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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

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

This work contains two main contributions concerning the asymmetric broadcast channel. The first is an analysis of the exact random coding error exponents for both users, and the second is the derivation of universal decoders for both…

Information Theory · Computer Science 2017-02-28 Ran Averbuch , Neri Merhav

Incorporating sample efficiency, by requiring the number of states consumed by broadcasting does not exceed that of a naive prepare-and-distribute strategy, gives rise to the no practical quantum broadcasting theorem. To navigate this…

Quantum Physics · Physics 2026-03-20 Ximing Wang , Yunlong Xiao

We propose two coding schemes for the two-receiver discrete memoryless broadcast channel (BC) with rate-limited feedback from one or both receivers. They improve over the nofeedback capacity region for a large class of channels, including…

Information Theory · Computer Science 2016-02-19 Youlong Wu , Michèle Wigger

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

In [1], it is shown that the simultaneous identification capacity region for the discrete, memoryless, classical-quantum multiple access channel is equal to the transmission capacity region for codes using a deterministic encoding scheme.…

Quantum Physics · Physics 2019-03-11 Stephen Diadamo , Holger Boche

We develop a low-complexity polar coding scheme for the discrete memoryless broadcast channel with confidential messages under strong secrecy and randomness constraints. Our scheme extends previous work by using an optimal rate of uniform…

Information Theory · Computer Science 2016-03-08 Remi A. Chou , Matthieu R. Bloch

Holevo, Schumacher, and Westmoreland's coding theorem guarantees the existence of codes that are capacity-achieving for the task of sending classical data over a channel with classical inputs and quantum outputs. Although they demonstrated…

Quantum Physics · Physics 2013-01-21 Mark M. Wilde , Saikat Guha

The capacity of a channel can usually be characterized as a maximization of certain entropic quantities. From a practical point of view it is of primary interest to not only compute the capacity value, but also to find the corresponding…

Information Theory · Computer Science 2023-05-25 Holger Boche , Rafael F. Schaefer , H. Vincent Poor

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 study the problem of transmission of information over classical and classical-quantum channels in the one-shot regime where the underlying codes are constrained to be group codes. In the achievability part, we introduce a new input…

Information Theory · Computer Science 2024-06-21 James Chin-Jen Pang , Sandeep Pradhan , Hessam Mahdavifar

The quantum capacity of a memoryless channel is often used as a single figure of merit to characterize its ability to transmit quantum information coherently. The capacity determines the maximal rate at which we can code reliably over…

Quantum Physics · Physics 2016-05-10 Marco Tomamichel , Mario Berta , Joseph M. Renes

We focus on designing error-correcting codes for the symmetric Gaussian broadcast channel with feedback. Feedback not only expands the capacity region of the broadcast channel but also enhances transmission reliability. In this work, we…

Information Theory · Computer Science 2025-03-04 Yingyao Zhou , Natasha Devroye

We investigate the maximum coding rate for a given average blocklength and error probability over a K-user discrete memoryless broadcast channel for the scenario where a common message is transmitted using variable-length stop-feedback…

Information Theory · Computer Science 2018-09-03 Kasper Fløe Trillingsgaard , Wei Yang , Giuseppe Durisi , Petar Popovski

We consider the scenario of classical communication over a finite-dimensional quantum channel with memory using a separable-state input ensemble and local output measurements. We propose algorithms for estimating the information rate of…

Information Theory · Computer Science 2024-10-30 Michael X. Cao , Pascal O. Vontobel

This paper shows that the capacity region of the continuous-time Poisson broadcast channel is achieved via superposition coding for most channel parameter values. Interestingly, the channel in some subset of these parameter values does not…

Information Theory · Computer Science 2015-08-28 Hyeji Kim , Benjamin Nachman , Abbas El Gamal

The index coding problem is studied from an interference alignment perspective, providing new results as well as new insights into, and generalizations of, previously known results. An equivalence is established between multiple unicast…

Information Theory · Computer Science 2012-05-08 Hamed Maleki , Viveck R. Cadambe , Syed A. Jafar

We consider the joint source-channel coding problem of sending a Gaussian source on a K-user Gaussian broadcast channel with bandwidth mismatch. A new outer bound to the achievable distortion region is derived using the technique of…

Information Theory · Computer Science 2010-11-22 Chao Tian , Suhas Diggavi , Shlomo Shamai

Channel simulation algorithms can efficiently encode random samples from a prescribed target distribution $Q$ and find applications in machine learning-based lossy data compression. However, algorithms that encode exact samples usually have…

Information Theory · Computer Science 2024-05-16 Gergely Flamich , Lennie Wells