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We introduce Noise Recycling, a method that substantially enhances decoding performance of orthogonal channels subject to correlated noise without the need for joint encoding or decoding. The method can be used with any combination of…

Information Theory · Computer Science 2020-06-11 Alejandro Cohen , Amit Solomon , Ken R. Duffy , Muriel Médard

Departing from traditional communication theory where decoding algorithms are assumed to perform without error, a system where noise perturbs both computational devices and communication channels is considered here. This paper studies…

Information Theory · Computer Science 2010-05-31 Lav R. Varshney

Point-to-multipoint communications are expected to play a pivotal role in next-generation networks. This paper refers to a cellular system transmitting layered multicast services to a multicast group of users. Reliability of communications…

Information Theory · Computer Science 2016-11-17 Andrea Tassi , Ioannis Chatzigeorgiou , Daniel E. Lucani

List decoding for arbitrarily varying channels (AVCs) under state constraints is investigated. It is shown that rates within $\epsilon$ of the randomized coding capacity of AVCs with input-dependent state can be achieved under maximal error…

Information Theory · Computer Science 2009-10-06 Anand D. Sarwate , Michael Gastpar

This paper studies cross-domain lossy compression through the lens of minimum entropy coupling (MEC) with rate and classification constraints. In this setting, an encoder observes samples from a degraded source domain, while the decoder is…

Information Theory · Computer Science 2026-05-12 Nam Nguyen , Hassan Tavakoli , An Vuong , Thinh Nguyen , Bella Bose

We present an optimal method for encoding cluster assignments of arbitrary data sets. Our method, Random Cycle Coding (RCC), encodes data sequentially and sends assignment information as cycles of the permutation defined by the order of…

Machine Learning · Computer Science 2024-12-03 Daniel Severo , Ashish Khisti , Alireza Makhzani

Compressed sensing (CS) shows that a signal having a sparse or compressible representation can be recovered from a small set of linear measurements. In classical CS theory, the sampling matrix and representation matrix are assumed to be…

Information Theory · Computer Science 2015-07-03 Yipeng Liu

Reed-Muller (RM) codes are conjectured to achieve the capacity of any binary-input memoryless symmetric (BMS) channel, and are observed to have a comparable performance to that of random codes in terms of scaling laws. On the negative side,…

Information Theory · Computer Science 2021-02-03 Mohammad Vahid Jamali , Xiyang Liu , Ashok Vardhan Makkuva , Hessam Mahdavifar , Sewoong Oh , Pramod Viswanath

Stochastic encoders for channel coding and lossy source coding are introduced with a rate close to the fundamental limits, where the only restriction is that the channel input alphabet and the reproduction alphabet of the lossy source code…

Information Theory · Computer Science 2016-11-15 Jun Muramatsu

We consider the problem of remotely stabilizing a dynamical system. A sensor (encoder) co-located with the system communicates with a controller (decoder), whose goal is to stabilize the system, over a noisy communication channel with…

Information Theory · Computer Science 2025-08-07 Barron Han , Oron Sabag , Victoria Kostina , Babak Hassibi

In this paper, we consider the ChannelComp framework, which facilitates the computation of desired functions by multiple transmitters over a common receiver using digital modulations across a multiple access channel. While ChannelComp…

Signal Processing · Electrical Eng. & Systems 2024-04-26 Xiaojing Yan , Saeed Razavikia , Carlo Fischione

We propose an iterative decoding method, which we call turbo-CS, for the reception of concatenated source-channel encoded sparse signals transmitted over an AWGN channel. The turbo-CS encoder applies 1-bit compressed sensing as a source…

Information Theory · Computer Science 2016-11-23 Amin Movahed , Mark C. Reed , Shahriar Etemadi Tajbakhsh

The ubiquitous time-delay estimation (TDE) problem becomes nontrivial when sensors are non-co-located and communication between them is limited. Building on the recently proposed "extremum encoding" compression-estimation scheme, we address…

Signal Processing · Electrical Eng. & Systems 2024-12-25 Amir Weiss , Yuval Kochman , Gregory W. Wornell

This paper adapts a Multiple-Model Coding (MMC) approach for sampled electrical signal waveforms to satisfy reconstructed signal quality constraints. The baseline MMC approach consists of two stages processing vectors of Voltage and Current…

Signal Processing · Electrical Eng. & Systems 2025-11-14 Corentin Presvôts , Michel Kieffer , Thibault Prevost

Neural speech codecs aim to compress input signals into minimal bits while maintaining content quality in a low-latency manner. However, existing neural codecs often trade model complexity for reconstruction performance. These codecs…

Sound · Computer Science 2024-10-04 Yuzhe Gu , Enmao Diao

The code that combines channel estimation and error protection has received general attention recently, and has been considered a promising methodology to compensate multi-path fading effect. It has been shown by simulations that such code…

Information Theory · Computer Science 2007-12-18 Chia-Lung Wu , Po-Ning Chen , Yunghsiang S. Han , Ming-Hsin Kuo

Reed-Muller (RM) codes are one of the oldest families of codes. Recently, a recursive projection aggregation (RPA) decoder has been proposed, which achieves a performance that is close to the maximum likelihood decoder for short-length RM…

Information Theory · Computer Science 2020-11-30 Dorsa Fathollahi , Nariman Farsad , Seyyed Ali Hashemi , Marco Mondelli

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

This paper explores the application of reinforcement learning techniques to enhance the performance of decoding of linear block codes based on flipping bits and finding optimal decisions. We describe the methodology for mapping the…

Information Theory · Computer Science 2025-07-29 Milad Taghipour , Bane Vasic

We present error-correcting codes that achieve the information-theoretically best possible trade-off between the rate and error-correction radius. Specifically, for every $0 < R < 1$ and $\eps> 0$, we present an explicit construction of…

Information Theory · Computer Science 2007-10-08 Venkatesan Guruswami , Atri Rudra