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Approximate Message Passing (AMP) has been shown to be a superior method for inference problems, such as the recovery of signals from sets of noisy, lower-dimensionality measurements, both in terms of reconstruction accuracy and in…

Information Theory · Computer Science 2015-06-10 Andre Manoel , Florent Krzakala , Eric W. Tramel , Lenka Zdeborová

In this paper, we introduce the concept of spatially coupled turbo codes (SC-TCs), as the turbo codes counterpart of spatially coupled low-density parity-check codes. We describe spatial coupling for both Berrou et al. and Benedetto et al.…

Information Theory · Computer Science 2014-07-23 Saeedeh Moloudi , Michael Lentmaier , Alexandre Graell i Amat

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

Streaming codes (SCs) are packet-level codes that recover erased packets within a strict decoding-delay deadline. Streaming codes for various packet erasure channel models such as sliding-window (SW) channel models that admit random or…

Information Theory · Computer Science 2024-05-13 Shobhit Bhatnagar , P. Vijay Kumar

Compute-and-forward relaying is effective to increase bandwidth efficiency of wireless two-way relay channels. In a compute-and-forward scheme, a relay tries to decode a linear combination composed of transmitted messages from other…

Information Theory · Computer Science 2018-01-22 Satoshi Takabe , Yuta Ishimatsu , Tadashi Wadayama , Masahito Hayashi

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

The goal of predictive sparse coding is to learn a representation of examples as sparse linear combinations of elements from a dictionary, such that a learned hypothesis linear in the new representation performs well on a predictive task.…

Machine Learning · Computer Science 2012-10-09 Nishant A. Mehta , Alexander G. Gray

This paper presents a semantic-enhanced receiver framework for transmitting natural language sentences over noisy wireless channels using multiple short block codes. After ASCII encoding, the sentence is divided into segments, each…

Information Theory · Computer Science 2026-04-30 Jiafu Hao , Chentao Yue , Wanchun Liu , Branka Vucetic , Yonghui Li

In this paper we propose a novel power adapted network coding (PANC) for a non-orthogonal multiple-access relay channel (MARC), where two sources transmit their information simultaneously to the destination with the help of a relay.…

Signal Processing · Electrical Eng. & Systems 2020-03-03 Sha Wei , Jun Li , Wen Chen , Hang Su , Zihuai Lin , Branka Vucetic

We test whether Speech Articulatory Coding (SPARC) features can linearly predict surface electromyography (sEMG) envelopes across aloud, mimed, and subvocal speech in twenty-four subjects. Using elastic-net multivariate temporal response…

Random Linear Network Coding (RLNC) has been proved to offer an efficient communication scheme, leveraging an interesting robustness against packet losses. However, it suffers from a high computational complexity and some novel approaches,…

Networking and Internet Architecture · Computer Science 2016-07-25 Garrido Pablo , Lucani E. Daniel , Aguero Ramon

Recently a powerful class of rate-compatible serially concatenated convolutional codes (SCCCs) have been proposed based on minimizing analytical upper bounds on the error probability in the error floor region. Here this class of codes is…

Information Theory · Computer Science 2007-07-13 Alexandre Graell i Amat , Fredrik Brannstrom , Lars K. Rasmussen

Constellation shaping is an energy-efficient strategy involving the transmission of lower-energy signals more frequently than higher-energy signals. Previous work has shown that shaping is particularly effective when used with coded…

Information Theory · Computer Science 2012-10-18 Xingyu Xiang , Matthew C. Valenti

The generalized approximate message passing (GAMP) algorithm under the Bayesian setting shows advantage in recovering under-sampled sparse signals from corrupted observations. Compared to conventional convex optimization methods, it has a…

Information Theory · Computer Science 2017-01-12 Shuai Huang , Trac D. Tran

A novel code construction based on spatially coupled low-density parity-check (SC-LDPC) codes is presented. The proposed code ensembles are described by protographs, comprised of several protograph-based chains characterizing individual…

Information Theory · Computer Science 2016-11-18 Dmitri Truhachev , David G. M. Mitchell , Michael Lentmaier , Daniel J. Costello

Random linear network coding (RLNC) in theory achieves the max-flow capacity of multicast networks, at the cost of high decoding complexity. To improve the performance-complexity tradeoff, we consider the design of sparse network codes. A…

Information Theory · Computer Science 2016-04-20 Ye Li , Wai-Yip Chan , Steven D. Blostein

We establish the existence of wave-like solutions to spatially coupled graphical models which, in the large size limit, can be characterized by a one-dimensional real-valued state. This is extended to a proof of the threshold saturation…

Information Theory · Computer Science 2015-03-20 Shrinivas Kudekar , Tom Richardson , Ruediger Urbanke

We analyse a linear regression problem with nonconvex regularization called smoothly clipped absolute deviation (SCAD) under an overcomplete Gaussian basis for Gaussian random data. We propose an approximate message passing (AMP) algorithm…

Machine Learning · Statistics 2018-04-04 Ayaka Sakata , Yingying Xu

Designing high-performance error-correcting codes at short blocklengths is critical for low-latency communication systems, where decoding is governed by finite-length and graph-structural effects rather than asymptotic properties. This…

Information Theory · Computer Science 2026-04-10 Atharv Kanchi

This paper considers the massive connectivity application in which a large number of potential devices communicate with a base-station (BS) in a sporadic fashion. The detection of device activity pattern together with the estimation of the…

Information Theory · Computer Science 2018-03-14 Zhilin Chen , Foad Sohrabi , Wei Yu