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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

Distributed source coding is traditionally viewed in the block coding context -- all the source symbols are known in advance at the encoders. This paper instead considers a streaming setting in which iid source symbol pairs are revealed to…

Information Theory · Computer Science 2007-07-13 Cheng Chang , Stark Draper , Anant Sahai

We consider the distributed source coding problem in which correlated data picked up by scattered sensors has to be encoded separately and transmitted to a common receiver, subject to a rate-distortion constraint. Although near-tooptimal…

Information Theory · Computer Science 2008-09-09 G. Maierbacher , J. Barros

A sequential updating scheme (SUS) for belief propagation (BP) decoding of LDPC codes over Galois fields, $GF(q)$, and correlated Markov sources is proposed, and compared with the standard parallel updating scheme (PUS). A thorough…

Information Theory · Computer Science 2009-11-11 Nadav Yacov , Hadar Efraim , Haggai Kfir , Ido Kanter , Ori Shental

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

This article presents a novel enhancement to the random spreading based coding scheme developed by Pradhan et al.\ for the unsourced multiple access channel. The original coding scheme features a polar outer code in conjunction with a…

Information Theory · Computer Science 2021-05-31 Asit Kumar Pradhan , Vamsi K. Amalladinne , Krishna R. Narayanan , Jean-Francois Chamberland

Sphere decoding (SD) of polar codes is an efficient method to achieve the error performance of maximum likelihood (ML) decoding. But the complexity of the conventional sphere decoder is still high, where the candidates in a target sphere…

Information Theory · Computer Science 2013-08-14 Kai Niu , Kai Chen , Jiaru Lin

Optimal modulation (OM) schemes for Gaussian channels with peak and average power constraints are known to require nonuniform probability distributions over signal points, which presents practical challenges. An established way to map…

Information Theory · Computer Science 2022-11-01 Basak Ozaydin , Muriel Médard , Ken Duffy

The cyclic block coordinate descent-type (CBCD-type) methods, which performs iterative updates for a few coordinates (a block) simultaneously throughout the procedure, have shown remarkable computational performance for solving strongly…

Optimization and Control · Mathematics 2017-11-23 Xingguo Li , Tuo Zhao , Raman Arora , Han Liu , Mingyi Hong

Rank metric codes and constant-dimension codes (CDCs) have been considered for error control in random network coding. Since decoder errors are more detrimental to system performance than decoder failures, in this paper we investigate the…

Information Theory · Computer Science 2010-04-01 Maximilien Gadouleau , Zhiyuan Yan

Large-scale overlapping problems are prevalent in practical engineering applications, and the optimization challenge is significantly amplified due to the existence of shared variables. Decomposition-based cooperative coevolution (CC)…

Neural and Evolutionary Computing · Computer Science 2024-04-17 Maojiang Tian , Mingke Chen , Wei Du , Yang Tang , Yaochu Jin

A number of problems in relational Artificial Intelligence can be viewed as Stochastic Constraint Optimization Problems (SCOPs). These are constraint optimization problems that involve objectives or constraints with a stochastic component.…

Artificial Intelligence · Computer Science 2018-07-04 Anna L. D. Latour , Behrouz Babaki , Siegfried Nijssen

Contrastive decoding (CD) (Li et al., 2023) improves the next-token distribution of a large expert language model (LM) using a small amateur LM. Although CD is applied to various LMs and domains to enhance open-ended text generation, it is…

Computation and Language · Computer Science 2024-11-05 Haw-Shiuan Chang , Nanyun Peng , Mohit Bansal , Anil Ramakrishna , Tagyoung Chung

Coded computing has emerged as a promising framework for tackling significant challenges in large-scale distributed computing, including the presence of slow, faulty, or compromised servers. In this approach, each worker node processes a…

Machine Learning · Computer Science 2026-03-26 Parsa Moradi , Behrooz Tahmasebi , Mohammad Ali Maddah-Ali

We describe a novel approach to interpret a polar code as a low-density parity-check (LDPC)-like code with an underlying sparse decoding graph. This sparse graph is based on the encoding factor graph of polar codes and is suitable for…

Information Theory · Computer Science 2018-05-15 Sebastian Cammerer , Moustafa Ebada , Ahmed Elkelesh , Stephan ten Brink

In this paper, we prove that the sub-field images of generalized Reed-Solomon (RS) codes can achieve the symmetric capacity of p-ary memoryless channels. Unlike the totally random linear code ensemble, as a class of maximum distance…

Information Theory · Computer Science 2025-05-14 Xiangping Zheng , Xiao Ma

In this paper, we propose a finite alphabet message passing algorithm for LDPC codes that replaces the standard min-sum variable node update rule by a mapping based on generic look-up tables. This mapping is designed in a way that maximizes…

Information Theory · Computer Science 2015-10-16 Alexios Balatsoukas-Stimming , Michael Meidlinger , Reza Ghanaatian , Gerald Matz , Andreas Burg

A Bounded-Degree Low-Rank Parity-Check (BD-LRPC) code is a rank-metric code that admits a parity-check matrix whose support is generated by a set of powers of an element. This specific structure of the parity-check matrix was employed to…

Information Theory · Computer Science 2025-09-17 Hermann Tchatchiem Kamche

Compressive sensing (CS) is a sampling technique designed for reducing the complexity of sparse data acquisition. One of the major obstacles for practical deployment of CS techniques is the signal reconstruction time and the high storage…

Information Theory · Computer Science 2011-07-12 Wei Dai , Olgica Milenkovic , Hoa Vin Pham

Subcode-ensemble decoders improve iterative decoding by running multiple decoders in parallel over carefully chosen subcodes, increasing the likelihood that at least one decoder avoids the dominant trapping structures. Achieving strong…

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