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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

Compressive sensing (CS) has recently emerged as an extremely efficient technology of the wideband spectrum sensing. In compressive spectrum sensing (CSS), it is necessary to know the sparsity or the noise information in advance for…

Signal Processing · Electrical Eng. & Systems 2022-11-15 Liyang Lu , Wenbo Xu , Yue Wang , Zhi Tian

Direct satellite uplink is severely constrained by limited link budgets, which hinder the exploitation of wideband resources, and ultimately limit the throughout. This paper presents a pilot-less coded modulation scheme based on sparse…

Information Theory · Computer Science 2026-04-23 Alberto G. Perotti , Branislav M. Popovic , Renaud-Alexandre Pitaval

In this paper, we propose a physical-layer rateless code for wireless channels. A novel rateless encoding scheme is developed to overcome the high error floor problem caused by the low-density generator matrix (LDGM)-like encoding scheme in…

Information Theory · Computer Science 2013-06-25 Shuang Tian , Yonghui Li , Mahyar Shirvanimoghaddam , Branka Vucetic

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

Polar codes are capacity-achieving error-correcting codes with an explicit construction that can be decoded with low-complexity algorithms. In this work, we show how the state-of-the-art low-complexity decoding algorithm can be improved to…

Information Theory · Computer Science 2016-08-29 Pascal Giard , Alexios Balatsoukas-Stimming , Gabi Sarkis , Claude Thibeault , Warren J. Gross

Decoding via sequentially guessing the error pattern in a received noisy sequence has received attention recently, and ORBGRAND has been proposed as one such decoding algorithm that is capable of utilizing the soft information embedded in…

Information Theory · Computer Science 2022-12-20 Mengxiao Liu , Yuejun Wei , Zhenyuan Chen , Wenyi Zhang

Error correction techniques traditionally focus on the co-design of restricted code-structures in tandem with code-specific decoders that are computationally efficient when decoding long codes in hardware. Modern applications are, however,…

Information Theory · Computer Science 2022-10-12 Ken R. Duffy , Wei An , Muriel Medard

Sparse and convolutional constraints form a natural prior for many optimization problems that arise from physical processes. Detecting motifs in speech and musical passages, super-resolving images, compressing videos, and reconstructing…

Computer Vision and Pattern Recognition · Computer Science 2014-06-11 Hilton Bristow , Simon Lucey

This paper proposes a subspace decomposition method based on an over-complete dictionary in sparse representation, called "Sparse Signal Subspace Decomposition" (or 3SD) method. This method makes use of a novel criterion based on the…

Machine Learning · Statistics 2016-10-28 Hong Sun , Chengwei Sang , Didier Le Ruyet

This paper investigates guesswork over ordered statistics and formulates the achievable guesswork complexity of ordered statistics decoding (OSD) in binary additive white Gaussian noise (AWGN) channels. The achievable guesswork complexity…

Information Theory · Computer Science 2024-12-18 Chentao Yue , Changyang She , Branka Vucetic , Yonghui Li

This paper presents a refined analysis of the block error rate (BLER) of polar codes over symmetric binary-input discrete memoryless channels under successive cancellation (SC) and successive cancellation list (SCL) decoding. A novel…

Information Theory · Computer Science 2026-03-23 Hassan Noghrei , Murad Abdullah

Sparse codes in neuroscience have been suggested to offer certain computational advantages over other neural representations of sensory data. To explore this viewpoint, a sparse code is used to represent natural images in an optimal control…

Machine Learning · Computer Science 2021-01-08 Peter N. Loxley

The design and implementation of error correcting codes has long been informed by two fundamental results: Shannon's 1948 capacity theorem, which established that long codes use noisy channels most efficiently; and Berlekamp, McEliece, and…

Information Theory · Computer Science 2024-10-30 Ken R. Duffy , Muriel Médard , Wei An

We propose and practically demonstrate a joint detection and decoding scheme for short-packet wireless communications in scenarios that require to first detect the presence of a message before actually decoding it. For this, we extend the…

Information Theory · Computer Science 2022-07-13 Sebastian Dörner , Jannis Clausius , Sebastian Cammerer , Stephan ten Brink

The problem of super-resolution compressive sensing (SR-CS) is crucial for various wireless sensing and communication applications. Existing methods often suffer from limited resolution capabilities and sensitivity to hyper-parameters,…

Signal Processing · Electrical Eng. & Systems 2025-08-12 Yufan Zhou , Jingyi Li , Wenkang Xu , An Liu

In this paper, we propose a framework for cross-layer optimization to ensure ultra-high reliability and ultra-low latency in radio access networks, where both transmission delay and queueing delay are considered. With short transmission…

Information Theory · Computer Science 2017-10-10 Changyang She , Chenyang Yang , Tony Q. S. Quek

The orthogonal time frequency space (OTFS) modulation has emerged as a promising modulation scheme for high mobility wireless communications. To enable efficient OTFS detection in the delay-Doppler (DD) domain, the DD domain channels need…

Information Theory · Computer Science 2021-06-08 Fei Liu , Zhengdao Yuan , Qinghua Guo , Zhongyong Wang , Peng Sun

Motivated by modern network communication applications which require low latency, we study codes that correct erasures with low decoding delay. We provide a simple explicit construction that yields convolutional codes that can correct both…

Information Theory · Computer Science 2023-02-20 Serge Kas Hanna , Zhiyuan Tan , Wen Xu , Antonia Wachter-Zeh

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
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