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For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes. However, this decomposition can fall…

Machine Learning · Computer Science 2019-05-15 Kristy Choi , Kedar Tatwawadi , Aditya Grover , Tsachy Weissman , Stefano Ermon

This work develops a rate-distortion-based approach to stochastic Chase decoding of algebraic codes over binary memoryless symmetric (BMS) channels, replacing the heuristics traditionally used to determine flip probabilities with…

Information Theory · Computer Science 2026-05-20 Amit Berman , Ariel Doubchak , Uri Erez , Tal Philosof , Ilya Shapir

This paper considers lossy source coding of $n$-dimensional memoryless sources and shows an explicit approximation to the minimum source coding rate required to sustain the probability of exceeding distortion $d$ no greater than $\epsilon$,…

Information Theory · Computer Science 2017-02-28 Victoria Kostina

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

In communication through asymmetric channels the capacity-achieving input distribution is not uniform in general. Homophonic coding is a framework to invertibly convert a (usually uniform) message into a sequence with some target…

Information Theory · Computer Science 2017-06-30 Junya Honda , Hirosuke Yamamoto

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

We consider the discrete memoryless asymmetric broadcast channels. We prove that the error probability of decoding tends to one exponentially for rates outside the capacity region and derive an explicit lower bound of this exponent…

Information Theory · Computer Science 2020-08-11 Yasutada Oohama

Deep joint source-channel coding (DeepJSCC) has emerged as a powerful paradigm for end-to-end semantic communications, jointly learning to compress and protect task-relevant features over noisy channels. However, existing DeepJSCC schemes…

We study the amount of reliable information that can be stored in a DNA-based storage system with noisy sequencing, where each codeword is composed of short DNA molecules. We analyze a concatenated coding scheme, where the outer code is…

Information Theory · Computer Science 2026-05-19 Ran Tamir , Nir Weinberger , Albert Guillén i Fàbregas

The reliability function of memoryless channels with noiseless feedback and variable-length coding has been found to be a linear function of the average rate in the classic work of Burnashev. In this work we consider unifilar channels with…

Information Theory · Computer Science 2017-07-11 Achilleas Anastasopoulos , Jui Wu

This paper examines the maximum code rate achievable by a data-driven communication system over some unknown discrete memoryless channel in the finite blocklength regime. A class of channel codes, called learning-based channel codes, is…

Information Theory · Computer Science 2023-07-18 Neil Irwin Bernardo , Jingge Zhu , Jamie Evans

Recent works have shown that modern machine learning techniques can provide an alternative approach to the long-standing joint source-channel coding (JSCC) problem. Very promising initial results, superior to popular digital schemes that…

Image and Video Processing · Electrical Eng. & Systems 2022-06-17 Tze-Yang Tung , David Burth Kurka , Mikolaj Jankowski , Deniz Gunduz

This paper studies low-latency streaming codes for the multi-hop network. The source is transmitting a sequence of messages (streaming messages) to a destination through a chain of relays where each hop is subject to packet erasures. Every…

Information Theory · Computer Science 2020-06-11 Elad Domanovitz , Ashish Khisti , Wai-Tian Tan , Xiaoqing Zhu , John Apostolopoulos

The information bottleneck channel (or the oblivious relay channel) concerns a channel coding setting where the decoder does not directly observe the channel output. Rather, the channel output is relayed to the decoder by an oblivious relay…

Information Theory · Computer Science 2026-04-28 Yanxiao Liu , Sepehr Heidari Advary , Cheuk Ting Li

The reliability function of memoryless channels with noiseless feedback and variable-length coding has been found to be a linear function of the average rate in the classic work of Burnashev. In this work we consider unifilar channels with…

Information Theory · Computer Science 2017-07-13 Achilleas Anastasopoulos , Jui Wu

We propose an iterative method for approximately computing the capacity of discrete memoryless channels, possibly under additional constraints on the input distribution. Based on duality of convex programming, we derive explicit upper and…

Information Theory · Computer Science 2015-04-06 Tobias Sutter , David Sutter , Peyman Mohajerin Esfahani , John Lygeros

In this paper, we propose a novel code for transmitting a sequence of $n$ message bits in real time over a discrete-memoryless channel (DMC) with noiseless feedback, where the message bits stream into the encoder one by one at random time…

Information Theory · Computer Science 2021-05-10 Nian Guo , Victoria Kostina

Low-density parity-check (LDPC) codes with the parity-based approach for distributed joint source channel coding (DJSCC) with decoder side information is described in this paper. The parity-based approach is theoretical limit achievable.…

Information Theory · Computer Science 2014-04-10 Feng Cen

This paper is concerned with distributed stochastic multi-agent constrained optimization problem over time-varying network with a class of communication noise. This paper considers the problem in composite optimization setting which is more…

Optimization and Control · Mathematics 2022-12-20 Zhan Yu , Daniel W. C. Ho , Deming Yuan , Jie Liu

We study the problem of exact support recovery for high-dimensional sparse linear regression under independent Gaussian design when the signals are weak, rare, and possibly heterogeneous. Under a suitable scaling of the sample size and…

Statistics Theory · Mathematics 2023-07-19 Saptarshi Roy , Ambuj Tewari , Ziwei Zhu
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