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Motivated by hyper-reliable low-latency communication in 6G, we consider error control coding for short block lengths in multi-antenna fading channels. In general, the channel fading coefficients are unknown at both the transmitter and…

Signal Processing · Electrical Eng. & Systems 2025-05-13 Sai Dinesh Kancharana , Madhusudan Kumar Sinha , Arun Pachai Kannu

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

Belief propagation applied to iterative decoding and sparse recovery through approximate message passing (AMP) are two research areas that have seen monumental progress in recent decades. Inspired by these advances, this article introduces…

Information Theory · Computer Science 2023-01-06 Jamison R. Ebert , Jean-Francois Chamberland , Krishna R. Narayanan

Sparse Regression Codes (SPARCs) are capacity-achieving codes introduced for communication over the Additive White Gaussian Noise (AWGN) channels and were later extended to general memoryless channels. In particular it was shown via…

Information Theory · Computer Science 2024-09-10 Yuhao Liu , Yizhou Xu , Tianqi Hou

Sparse superposition codes, or sparse regression codes (SPARCs), are a recent class of codes for reliable communication over the AWGN channel at rates approaching the channel capacity. Approximate message passing (AMP) decoding, a…

Information Theory · Computer Science 2019-04-24 Cynthia Rush , Ramji Venkataramanan

We study sparse regression codes (SPARC) for multiple access channels with multiple receive antennas, in non-coherent flat fading channels. We propose a novel practical decoder, referred to as maximum likelihood matching pursuit (MLMP),…

Signal Processing · Electrical Eng. & Systems 2025-07-16 V S V Sandeep , Sai Dinesh Kancharana , Arun Pachai Kannu

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

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

Sparse regression codes (SPARC) connect the sparse signal recovery framework of compressive sensing with error control coding techniques. SPARC encoding produces codewords which are \emph{sparse} linear combinations of columns of a…

Information Theory · Computer Science 2023-03-27 Madhusudan Kumar Sinha , Arun Pachai Kannu

Sparse regression codes (SPARCs) are a promising coding scheme that can approach the Shannon limit over Additive White Gaussian Noise (AWGN) channels. Previous works have proven the capacity-achieving property of SPARCs with Gaussian design…

Information Theory · Computer Science 2023-03-16 Yizhou Xu , YuHao Liu , ShanSuo Liang , Tingyi Wu , Bo Bai , Jean Barbier , TianQi Hou

A joint sparse-regression-code (SPARC) and low-density-parity-check (LDPC) coding scheme for multiple-input multiple-output (MIMO) massive unsourced random access (URA) is proposed in this paper. Different from the state-of-the-art…

Information Theory · Computer Science 2022-01-12 Tianya Li , Yongpeng Wu , Mengfan Zheng , Dongming Wang , Wenjun Zhang

Developing computationally-efficient codes that approach the Shannon-theoretic limits for communication and compression has long been one of the major goals of information and coding theory. There have been significant advances towards this…

Information Theory · Computer Science 2019-11-05 Ramji Venkataramanan , Sekhar Tatikonda , Andrew Barron

Sparse superposition codes are a recent class of codes introduced by Barron and Joseph for efficient communication over the AWGN channel. With an appropriate power allocation, these codes have been shown to be asymptotically…

Information Theory · Computer Science 2018-03-19 Adam Greig , Ramji Venkataramanan

Next-generation wireless communication systems impose much stricter requirements for transmission rate, latency, and reliability. The peak data rate of 6G networks should be no less than 1 Tb/s, which is comparable to existing long-haul…

Information Theory · Computer Science 2024-10-28 Kirill Andreev , Pavel Rybin , Alexey Frolov

This paper studies a generalization of sparse superposition codes (SPARCs) for communication over the complex additive white Gaussian noise (AWGN) channel. In a SPARC, the codebook is defined in terms of a design matrix, and each codeword…

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

This paper considers the massive MIMO unsourced random access problem in a quasi-static Rayleigh fading setting. The proposed coding scheme is based on a concatenation of a "conventional" channel code (such as, e.g., LDPC) serving as an…

Signal Processing · Electrical Eng. & Systems 2023-05-01 Patrick Agostini , Zoran Utkovski , Slawomir Stanczak

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

Novel sparse regression LDPC (SR-LDPC) codes exhibit excellent performance over additive white Gaussian noise (AWGN) channels in part due to their natural provision of shaping gains. Though SR-LDPC-like codes have been considered within the…

Information Theory · Computer Science 2024-02-13 Jamison R. Ebert , Jean-Francois Chamberland , Krishna R. Narayanan

Rate-matching of low-density parity-check (LDPC) codes enables a single code description to support a wide range of code lengths and rates. In 5G NR, rate matching is accomplished by extending (lifting) a base code to a desired target…

Information Theory · Computer Science 2024-10-29 Reinhard Wiesmayr , Darja Nonaca , Chris Dick , Christoph Studer

Low-density parity-check (LDPC) codes together with belief propagation (BP) decoding yield exceptional error correction capabilities in the large block length regime. Yet, there remains a gap between BP decoding and maximum likelihood…

Information Theory · Computer Science 2025-01-22 Jonathan Mandelbaum , Holger Jäkel , Laurent Schmalen
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