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A quantized message passing decoding algorithm for low-density parity-check codes is presented. The algorithm relies on the min approximation at the check nodes, and on modelling the variable node inbound messages as observations of an…

Information Theory · Computer Science 2021-01-01 Emna Ben Yacoub

Learning a hidden parity function from noisy data, known as learning parity with noise (LPN), is an example of intelligent behavior that aims to generalize a concept based on noisy examples. The solution to LPN immediately leads to decoding…

Quantum Physics · Physics 2020-09-16 Daniel K. Park , Jonghun Park , June-Koo Kevin Rhee

The performance of low-density parity-check (LDPC) codes at high signal-to-noise ratios (SNRs) is known to be limited by the presence of certain sub-graphs that exist in the Tanner graph representation of the code, for example trapping sets…

Information Theory · Computer Science 2019-11-11 Homayoon Hatami , David G. M. Mitchell , Daniel J. Costello , Thomas E. Fuja

This paper basically expresses the core fundamentals and brief overview of the research of R. G. GALLAGER [1] on Low-Density Parity-Check (LDPC) codes and various parameters related to LDPC codes like, encoding and decoding of LDPC codes,…

Information Theory · Computer Science 2020-09-21 Saumya Borwankar , Dhruv Shah

Low density parity-check (LDPC) codes are a class of linear block codes that are decoded by running belief propagation (BP) algorithm or log-likelihood ratio belief propagation (LLR-BP) over the factor graph of the code. One of the…

Information Theory · Computer Science 2011-07-15 A. Dinesh Kumar , Ambedkar Dukkipati

We present a two-step decoder for the parity code and evaluate its performance in code-capacity and faulty-measurement settings. For noiseless measurements, we find that the decoding problem can be reduced to a series of repetition codes…

We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show…

Information Theory · Computer Science 2016-11-15 Andrew L. Jones , Ioannis Chatzigeorgiou , Andrea Tassi

Forward error correcting (FEC) codes are used in many communication standards with a wide range of re quirements. FEC codes should work close to capacity, achieve low error floors, and have low decoding complexity. In this paper, we propose…

Information Theory · Computer Science 2025-05-26 Vincent Wüst , Erdem Eray Cil , Laurent Schmalen

Dense coding with non-maximally entangled states has been investigated in many different scenarios. We revisit this problem for protocols adopting the standard encoding scheme. In this case, the set of possible classical messages cannot be…

Quantum Physics · Physics 2017-03-03 Roger Alfredo Kögler , Leonardo Neves

We discuss the performance of Low-Density-Parity-Check (LDPC) codes decoded by means of Linear Programming (LP) at moderate and large Signal-to-Noise-Ratios (SNR). Utilizing a combination of the previously introduced pseudo-codeword-search…

Information Theory · Computer Science 2007-07-13 Michael Chertkov , Mikhail Stepanov

In this paper, we propose a new coded computing technique called "substitute decoding" for general iterative distributed computation tasks. In the first part of the paper, we use PageRank as a simple example to show that substitute decoding…

Information Theory · Computer Science 2018-05-17 Yaoqing Yang , Malhar Chaudhari , Pulkit Grover , Soummya Kar

Large alphabet source coding is a basic and well-studied problem in data compression. It has many applications such as compression of natural language text, speech and images. The classic perception of most commonly used methods is that a…

Information Theory · Computer Science 2016-07-26 Amichai Painsky , Saharon Rosset , Meir Feder

Belief Propagation (BP) followed by Ordered Statistics Decoding (OSD) has emerged as the gold standard for decoding quantum low-density parity-check (QLDPC) codes. Recent advancements in this field have proposed new methods and algorithms…

Information Theory · Computer Science 2026-05-26 Michele Banfi , Marco Ferrari , Antonino Favano , Alberto Tarable , Luca Barletta

An efficient decoding algorithm for horizontally u-interleaved LRPC codes is proposed and analyzed. Upper bounds on the decoding failure rate and the computational complexity of the algorithm are derived. It is shown that interleaving…

Information Theory · Computer Science 2019-08-29 Julian Renner , Thomas Jerkovits , Hannes Bartz

In order to understand the performance of a code under maximum-likelihood (ML) decoding, one studies the codewords, in particular the minimal codewords, and their Hamming weights. In the context of linear programming (LP) decoding, one's…

Information Theory · Computer Science 2007-07-13 Roxana Smarandache , Pascal O. Vontobel

This paper studies coding schemes for the $q$-ary symmetric channel based on binary low-density parity-check (LDPC) codes that work for any alphabet size $q=2^m$, $m\in\mathbb{N}$, thus complementing some recently proposed packet-based…

Information Theory · Computer Science 2015-03-13 Claudio Weidmann , Gottfried Lechner

Channel coding aims to minimize errors that occur during the transmission of digital information from one place to another. Low-density parity-check (LDPC) codes can detect and correct transmission errors if one encodes the original…

Information Theory · Computer Science 2018-03-14 Banu Kabakulak , Z. Caner Taşkın , Ali Emre Pusane

In practice, LDPC codes are decoded using message passing methods. These methods offer good performance but tend to converge slowly and sometimes fail to converge and to decode the desired codewords correctly. Recently, tree-reweighted…

Information Theory · Computer Science 2014-03-05 J. Li , R. C. de Lamare , H. Wymeersch

Quantum low-density parity-check (QLDPC) codes with asymptotically non-zero rates are prominent candidates for achieving fault-tolerant quantum computation, primarily due to their syndrome-measurement circuit's low operational depth.…

Information Theory · Computer Science 2025-04-03 Asit Kumar Pradhan , Nithin Raveendran , Narayanan Rengaswamy , Bane Vasić

Many probabilistic inference tasks involve summations over exponentially large sets. Recently, it has been shown that these problems can be reduced to solving a polynomial number of MAP inference queries for a model augmented with randomly…

Artificial Intelligence · Computer Science 2013-09-27 Stefano Ermon , Carla P. Gomes , Ashish Sabharwal , Bart Selman
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