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Consider a binary linear code of length $N$, minimum distance $d_{\text{min}}$, transmission over the binary erasure channel with parameter $0 < \epsilon < 1$ or the binary symmetric channel with parameter $0 < \epsilon < \frac12$, and…

Information Theory · Computer Science 2018-01-30 Hamed Hassani , Shrinivas Kudekar , Or Ordentlich , Yury Polyanskiy , Rüdiger Urbanke

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

Motivated by recommendation systems, we consider the problem of estimating block constant binary matrices (of size $m \times n$) from sparse and noisy observations. The observations are obtained from the underlying block constant matrix…

Information Theory · Computer Science 2009-01-14 S. T. Aditya , Onkar Dabeer , Bikash Kumar Dey

Recent developments have shown the existence of quantum low-density parity check (qLDPC) codes with constant rate and linear distance. A natural question concerns the efficient decodability of these codes. In this paper, we present a linear…

Quantum Physics · Physics 2022-06-15 Shouzhen Gu , Christopher A. Pattison , Eugene Tang

Designing high-performance error-correcting codes at short blocklengths is critical for low-latency communication systems, where decoding is governed by finite-length and graph-structural effects rather than asymptotic properties. This…

Information Theory · Computer Science 2026-04-10 Atharv Kanchi

Low complexity error correction code is a key enabler for next generation ultra-reliable low-latency communications (xURLLC) in six generation (6G). Against this background, this paper proposes a decoding scheme for linear block code by…

Signal Processing · Electrical Eng. & Systems 2025-12-11 Di Zhang , Yinglei Yang , Zilong Liu , Shaobo Jia , Kyungchun Lee , Zhirong Zhang

Performance evaluation of particular channel coding has been a significant topic in coding theory, often involving the use of bounding techniques. This paper focuses on the new family of capacity-achieving codes, Spinal codes, to provide a…

Information Theory · Computer Science 2025-10-14 Aimin Li , Xiaomeng Chen , Shaohua Wu , Gary C. F. Lee , Sumei Sun

Polar codes asymptotically achieve the symmetric capacity of memoryless channels, yet their error-correcting performance under successive-cancellation (SC) decoding for short and moderate length codes is worse than that of other modern…

Information Theory · Computer Science 2015-12-25 Gabi Sarkis , Pascal Giard , Alexander Vardy , Claude Thibeault , Warren J. Gross

In his thesis, Wiberg showed the existence of thresholds for families of regular low-density parity-check codes under min-sum algorithm decoding. He also derived analytic bounds on these thresholds. In this paper, we formulate similar…

Information Theory · Computer Science 2007-07-16 Ralf Koetter , Pascal O. Vontobel

In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such…

Information Theory · Computer Science 2013-04-11 Walid Abediseid , Mohamed-Slim Alouini

The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

Binary quantization represents the most extreme form of compression, reducing weights to +/-1 for maximal memory and computational efficiency. While recent sparsity-aware binarization achieves sub-1-bit compression via weight pruning, it…

Machine Learning · Computer Science 2026-04-10 Hao Gu , Lujun Li , Hao Wang , Lei Wang , Zheyu Wang , Bei Liu , Jiacheng Liu , Qiyuan Zhu , Sirui Han , Yike Guo

We study relationships between worst-case and random-noise properties of error correcting codes. More concretely, we consider connections between minimum distance, list decoding radius, and block error probability on noisy channels. A…

Information Theory · Computer Science 2026-04-06 Donald Kougang-Yombi , Jan Hązła

We formulate maximum likelihood (ML) channel decoding as a quadratic unconstraint binary optimization (QUBO) and simulate the decoding by the current commercial quantum annealing machine, D-Wave 2000Q. We prepared two implementations with…

Information Theory · Computer Science 2020-10-06 Naoki Ide , Tetsuya Asayama , Hiroshi Ueno , Masayuki Ohzeki

We provide a general framework for bounding the block error threshold of a linear code $C\subseteq \mathbb{F}_2^N$ over the erasure channel in terms of its bit error threshold. Our approach relies on understanding the minimum support weight…

Information Theory · Computer Science 2025-02-27 Henry D. Pfister , Oscar Sprumont , Gilles Zémor

In this paper, we present improved decoding algorithms for expander-based Tanner codes. We begin by developing a randomized linear-time decoding algorithm that, under the condition that $ \delta d_0 > 2 $, corrects up to $ \alpha n $ errors…

Information Theory · Computer Science 2025-04-29 Zhaienhe Zhou , Zeyu Guo

Linear Programming (LP) decoding of Low-Density Parity-Check (LDPC) codes has attracted much attention in the research community in the past few years. LP decoding has been derived for binary and nonbinary linear codes. However, the most…

Information Theory · Computer Science 2016-11-17 Mayur Punekar , Pascal O. Vontobel , Mark F. Flanagan

We prove that, for the binary erasure channel (BEC), the polar-coding paradigm gives rise to codes that not only approach the Shannon limit but do so under the best possible scaling of their block length as a~function of the gap to…

Information Theory · Computer Science 2020-10-15 Arman Fazeli , S. Hamed Hassani , Marco Mondelli , Alexander Vardy

In this paper, we propose a new method for calculating the output layer in neural machine translation systems. The method is based on predicting a binary code for each word and can reduce computation time/memory requirements of the output…

Computation and Language · Computer Science 2017-04-25 Yusuke Oda , Philip Arthur , Graham Neubig , Koichiro Yoshino , Satoshi Nakamura

Guruswami and Indyk showed in [1] that Forney's error exponent can be achieved with linear coding complexity over binary symmetric channels. This paper extends this conclusion to general discrete-time memoryless channels and shows that…

Information Theory · Computer Science 2016-11-17 Zheng Wang , Jie Luo
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