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Recent works have shown that imposing tensor structures on the coefficient tensor in regression problems can lead to more reliable parameter estimation and lower sample complexity compared to vector-based methods. This work investigates a…

Machine Learning · Statistics 2023-08-08 Batoul Taki , Anand D. Sarwate , Waheed U. Bajwa

We consider near maximum-likelihood (ML) decoding of short linear block codes based on neural belief propagation (BP) decoding recently introduced by Nachmani et al.. While this method significantly outperforms conventional BP decoding, the…

Information Theory · Computer Science 2020-10-26 Andreas Buchberger , Christian Häger , Henry D. Pfister , Laurent Schmalen , Alexandre Graell i Amat

Spatially-coupled (SC) codes, known for their threshold saturation phenomenon and low-latency windowed decoding algorithms, are ideal for streaming applications and data storage systems. SC codes are constructed by partitioning an…

Information Theory · Computer Science 2021-09-21 Siyi Yang , Ahmed Hareedy , Robert Calderbank , Lara Dolecek

The recently proposed SCLF decoding algorithm for polar codes improves the error-correcting performance of state-of-the-art SCL decoding. However, it comes at the cost of a higher complexity. In this paper, partitioned polar codes tailored…

Information Theory · Computer Science 2026-05-12 Charles Pillet , Ilshat Sagitov , Pascal Giard

In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector…

Information Theory · Computer Science 2009-11-13 Tadashi Wadayama

Spatially-coupled (SC) codes, known for their threshold saturation phenomenon and low-latency windowed decoding algorithms, are ideal for streaming applications. They also find application in various data storage systems because of their…

Information Theory · Computer Science 2021-01-26 Siyi Yang , Ahmed Hareedy , Shyam Venkatasubramanian , Robert Calderbank , Lara Dolecek

Polarization-adjusted convolutional (PAC) codes are special concatenated codes in which we employ a one-to-one convolutional transform as a pre-coding step before the polar transform. In this scheme, the polar transform (as a mapper) and…

Information Theory · Computer Science 2020-07-13 Mohammad Rowshan , Emanuele Viterbo

In this paper, we propose an efficient reliability based segmentation-discarding decoding (SDD) algorithm for short block-length codes. A novel segmentation-discarding technique is proposed along with the stopping rule to significantly…

Information Theory · Computer Science 2019-01-23 Chentao Yue , Mahyar Shirvanimoghaddam , Yonghui Li , Branka Vucetic

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

A trend in compressed sensing (CS) is to exploit structure for improved reconstruction performance. In the basic CS model, exploiting the clustering structure among nonzero elements in the solution vector has drawn much attention, and many…

Computation · Statistics 2011-06-13 Zhilin Zhang , Bhaskar D. Rao

In this letter, we develop an efficient linear programming (LP) decoding algorithm for low-density parity-check (LDPC) codes. We first relax the maximum likelihood (ML) decoding problem to a LP problem by using check-node decomposition.…

Information Theory · Computer Science 2019-01-24 Jing Bai , Yongchao Wang , Francis C. M. Lau

Systematic polar codes are shown to outperform non-systematic polar codes in terms of the bit-error-rate (BER) performance. However theoretically the mechanism behind the better performance of systematic polar codes is not yet clear. In…

Information Theory · Computer Science 2015-04-17 Liping Li , Wenyi Zhang , Yanjun Hu

Polar codes are high density parity check codes and hence the sparse factor graph, instead of the parity check matrix, has been used to practically represent an LP polytope for LP decoding. Although LP decoding on this polytope has the…

Information Theory · Computer Science 2014-04-30 Veeresh Taranalli , Paul H. Siegel

To decode a short linear block code, ordered statics decoding (OSD) and/or the $A^*$ decoding are usually considered. Either OSD or the $A^*$ decoding utilizes the magnitudes of the received symbols to establish the most reliable and…

Information Theory · Computer Science 2025-05-16 Mao-Chao Lin , Shih-Kai Lee , Pin Lin , Ching-Chang Lin , Chia-Chun Chen , Teng-Yuan Syu , Huang-Chang Lee

For polar codes, successive cancellation list (SCL) decoding algorithm significantly improves finite-length performance compared to SC decoding. SCL-flip decoding can further enhance the performance but the gain diminishes as code length…

Information Theory · Computer Science 2024-07-08 Xianbin Wang , Huazi Zhang , Jiajie Tong , Jun Wang , Wen Tong

The construction of polar codes for channels other than BECs requires sorting of all bit channels and then selecting the best $K$ of them for a block length $N=2^n$. In this paper, two types of partial orders (PO) of polar codes are…

Information Theory · Computer Science 2017-04-25 Wei Wang , Liping Li

In this paper, soft-decision (SD) decoders of permutation trellis code (PTC) with $M$-ary frequency shift keying are designed using three optimization algorithms and presented in four decoding schemes. In a concatenated code such as PTC,…

Signal Processing · Electrical Eng. & Systems 2020-11-12 Oluwafemi Kolade , Mulundumina Shimaponda-Nawa , Daniel J. J. Versfeld , Ling Cheng

Polar codes are a class of channel capacity achieving codes that has been selected for the next generation of wireless communication standards. Successive-cancellation (SC) is the first proposed decoding algorithm, suffering from mediocre…

Information Theory · Computer Science 2018-10-09 Furkan Ercan , Carlo Condo , Seyyed Ali Hashemi , Warren J. Gross

In this paper, we study the sequential convex programming method with monotone line search (SCP$_{ls}$) in [46] for a class of difference-of-convex (DC) optimization problems with multiple smooth inequality constraints. The SCP$_{ls}$ is a…

Optimization and Control · Mathematics 2021-05-12 Peiran Yu , Ting Kei Pong , Zhaosong Lu

We study the task of Multiclass Linear Classification (MLC) in the distribution-free PAC model with Random Classification Noise (RCN). Specifically, the learner is given a set of labeled examples $(x, y)$, where $x$ is drawn from an unknown…

Machine Learning · Computer Science 2025-02-18 Ilias Diakonikolas , Mingchen Ma , Lisheng Ren , Christos Tzamos