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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,…

Information Theory · Computer Science 2010-06-21 Andrew R. Barron , Antony Joseph

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.…

Information Theory · Computer Science 2012-07-11 Antony Joseph , Andrew Barron

We study the approximate message-passing decoder for sparse superposition coding on the additive white Gaussian noise channel and extend our preliminary work [1]. We use heuristic statistical-physics-based tools such as the cavity and the…

Information Theory · Computer Science 2017-07-17 Jean Barbier , Florent Krzakala

This paper presents a new class of sparse superposition codes for low-rates and short-packet communications over the additive white Gaussian noise channel. The new code is orthogonal sparse superposition (OSS) code. A codeword of OSS codes…

Information Theory · Computer Science 2020-11-24 Yunseo Nam , Jeonghun Park , Songnam Hong , Namyoon Lee

Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the AWGN channel at rates approaching the channel capacity. The codebook is defined in terms of a Gaussian design matrix, and codewords…

Information Theory · Computer Science 2017-03-14 Cynthia Rush , Adam Greig , Ramji Venkataramanan

We consider the additive white Gaussian noise channels. We prove that the error probability of decoding tends to one exponentially for rates above the capacity and derive the optimal exponent function. We shall demonstrate that the…

Information Theory · Computer Science 2017-02-07 Yasutada Oohama

Consider a pair of terminals connected by two independent additive white Gaussian noise channels, and limited by individual power constraints. The first terminal would like to reliably send information to the second terminal, within a given…

Information Theory · Computer Science 2014-12-16 Assaf Ben-Yishai , Ofer Shayevitz

We study a new class of codes for Gaussian multi-terminal source and channel coding. These codes are designed using the statistical framework of high-dimensional linear regression and are called Sparse Superposition or Sparse Regression…

Information Theory · Computer Science 2012-12-11 Ramji Venkataramanan , Sekhar Tatikonda

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

Sparse regression codes (SPARCs) are a promising coding scheme that can approach the Shannon limit over Additive White Gaussian Noise (AWGN) channels. Previous works have proven the capacity-achieving property of SPARCs with Gaussian design…

Information Theory · Computer Science 2023-03-16 Yizhou Xu , YuHao Liu , ShanSuo Liang , Tingyi Wu , Bo Bai , Jean Barbier , TianQi Hou

This paper considers the achievability and converse bounds on the maximal channel coding rate at a given blocklength and error probability over AWGN channels. The problem stems from covert communication with Gaussian codewords. By…

Information Theory · Computer Science 2021-01-01 Xinchun Yu , Shuangqin Wei , Yuan Luo

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…

Information Theory · Computer Science 2025-04-22 Yoshinari Takeishi , Jun'ichi Takeuchi

We recently proved threshold saturation for spatially coupled sparse superposition codes on the additive white Gaussian noise channel. Here we generalize our analysis to a much broader setting. We show for any memoryless channel that…

Information Theory · Computer Science 2016-03-16 Jean Barbier , Mohamad Dia , Nicolas Macris

The generalization of Shannon's theory to include messages with given autocorrelations is presented. The analytical calculation of the channel capacity is based on the transfer matrix method of the effective 1D Hamiltonian. This bridge…

Statistical Mechanics · Physics 2007-05-23 Ido Kanter , Hanan Rosemarin

Superposition codes are efficient for the Additive White Gaussian Noise channel. We provide here a replica analysis of the performances of these codes for large signals. We also consider a Bayesian Approximate Message Passing decoder based…

Information Theory · Computer Science 2014-10-03 Jean Barbier , Florent Krzakala

An additive noise channel is considered, in which the distribution of the noise is nonparametric and unknown. The problem of learning encoders and decoders based on noise samples is considered. For uncoded communication systems, the problem…

Information Theory · Computer Science 2021-11-17 Nir Weinberger

In this paper, we investigate the additive Gaussian noise channel with noisy feedback. We consider the setup of linear coding of the feedback information and Gaussian signaling of the message (i.e. Cover-Pombra Scheme). Then, we derive the…

Information Theory · Computer Science 2015-03-19 Chong Li , Nicola Elia

Developing computationally-efficient codes that approach the Shannon-theoretic limits for communication and compression has long been one of the major goals of information and coding theory. There have been significant advances towards this…

Information Theory · Computer Science 2019-11-05 Ramji Venkataramanan , Sekhar Tatikonda , Andrew Barron

The L-user additive white Gaussian noise multi-way relay channel is considered, where multiple users exchange information through a single relay at a common rate. Existing coding strategies, i.e., complete-decode-forward and…

Information Theory · Computer Science 2015-03-14 Lawrence Ong , Christopher M. Kellett , Sarah J. Johnson

The efficacy of a specially constructed Gallager-type error-correcting code to communication in a Gaussian channel is being examined. The construction is based on the introduction of complex matrices, used in both encoding and decoding,…

Disordered Systems and Neural Networks · Physics 2009-10-31 Ido Kanter , David Saad
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