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Motivated by the growing application of wireless multi-access networks with stringent delay constraints, we investigate the Gaussian multiple access channel (MAC) in the finite blocklength regime. Building upon information spectrum…

Information Theory · Computer Science 2013-09-11 Ebrahim MolavianJazi , J. Nicholas Laneman

Using a mild variant of polar codes we design linear compression schemes compressing Hidden Markov sources (where the source is a Markov chain, but whose state is not necessarily observable from its output), and to decode from Hidden Markov…

Information Theory · Computer Science 2018-10-05 Venkatesan Guruswami , Preetum Nakkiran , Madhu Sudan

This paper considers the problem of transmitting the difference of two jointly Gaussian sources over a two-user additive Gaussian noise multiple access channel (MAC). The goal is to recover this difference within an average mean squared…

Information Theory · Computer Science 2008-12-08 Rajiv Soundararajan , Sriram Vishwanath

This paper proves the separation between source-network coding and channel coding in networks of noisy, discrete, memoryless channels. We show that the set of achievable distortion matrices in delivering a family of dependent sources across…

Information Theory · Computer Science 2016-11-17 Shirin Jalali , Michelle Effros

This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-channel code rate, and demonstrates that joint source-channel code design brings considerable performance advantage over a separate one in the…

Information Theory · Computer Science 2014-02-05 Victoria Kostina , Sergio Verdú

A general lossless joint source-channel coding scheme based on linear codes is proposed and then analyzed in this paper. It is shown that a linear code with good joint spectrum can be used to establish limit-approaching joint source-channel…

Information Theory · Computer Science 2016-11-17 Shengtian Yang , Peiliang Qiu

We consider the problem of causal source coding and causal decoding of a Gauss--Markov source, where the decoder has causal access to a side-information signal. We define the information causal rate-distortion function with causal decoder…

Information Theory · Computer Science 2020-08-13 Omri Lev , Anatoly Khina

Reliable transmission of arbitrarily correlated sources over multiple-access relay channels (MARCs) and multiple-access broadcast relay channels (MABRCs) is considered. In MARCs, only the destination is interested in a reconstruction of the…

Information Theory · Computer Science 2012-07-04 Yonathan Murin , Ron Dabora , Deniz Gündüz

A fundamental property of codes, the second-order weight distribution, is proposed to solve the problems such as computing second moments of weight distributions of linear code ensembles. A series of results, parallel to those for weight…

Information Theory · Computer Science 2011-11-15 Shengtian Yang

Achievability and converse results for the lossy transmission of correlated sources over Shannon's two-way channels (TWCs) are presented. A joint source-channel coding theorem for independent sources and TWCs for which adaptation cannot…

Information Theory · Computer Science 2018-05-08 Jian-Jia Weng , Fady Alajaji , Tamás Linder

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

One open problem in source coding is to characterize the limits of representing losslessly a non-identity discrete function of the data encoded independently by the encoders of several correlated sources with memory. This paper investigates…

Information Theory · Computer Science 2013-06-26 Sheng Huang , Mikael Skoglund

In this article, the two filter formula is re-examined in the setting of partially observed Gauss--Markov models. It is traditionally formulated as a filter running backward in time, where the Gaussian density is parametrized in…

Methodology · Statistics 2025-03-03 Filip Tronarp

We consider a problem where a memoryless bi-variate Gaussian source is to be transmitted over an additive white Gaussian multiple-access channel with two transmitting terminals and one receiving terminal. The first transmitter only sees the…

Information Theory · Computer Science 2007-07-16 Amos Lapidoth , Stephan Tinguely

Through refined asymptotic analysis based on the normal approximation, we study how higher-order coding performance depends on the mean power as well as on finer statistics of the input power. We introduce a multifaceted power model in…

Information Theory · Computer Science 2026-05-13 Adeel Mahmood , Aaron B. Wagner

We study the two-user broadcast channel with degraded message sets and derive second-order achievability rate regions. Specifically, the channel noises are not necessarily Gaussian and we use spherical codebooks for both users. The weak…

Information Theory · Computer Science 2024-10-24 Zhuangfei Wu , Lin Bai , Jinpeng Xu , Lin Zhou , Mehul Motani

We study reliable transmission of arbitrarily correlated sources over multiple-access relay channels (MARCs) and multiple-access broadcast relay channels (MABRCs). In MARCs only the destination is interested in reconstructing the sources,…

Information Theory · Computer Science 2016-11-17 Yonathan Murin , Ron Dabora , Deniz Gündüz

We design a low complexity distributed compression scheme for computing arbitrary functions of sources with discrete alphabets. We use a helper-based method that extends the definition of the G{\'a}cs-K{\"o}rner-Witsenhausen (GKW) common…

Information Theory · Computer Science 2021-04-01 Derya Malak

We study the transmission of correlated sources over discrete memoryless (DM) multiple-access-relay channels (MARCs), in which both the relay and the destination have access to side information arbitrarily correlated with the sources. As…

Information Theory · Computer Science 2014-07-29 Yonathan Murin , Ron Dabora , Deniz Gündüz

Flow matching has emerged as a powerful generative modeling approach with flexible choices of source distribution. While Gaussian distributions are commonly used, the potential for better alternatives in high-dimensional data generation…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Junho Lee , Kwanseok Kim , Joonseok Lee
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