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Stochastic encoders for channel coding and lossy source coding are introduced with a rate close to the fundamental limits, where the only restriction is that the channel input alphabet and the reproduction alphabet of the lossy source code…

Information Theory · Computer Science 2016-11-15 Jun Muramatsu

This paper studies channel coding for the discrete memoryless multiple-access channel with a given (possibly suboptimal) decoding rule. A multi-letter successive decoding rule depending on an arbitrary non-negative decoding metric is…

Information Theory · Computer Science 2017-12-08 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

Polar codes were introduced in 2009 and proven to achieve the symmetric capacity of any binary-input discrete memoryless channel under low-complexity successive cancellation decoding. In this thesis, we construct cyclic polar codes based on…

Information Theory · Computer Science 2020-04-16 Narayanan Rengaswamy

We establish several new results on Marton's coding scheme and its corresponding inner bound on the capacity region of the general broadcast channel. We show that unlike the Gaussian case, Marton's coding scheme without superposition coding…

Information Theory · Computer Science 2016-11-18 Amin Aminzadeh Gohari , Abbas El Gamal , Venkat Anantharam

We investigate power allocation for the base matrix of a spatially coupled sparse regression code (SC-SPARC) for reliable communications over an additive white Gaussian noise channel. A conventional SC-SPARC allocates power uniformly to the…

Information Theory · Computer Science 2023-05-16 Nian Guo , Shansuo Liang , Wei Han

We study reliable communication over finite-state channels (FSCs) using Reed--Muller (RM) codes. Building on recent symmetry-based analyses for memoryless channels, we show that a sequence of binary RM codes (with some random scrambling)…

Information Theory · Computer Science 2026-04-17 Henry D. Pfister , Navin Kashyap , Jean-Francois Chamberland , Galen Reeves

We address the problem of converting large-scale high-dimensional image data into binary codes so that approximate nearest-neighbor search over them can be efficiently performed. Different from most of the existing unsupervised approaches…

Computer Vision and Pattern Recognition · Computer Science 2015-12-02 Tsung-Yu Lin , Tsung-Wei Ke , Tyng-Luh Liu

A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity $I(W)$ of any given binary-input discrete memoryless channel (B-DMC) $W$. The symmetric capacity is the highest rate…

Information Theory · Computer Science 2016-11-18 Erdal Arikan

In this paper, we leverage polar codes and the well-established channel polarization to design capacity-achieving codes with a certain constraint on the weights of all the columns in the generator matrix (GM) while having a low-complexity…

Information Theory · Computer Science 2023-03-17 James Chin-Jen Pang , Hessam Mahdavifar , S. Sandeep Pradhan

Let $W$ be a binary-input memoryless symmetric (BMS) channel with Shannon capacity $I(W)$ and fix any $\alpha > 0$. We construct, for any sufficiently small $\delta > 0$, binary linear codes of block length $O(1/\delta^{2+\alpha})$ and rate…

Information Theory · Computer Science 2022-01-25 Venkatesan Guruswami , Andrii Riazanov , Min Ye

Noisy matrix completion has attracted significant attention due to its applications in recommendation systems, signal processing and image restoration. Most existing works rely on (weighted) least squares methods under various low-rank…

Machine Learning · Statistics 2024-12-17 Ziyuan Chen , Fang Yao

A polar coding scheme is introduced in this paper for the wire-tap channel. It is shown that the provided scheme achieves the entire rate-equivocation region for the case of symmetric and degraded wire-tap channel, where the weak notion of…

Information Theory · Computer Science 2015-03-17 Eran Hof , Shlomo Shamai

We present a constraint-coding scheme to correct asymmetric magnitude-$1$ errors in multi-level non-volatile memories. For large numbers of such errors, the scheme is shown to deliver better correction capability compared to known…

Information Theory · Computer Science 2017-09-12 Evyatar Hemo , Yuval Cassuto

Given a probability distribution $\mathcal{D}$ over the non-negative integers, a $\mathcal{D}$-repeat channel acts on an input symbol by repeating it a number of times distributed as $\mathcal{D}$. For example, the binary deletion channel…

Information Theory · Computer Science 2022-02-08 Francisco Pernice , Ray Li , Mary Wootters

Recently, the authors showed that Reed-Muller (RM) codes achieve capacity on binary memoryless symmetric (BMS) channels with respect to bit error rate. This paper extends that work by showing that RM codes defined on non-binary fields,…

Information Theory · Computer Science 2023-05-16 Galen Reeves , Henry D. Pfister

Sparse superposition (SS) codes provide an efficient communication scheme over the Gaussian channel, utilizing the vector approximate message passing (VAMP) decoder for rotational invariant design matrices. Previous work has established…

Information Theory · Computer Science 2025-04-21 Yuhao Liu , Teng Fu , Jie Fan , Panpan Niu , Chaowen Deng , Zhongyi Huang

We describe some pseudorandom properties of binary linear codes achieving capacity on the binary erasure channel under bit-MAP decoding (as shown in Kudekar et al this includes doubly transitive codes and, in particular, Reed-Muller codes).…

Information Theory · Computer Science 2022-06-13 Alex Samorodnitsky

The problem of channel coding with the erasure option is revisited for discrete memoryless channels. The interplay between the code rate, the undetected and total error probabilities is characterized. Using the information spectrum method,…

Information Theory · Computer Science 2015-10-22 Masahito Hayashi , Vincent Y. F. Tan

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

We present an analysis, under iterative decoding, of coset LDPC codes over GF(q), designed for use over arbitrary discrete-memoryless channels (particularly nonbinary and asymmetric channels). We use a random-coset analysis to produce an…

Information Theory · Computer Science 2007-07-16 Amir Bennatan , David Burshtein