Dictionary are Capacity-Achieving with Maximum Likelihood Decoding

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Abstract

It is known that sparse superposition codes asymptotically achieve the channel capacity over the additive white Gaussian noise channel with both maximum likelihood decoding and efficient decoding (Joseph and Barron in 2012, 2014). Takeishi et al. (in 2014, 2019) demonstrated that these codes can also asymptotically achieve the channel capacity with maximum likelihood decoding when the dictionary is drawn from a Bernoulli distribution. In this paper, we extend these results by showing that the dictionary distribution can be naturally generalized to the binomial distribution.

ArXiv.org
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Error Correcting Code Techniques
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Sparse Superposition Codes with Binomial Dictionary are Capacity-Achieving with Maximum Likelihood Decoding · ArXiv.org (2025) | TGRS Research Map | TGRS