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We initiate the probabilistic analysis of linear programming (LP) decoding of low-density parity-check (LDPC) codes. Specifically, we show that for a random LDPC code ensemble, the linear programming decoder of Feldman et al. succeeds in…

Information Theory · Computer Science 2016-11-15 Constantinos Daskalakis , Alexandros G. Dimakis , Richard M. Karp , Martin J. Wainwright

A new approach for decoding binary linear codes by solving a linear program (LP) over a relaxed codeword polytope was recently proposed by Feldman et al. In this paper we investigate the structure of the polytope used in the LP relaxation…

Information Theory · Computer Science 2007-07-13 Alexandros G. Dimakis , Martin J. Wainwright

This work introduces a novel, fully differentiable linear-time complexity transformer decoder and a transformer decoder to correct 5G New Radio (NR) LDPC. We propose a scalable approach to decode linear block codes with $O(n)$ complexity…

Machine Learning · Computer Science 2025-01-27 Mario Hernandez , Fernando Pinero

In Linear Programming (LP) decoding of a Low-Density-Parity-Check (LDPC) code one minimizes a linear functional, with coefficients related to log-likelihood ratios, over a relaxation of the polytope spanned by the codewords \cite{03FWK}. In…

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

Algebraic space-time coding allows for reliable data exchange across fading multiple-input multiple-output channels. A powerful technique for decoding space-time codes in Maximum-Likelihood (ML) decoding, but well-performing and widely-used…

Information Theory · Computer Science 2015-01-28 Amaro Barreal , Camilla Hollanti , David Karpuk

The advancement of deep learning has led to the development of neural decoders for low latency communications. However, neural decoders can be very complex which can lead to increased computation and latency. We consider iterative pruning…

Machine Learning · Computer Science 2022-11-17 Vikrant Malik , Rohan Ghosh , Mehul Motani

We investigate the parameterized complexity of Vertex Cover parameterized by the difference between the size of the optimal solution and the value of the linear programming (LP) relaxation of the problem. By carefully analyzing the change…

Data Structures and Algorithms · Computer Science 2012-03-14 Daniel Lokshtanov , N. S. Narayanaswamy , Venkatesh Raman , M. S. Ramanujan , Saket Saurabh

We present a new model for LT codes which simplifies the analysis of the error probability of decoding by belief propagation. For any given degree distribution, we provide the first rigorous expression for the limiting error probability as…

Information Theory · Computer Science 2007-07-13 Elitza N. Maneva , Amin Shokrollahi

Modern program verifiers use logic-based encodings of the verification problem that are discharged by a back end reasoning engine. However, instances of such encodings for large programs can quickly overwhelm these back end solvers. Hence,…

Logic in Computer Science · Computer Science 2016-07-18 Peter Schrammel

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

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder,…

Information Theory · Computer Science 2018-03-14 Eliya Nachmani , Elad Marciano , Loren Lugosch , Warren J. Gross , David Burshtein , Yair Beery

We develop a framework for linear-programming (LP) decoding of non-binary linear codes over rings. We prove that the resulting LP decoder has the `maximum likelihood certificate' property, and we show that the decoder output is the lowest…

Information Theory · Computer Science 2007-10-10 Mark F. Flanagan , Vitaly Skachek , Eimear Byrne , Marcus Greferath

The 3D MIMO code is a robust and efficient space-time block code (STBC) for the distributed MIMO broadcasting but suffers from high maximum-likelihood (ML) decoding complexity. In this paper, we first analyze some properties of the 3D MIMO…

Information Theory · Computer Science 2014-01-16 Ming Liu , Matthieu Crussière , Maryline Hélard , Jean-François Hélard

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

In this paper, a new method for decoding Low Density Parity Check (LDPC) codes, based on Multi-Layer Perceptron (MLP) neural networks is proposed. Due to the fact that in neural networks all procedures are processed in parallel, this method…

Information Theory · Computer Science 2014-11-14 Alireza Karami , Mahmoud Ahmadian Attari

A linear programming (LP) based framework is presented for obtaining converses for finite blocklength lossy joint source-channel coding problems. The framework applies for any loss criterion, generalizes certain previously known converses,…

Information Theory · Computer Science 2017-05-04 Sharu Theresa Jose , Ankur A. Kulkarni

We argue that reducing nonlinear programming problems to a simple canonical form is an effective way to analyze them, specially when the problem is degenerate and the usual linear independence hypothesis does not hold. To illustrate this…

Optimization and Control · Mathematics 2018-04-02 Walter F. Mascarenhas

The problem of finding code distance has been long studied for the generic ensembles of linear codes and led to several algorithms that substantially reduce exponential complexity of this task. However, no asymptotic complexity bounds are…

Information Theory · Computer Science 2016-11-17 Ilya Dumer , Alexey A. Kovalev , Leonid P. Pryadko

Linear computation coding is concerned with the compression of multidimensional linear functions, i.e. with reducing the computational effort of multiplying an arbitrary vector to an arbitrary, but known, constant matrix. This paper…

Information Theory · Computer Science 2025-07-02 Hans Rosenberger , Johanna S. Fröhlich , Ali Bereyhi , Ralf R. Müller

Whereas many results are known about thresholds for ensembles of low-density parity-check codes under message-passing iterative decoding, this is not the case for linear programming decoding. Towards closing this knowledge gap, this paper…

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