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Related papers: Coding for Parallel Channels: Gallager Bounds for …

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This work identifies information-theoretic quantities that are closely related to the required list size on average for successive cancellation list (SCL) decoding to implement maximum-likelihood decoding over general binary memoryless…

Information Theory · Computer Science 2022-04-04 Mustafa Cemil Coşkun , Henry D. Pfister

This paper studies the third-order characteristic of nonsingular discrete memoryless channels and the Gaussian channel with a maximal-power constraint. The third-order term in our expansions employs a new quantity here called the channel…

Information Theory · Computer Science 2024-08-23 Recep Can Yavas , Victoria Kostina , Michelle Effros

Over binary input channels, uniform distribution is a universal prior, in the sense that it allows to maximize the worst case mutual information over all binary input channels, ensuring at least 94.2% of the capacity. In this paper, we…

Information Theory · Computer Science 2010-04-28 Emmanuel Abbe , Rethnakaran Pulikkoonattu

We consider the problem of coded distributed computing where a large linear computational job, such as a matrix multiplication, is divided into $k$ smaller tasks, encoded using an $(n,k)$ linear code, and performed over $n$ distributed…

Information Theory · Computer Science 2021-10-06 Mahdi Soleymani , Mohammad Vahid Jamali , Hessam Mahdavifar

This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with…

Information Theory · Computer Science 2016-11-18 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

We present an approach to showing that a linear code is resilient to random errors. We use this approach to obtain decoding results for both transitive codes and Reed-Muller codes. We give three kinds of results about linear codes in…

Information Theory · Computer Science 2025-02-27 Anup Rao , Oscar Sprumont

We introduce Noise Recycling, a method that substantially enhances decoding performance of orthogonal channels subject to correlated noise without the need for joint encoding or decoding. The method can be used with any combination of…

Information Theory · Computer Science 2020-06-11 Alejandro Cohen , Amit Solomon , Ken R. Duffy , Muriel Médard

New non-asymptotic random coding theorems (with error probability $\epsilon$ and finite block length $n$) based on Gallager parity check ensemble and Shannon random code ensemble with a fixed codeword type are established for discrete input…

Information Theory · Computer Science 2013-03-05 En-hui Yang , Jin Meng

We consider network coding for networks experiencing worst-case bit-flip errors, and argue that this is a reasonable model for highly dynamic wireless network transmissions. We demonstrate that in this setup prior network error-correcting…

Information Theory · Computer Science 2011-08-16 Qiwen Wang , Sidharth Jaggi , Shuo-Yen Robert Li

Batched sparse (BATS) codes were proposed as a reliable communication solution for networks with packet loss. In the finite-length regime, the error probability of BATS codes under belief propagation (BP) decoding has been studied in the…

Information Theory · Computer Science 2025-02-12 Mingyang Zhu , Shenghao Yang , Ming Jiang , Chunming Zhao

For a given family of spatially coupled codes, we prove that the LP threshold on the BSC of the graph cover ensemble is the same as the LP threshold on the BSC of the derived spatially coupled ensemble. This result is in contrast with the…

Information Theory · Computer Science 2013-03-06 Louay Bazzi , Badih Ghazi , Rudiger Urbanke

This paper presents finite-blocklength achievability bounds for the Gaussian multiple access channel (MAC) and random access channel (RAC) under average-error and maximal-power constraints. Using random codewords uniformly distributed on a…

Information Theory · Computer Science 2022-05-05 Recep Can Yavas , Victoria Kostina , Michelle Effros

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

Using combinatorial arguments, we determine an upper bound on achievable rates of stabilizer codes used over the quantum erasure channel. This allows us to recover the no-cloning bound on the capacity of the quantum erasure channel, R is…

Quantum Physics · Physics 2016-11-29 Nicolas Delfosse , Gilles Zémor

In this paper, we revisit the Recursive Projection-Aggregation (RPA) decoder, of Ye and Abbe (2020), for Reed-Muller (RM) codes. Our main contribution is an explicit upper bound on the probability of incorrect decoding, using the RPA…

Information Theory · Computer Science 2025-05-27 V. Arvind Rameshwar , V. Lalitha

This paper studies the coherent and non-coherent multiuser multiple-input multiple-output (MU-MIMO) uplink system in the finite blocklength regime. The i.i.d. Gaussian codebook is assumed for each user. To be more specific, the BS first…

Information Theory · Computer Science 2022-10-04 Junjuan Feng , Hien Quoc Ngo , Michail Matthaiou

This paper studies expurgated random-coding bounds and exponents for channel coding with a given (possibly suboptimal) decoding rule. Variations of Gallager's analysis are presented, yielding several asymptotic and non-asymptotic bounds on…

Information Theory · Computer Science 2016-11-17 Jonathan Scarlett , Li Peng , Neri Merhav , Alfonso Martinez , Albert Guillén i Fàbregas

This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation…

Information Theory · Computer Science 2023-05-17 Ioannis Papoutsidakis , Angela Doufexi , Robert J. Piechocki

Iterative decoders used for decoding low-density parity-check (LDPC) and moderate-density parity-check (MDPC) codes are not characterized by a deterministic decoding radius and their error rate performance is usually assessed through…

Information Theory · Computer Science 2020-02-27 Paolo Santini , Massimo Battaglioni , Marco Baldi , Franco Chiaraluce
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