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Identification in quantum communication enables receivers to verify the presence of a message without decoding its entire content. While identification capacity has been explored for classical and finite-dimensional quantum channels, its…

Quantum Physics · Physics 2025-12-02 Zuhra Amiri , Janis Nötzel

This paper presents an achievability bound that evaluates the exact probability of error of an ensemble of random codes that are decoded by a minimum distance decoder. Compared to the state-of-the-art which demands exponential computation…

Information Theory · Computer Science 2023-05-17 Ioannis Papoutsidakis , Angela Doufexi , Robert J. Piechocki

We review recent results on the simulation of quantum channels, the reduction of adaptive protocols (teleportation stretching), and the derivation of converse bounds for quantum and private communication, as established in PLOB [Pirandola,…

We consider the discrete memoryless symmetric primitive relay channel, where, a source $X$ wants to send information to a destination $Y$ with the help of a relay $Z$ and the relay can communicate to the destination via an error-free…

Information Theory · Computer Science 2016-03-31 Xiugang Wu , Ayfer Ozgur , Liang-Liang Xie

We study communication systems over band-limited Additive White Gaussian Noise (AWGN) channels in which the transmitter output is constrained to be symmetric binary (bi-polar). In this work we improve the original Ozarov-Wyner-Ziv (OWZ)…

Information Theory · Computer Science 2021-10-07 Michael Peleg , Tomer Michaeli , Shlomo Shamai

In recent years, the derivation of nonasymptotic converse and achievability bounds on the maximum coding rate as a function of the error probability and blocklength has gained attention in the information theory literature. While these…

Information Theory · Computer Science 2020-09-25 Alejandro Lancho , Jöhan Ostman , Giuseppe Durisi , Tobias Koch , Gonzalo Vazquez-Vilar

In this paper, capacity bounds for the two-user Interference Channel (IC) with cooperative receivers via conferencing links of finite capacities is investigated. The capacity results known for this communication scenario are limited to a…

Information Theory · Computer Science 2015-12-17 Reza K. Farsani , Amir K. Khandani

We study encodings that give the best known thresholds for the non-zero capacity of quantum channels, i.e., the upper bound for correctable noise, using an entropic approach to calculation of the threshold values. Our results show that…

Quantum Physics · Physics 2009-02-22 Jesse Fern , K. Birgitta Whaley

We provide tight upper and lower bounds on the noise resilience of interactive communication over noisy channels with feedback. In this setting, we show that the maximal fraction of noise that any robust protocol can resist is 1/3.…

Data Structures and Algorithms · Computer Science 2015-01-06 Klim Efremenko , Ran Gelles , Bernhard Haeupler

In this paper, we study the achievable performance of dirty paper coding for the Gaussian broadcast channel (BC) with finite blocklength and we propose two different achievability bounds for this problem. We present the broadcast adaptation…

Information Theory · Computer Science 2026-02-20 Ayşe Ünsal , Jean-Marie Gorce

Generative models that maximize model likelihood have gained traction in many practical settings. Among them, perturbation based approaches underpin many strong likelihood estimation models, yet they often face slow convergence and limited…

Information Theory · Computer Science 2025-10-27 Yirong Shen , Lu Gan , Cong Ling

New non-asymptotic random coding theorems (with error probability $\epsilon$ and finite block length $n$) based on Gallager parity check ensemble and Shannon random code ensemble with a fixed codeword type are established for discrete input…

Information Theory · Computer Science 2013-03-05 En-hui Yang , Jin Meng

This paper studies an $n$-dimensional additive Gaussian noise channel with a peak-power-constrained input. It is well known that, in this case, when $n=1$ the capacity-achieving input distribution is discrete with finitely many mass points,…

Information Theory · Computer Science 2019-11-18 Alex Dytso , Semih Yagli , H. Vincent Poor , Shlomo Shamai

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

The rate regions of many variations of the standard and wire-tap channels have been thoroughly explored. Secrecy capacity characterizes the loss of rate required to ensure that the adversary gains no information about the transmissions.…

Information Theory · Computer Science 2018-06-27 Jake Perazzone , Eric Graves , Paul Yu , Rick Blum

We derive bounds on the asymptotic density of parity-check matrices and the achievable rates of binary linear block codes transmitted over memoryless binary-input output-symmetric (MBIOS) channels. The lower bounds on the density of…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

In this work, message authentication over noisy channels is studied. The model developed in this paper is the authentication theory counterpart of Wyner's wiretap channel model. Two types of opponent attacks, namely impersonation attacks…

Information Theory · Computer Science 2008-02-20 Lifeng Lai , Hesham El Gamal , H. Vincent Poor

We study the amount of randomness needed for an input process to approximate a given output distribution of a channel in the $E_{\gamma}$ distance. A general one-shot achievability bound for the precision of such an approximation is…

Information Theory · Computer Science 2015-12-01 Jingbo Liu , Paul Cuff , Sergio Verdú

In this paper, we consider the group testing problem with adaptive test designs and noisy outcomes. We propose a computationally efficient four-stage procedure with components including random binning, identification of bins containing…

Computation · Statistics 2019-11-11 Jonathan Scarlett

We consider a standard distributed optimisation setting where $N$ machines, each holding a $d$-dimensional function $f_i$, aim to jointly minimise the sum of the functions $\sum_{i = 1}^N f_i (x)$. This problem arises naturally in…

Machine Learning · Computer Science 2021-12-08 Dan Alistarh , Janne H. Korhonen
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