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Consider a lossy compression system with $\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under…

Information Theory · Computer Science 2018-07-19 Yizhong Wang , Li Xie , Xuan Zhang , Jun Chen

We consider a multiterminal source coding problem in which a source is estimated at a central processing unit from lossy-compressed remote observations. Each lossy-encoded observation is produced by a remote sensor which obtains a noisy…

Information Theory · Computer Science 2016-05-13 Ruiyang Song , Stefano Rini , Alon Kipnis , Andrea J. Goldsmith

A conjectural expression of the asymptotic gap between the rate-distortion function of an arbitrary generalized Gaussian multiterminal source coding system and that of its centralized counterpart in the high-resolution regime is proposed.…

Information Theory · Computer Science 2019-08-19 Li Xie , Xiaolan Tu , Siyao Zhou , Jun Chen

A distributed lossy compression network with $L$ encoders and a decoder is considered. Each encoder observes a source and sends a compressed version to the decoder. The decoder produces a joint reconstruction of target signals with the mean…

Information Theory · Computer Science 2022-06-06 Siyao Zhou , Sadaf Salehkalaibar , Jingjing Qian , Jun Chen , Wuxian Shi , Yiqun Ge , Wen Tong

We investigate whether uncoded schemes are optimal for Gaussian sources on multiuser Gaussian channels. Particularly, we consider two problems: the first is to send correlated Gaussian sources on a Gaussian broadcast channel where each…

Information Theory · Computer Science 2017-03-02 Chao Tian , Jun Chen , Suhas Diggavi , Shlomo Shamai

An encoder, subject to a rate constraint, wishes to describe a Gaussian source under squared error distortion. The decoder, besides receiving the encoder's description, also observes side information consisting of uncompressed source symbol…

Information Theory · Computer Science 2013-05-10 Chris T. K. Ng , Chao Tian , Andrea J. Goldsmith , Shlomo Shamai

A novel distributed source coding model which named semantic-aware multi-terminal (MT) source coding is proposed and investigated in the paper, where multiple agents independently encode an imperceptible semantic source, while both semantic…

Information Theory · Computer Science 2024-04-24 Yuxuan Shi , Shuo Shao , Yongpeng Wu , Jun Chen , Wenjun Zhang

Jointly Gaussian memoryless sources are observed at N distinct terminals. The goal is to efficiently encode the observations in a distributed fashion so as to enable reconstruction of any one of the observations, say the first one, at the…

Information Theory · Computer Science 2008-05-14 Saurabha Tavildar , Pramod Viswanath , Aaron B. Wagner

We consider the classical two-encoder multiterminal source coding problem where distortion is measured under logarithmic loss. We provide a single-letter characterization of the achievable rate distortion region for arbitrarily correlated…

Information Theory · Computer Science 2012-07-12 Thomas Courtade , Tsachy Weissman

Transmission of a Gaussian source over a time-varying Gaussian channel is studied in the presence of time-varying correlated side information at the receiver. A block fading model is considered for both the channel and the side information,…

Information Theory · Computer Science 2015-05-27 Iñaki Estella Aguerri , Deniz Gündüz

We consider the k-encoder source coding problem with a quadratic distortion measure. We show that among all source distributions with a given covariance matrix K, the jointly Gaussian source requires the highest rates in order to meet a…

Information Theory · Computer Science 2016-11-15 Ilan Shomorony , A. Salman Avestimehr , Himanshu Asnani , Tsachy Weissman

Consider a Gaussian memoryless multiple source with $m$ components with joint probability distribution known only to lie in a given class of distributions. A subset of $k \leq m$ components are sampled and compressed with the objective of…

Information Theory · Computer Science 2018-03-16 Vinay Praneeth Boda

In this paper, we consider a distributed remote source coding problem, where a sequence of observations of source vectors is available at the encoder. The problem is to specify the optimal rate for encoding the observations subject to a…

Information Theory · Computer Science 2014-06-05 Adel Zahedi , Jan Ostergaard , Soren Holdt Jensen , Patrick Naylor , Soren Bech

We investigate distributed source coding of two correlated sources X and Y where messages are passed to a decoder in a cascade fashion. The encoder of X sends a message at rate R_1 to the encoder of Y. The encoder of Y then sends a message…

Information Theory · Computer Science 2009-05-13 Paul Cuff , Han-I Su , Abbas El Gamal

Transmission of a Gaussian source over a time-varying multiple-input multiple-output (MIMO) channel is studied under strict delay constraints. Availability of a correlated side information at the receiver is assumed, whose quality, i.e.,…

Information Theory · Computer Science 2015-05-27 Iñaki Estella Aguerri , Deniz Gündüz

We characterize the rate-distortion function for zero-mean stationary Gaussian sources under the MSE fidelity criterion and subject to the additional constraint that the distortion is uncorrelated to the input. The solution is given by two…

Information Theory · Computer Science 2008-01-14 Milan S. Derpich , Jan Ostergaard , Graham C. Goodwin

This paper studies a variant of the rate-distortion problem motivated by task-oriented semantic communication and distributed learning problems, where $M$ correlated sources are independently encoded for a central decoder. The decoder has…

Information Theory · Computer Science 2024-05-24 Jiancheng Tang , Qianqian Yang , Deniz Gündüz

We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements from an underlying random process, code and transmit those…

Information Theory · Computer Science 2007-07-13 Nan Liu , Sennur Ulukus

We consider the distributed source coding system of $L$ correlated Gaussian sources $Y_i,i=1,2,...,L$ which are noisy observations of correlated Gaussian remote sources $X_k, k=1,2,...,K$. We assume that $Y^{L}={}^{\rm t}(Y_1,Y_2,$ $...,…

Information Theory · Computer Science 2011-02-21 Yasutada Oohama

We consider the distributed source coding system for $L$ correlated Gaussian observations $Y_i, i=1,2, ..., L$. Let $X_i,i=1,2, ..., L$ be $L$ correlated Gaussian random variables and $N_i,$ $i=1,2,... L$ be independent additive Gaussian…

Information Theory · Computer Science 2009-08-09 Yasutada Oohama
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