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Motivated by the need for channel codes with low-complexity soft-decision decoding algorithms, we consider the recursive Plotkin concatenation of optimal low-rate and high-rate codes based on simplex codes and their duals. These component…

Information Theory · Computer Science 2025-10-14 Andreas Zunker , Marvin Rübenacke , Stephan ten Brink

Several types of AL-FEC (Application-Level FEC) codes for the Packet Erasure Channel exist. Random Linear Codes (RLC), where redundancy packets consist of random linear combinations of source packets over a certain finite field, are a…

Information Theory · Computer Science 2014-08-26 Kazuhisa Matsuzono , Vincent Roca , Hitoshi Asaeda

Sparse random linear network coding (SRLNC) is an attractive technique proposed in the literature to reduce the decoding complexity of random linear network coding. Recognizing the fact that the existing SRLNC schemes are not efficient in…

Information Theory · Computer Science 2013-11-12 Kaveh Mahdaviani , Raman Yazdani , Masoud Ardakani

This paper proposes the design of polar and convolutional coset codes for the unequal message protection (UMP) in the short blocklength regime, to overcome the rate loss introduced by preamble-based solutions. After providing conditions to…

Information Theory · Computer Science 2026-04-21 Alexander Sauter , Riccardo Schiavone , Lucía Balsa Picado , Gianluigi Liva

Ultra-reliable low-latency communications (URLLC) operate with short packets, where finite-blocklength effects make near-maximum-likelihood (near-ML) decoding desirable but often too costly. This paper proposes a two-stage near-ML decoding…

Information Theory · Computer Science 2026-02-10 Yubeen Jo , Geon Choi , Yongjune Kim , Namyoon Lee

Sparse superposition codes, also called sparse regression codes (SPARCs), are a class of codes for efficient communication over the AWGN channel at rates approaching the channel capacity. In a standard SPARC, codewords are sparse linear…

Information Theory · Computer Science 2021-06-25 Cynthia Rush , Kuan Hsieh , Ramji Venkataramanan

Long polar codes can achieve the capacity of arbitrary binary-input discrete memoryless channels under a low complexity successive cancelation (SC) decoding algorithm. But for polar codes with short and moderate code length, the decoding…

Information Theory · Computer Science 2016-11-18 Jun Lin , Chenrong Xiong , Zhiyuan Yan

This article introduces a novel concatenated coding scheme called sparse regression LDPC (SR-LDPC) codes. An SR-LDPC code consists of an outer non-binary LDPC code and an inner sparse regression code (SPARC) whose respective field size and…

Information Theory · Computer Science 2024-10-28 Jamison R. Ebert , Jean-Francois Chamberland , Krishna R. Narayanan

We consider sparse superposition codes (SPARCs) over complex AWGN channels. Such codes can be efficiently decoded by an approximate message passing (AMP) decoder, whose performance can be predicted via so-called state evolution in the…

Information Theory · Computer Science 2021-03-09 Haiwen Cao , Pascal O. Vontobel

Non-binary linear block codes (NB-LBCs) are an important class of error-correcting codes that are especially competent in correcting burst errors. They have broad applications in modern communications and storage systems. However, efficient…

Information Theory · Computer Science 2026-01-21 Jingyu Lin , Li Chen , Xiaoqian Ye

Long polar codes can achieve the symmetric capacity of arbitrary binary-input discrete memoryless channels under a low complexity successive cancelation (SC) decoding algorithm. However, for polar codes with short and moderate code length,…

Hardware Architecture · Computer Science 2014-11-18 Jun Lin , Zhiyuan Yan

Point-to-multipoint communications are expected to play a pivotal role in next-generation networks. This paper refers to a cellular system transmitting layered multicast services to a multicast group of users. Reliability of communications…

Information Theory · Computer Science 2016-11-17 Andrea Tassi , Ioannis Chatzigeorgiou , Daniel E. Lucani

Nowadays polar codes are becoming one of the most favorable capacity achieving error correction codes for their low encoding and decoding complexity. However, due to the large code length required by practical applications, the few existing…

Hardware Architecture · Computer Science 2011-11-04 Chuan Zhang , Bo Yuan , Keshab K. Parhi

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 letter, we analyze the achievable rate of ultra-reliable low-latency communications (URLLC) in a randomly modeled wireless network. We use two mathematical tools to properly characterize the considered system: i) stochastic geometry…

Information Theory · Computer Science 2019-10-31 Jeonghun Park

In this paper, we propose a network coding (NC) based approach to ultra-reliable low-latency communication (URLLC) over erasure channels. In transmitting multiple data packets, we demonstrate that the use of random NC can improve the…

Information Theory · Computer Science 2021-11-23 Jinho Choi

Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the AWGN channel at rates approaching the channel capacity. The codebook is defined in terms of a Gaussian design matrix, and codewords…

Information Theory · Computer Science 2017-03-14 Cynthia Rush , Adam Greig , Ramji Venkataramanan

Ultra-reliable low-latency communications (URLLC) demand high-performance error-correcting codes and decoders in the finite blocklength regime. This letter introduces a novel two-stage near-maximum likelihood (near-ML) decoding framework…

Signal Processing · Electrical Eng. & Systems 2026-02-10 Yubeen Jo , Geon Choi , Yongjune Kim , Namyoon Lee

Ultra-reliable low latency communication (URLLC) is a key part of 5G wireless systems. Achieving low latency necessitates codes with short blocklengths for which polar codes with successive cancellation list (SCL) decoding typically…

Hardware Architecture · Computer Science 2025-12-22 Darja Nonaca , Jérémy Guichemerre , Reinhard Wiesmayr , Nihat Engin Tunali , Christoph Studer

We present a comprehensive framework for structured sparse coding and modeling extending the recent ideas of using learnable fast regressors to approximate exact sparse codes. For this purpose, we develop a novel block-coordinate proximal…

Machine Learning · Computer Science 2012-06-22 Alex Bronstein , Pablo Sprechmann , Guillermo Sapiro