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Related papers: Systematic Bernoulli Generator Matrix Codes

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We propose in this paper to exploit convolutional low density generator matrix (LDGM) codes for transmission of Bernoulli sources over binary-input output-symmetric (BIOS) channels. To this end, we present a new framework to prove the…

Information Theory · Computer Science 2022-06-07 Yixin Wang , Tingting Zhu , Xiao Ma

In this paper, we propose a systematic low density generator matrix (LDGM) code ensemble, which is defined by the Bernoulli process. We prove that, under maximum likelihood (ML) decoding, the proposed ensemble can achieve the capacity of…

Information Theory · Computer Science 2020-01-10 Suihua Cai , Wenchao Lin , Xinyuanmeng Yao , Baodian Wei , Xiao Ma

This paper is concerned with a class of low density generator matrix codes (LDGM), called repetition and superposition (RaS) codes, which have been proved to be capacity-achieving over binary-input output-symmetric (BIOS) channels in terms…

Information Theory · Computer Science 2024-02-22 Yixin Wang , Xiao Ma

In this paper, by treating Reed-Muller (RM) codes as a special class of low-density parity-check (LDPC) codes and assuming that sub-blocks of the parity-check matrix are randomly interleaved to each other as Gallager's codes, we present a…

Information Theory · Computer Science 2025-04-24 Xiao Ma

In this paper, we prove the existence of capacity achieving linear codes with random binary sparse generating matrices. The results on the existence of capacity achieving linear codes in the literature are limited to the random binary codes…

Information Theory · Computer Science 2011-08-31 A. Makhdoumi Kakhaki , H. Karkeh Abadi , P. Pad , H. Saeedi , F. Marvasti , K. Alishahi

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

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

We derive bounds on the asymptotic density of parity-check matrices and the achievable rates of binary linear block codes transmitted over memoryless binary-input output-symmetric (MBIOS) channels. The lower bounds on the density of…

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

For any given short code (referred to as the basic code), block Markov superposition transmission (BMST) provides a simple way to obtain predictable extra coding gain by spatial coupling the generator matrix of the basic code. This paper…

Information Theory · Computer Science 2014-05-13 Chulong Liang , Xiao Ma , Qiutao Zhuang , Baoming Bai

The past decade has seen notable advances in our understanding of structured error-correcting codes, particularly binary Reed--Muller (RM) codes. While initial breakthroughs were for erasure channels based on symmetry, extending these…

Information Theory · Computer Science 2025-04-23 Henry D. Pfister , Galen Reeves

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

We introduce a new family of concatenated codes with an outer low-density parity-check (LDPC) code and an inner low-density generator matrix (LDGM) code, and prove that these codes can achieve capacity under any memoryless binary-input…

Information Theory · Computer Science 2016-08-31 Chun-Hao Hsu , Achilleas Anastasopoulos

Low-density parity-check (LDPC) convolutional codes have been shown to exhibit excellent performance under low-complexity belief-propagation decoding [1], [2]. This phenomenon is now termed threshold saturation via spatial coupling. The…

Information Theory · Computer Science 2013-12-30 Santhosh Kumar , Andrew J. Young , Nicolas Macris , Henry D. Pfister

In this paper, we study codes with sparse generator matrices. More specifically, low-density generator matrix (LDGM) codes with a certain constraint on the weight of the columns in the generator matrix are considered. In this paper, it is…

Information Theory · Computer Science 2022-06-28 James Chin-Jen Pang , Hessam Mahdavifar , S. Sandeep Pradhan

It was recently shown that spatial coupling of individual low-density parity-check codes improves the belief-propagation threshold of the coupled ensemble essentially to the maximum a posteriori threshold of the underlying ensemble. We…

Information Theory · Computer Science 2011-08-03 Vahid Aref , Rüdiger L. Urbanke

In this paper, we present an improved union bound on the Linear Programming (LP) decoding performance of the binary linear codes transmitted over an additive white Gaussian noise channels. The bounding technique is based on the second-order…

Information Theory · Computer Science 2012-03-09 Ohad Gidon , Yair Be'ery

Generalized bicycle (GB) codes have emerged as a promising class of quantum error-correcting codes with practical decoding capabilities. While numerous asymptotically good quantum codes and quantum low-density parity-check code…

Quantum Physics · Physics 2025-05-12 Olai Å. Mostad , Hsuan-Yin Lin , Eirik Rosnes , De-Shih Lee , Ching-Yi Lai

Assuming iterative decoding for binary erasure channels (BECs), a novel tree-based technique for upper bounding the bit error rates (BERs) of arbitrary, finite low-density parity-check (LDPC) codes is provided and the resulting bound can be…

Information Theory · Computer Science 2007-07-13 Chih-Chun Wang , Sanjeev R. Kulkarni , H. Vincent Poor

We introduce a new approach to proving that a sequence of deterministic linear codes achieves capacity on an erasure channel under maximum a posteriori decoding. Rather than relying on the precise structure of the codes our method exploits…

Information Theory · Computer Science 2016-01-19 Shrinivas Kudekar , Santhosh Kumar , Marco Mondelli , Henry D. Pfister , Eren Şaşoğlu , Rüdiger Urbanke

In this paper we study codes with sparse generator matrices. More specifically, codes with a certain constraint on the weight of all the columns in the generator matrix are considered. The end result is the following. For any binary-input…

Signal Processing · Electrical Eng. & Systems 2020-02-03 James Chin-Jen Pang , Hessam Mahdavifar , S. Sandeep Pradhan
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