A Lower and Upper Bound on the Epsilon-Uniform Common Randomness Capacity

Rami Ezzine, Moritz Wiese, Christian Deppe, Holger Boche

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider a standard two-source model for uniform common randomness (UCR) generation, in which Alice and Bob observe independent and identically distributed (i. i. d.) samples of a correlated finite source and where Alice is allowed to send information to Bob over an arbitrary single-user channel. We study the ?-UCR capacity for the proposed model, defined as the maximum common randomness rate one can achieve such that the probability that Alice and Bob do not agree on a common uniform or nearly uniform random variable does not exceed ?. We establish a lower and an upper bound on the ?-UCR capacity using the bounds on the ?-transmission capacity proved by Verdú and Han for arbitrary point-to-point channels.A detailed version with all proofs, explanations and more discussions can be found in [1].

Original languageEnglish
Title of host publication2023 IEEE International Symposium on Information Theory, ISIT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages240-245
Number of pages6
ISBN (Electronic)9781665475549
DOIs
StatePublished - 2023
Event2023 IEEE International Symposium on Information Theory, ISIT 2023 - Taipei, Taiwan, Province of China
Duration: 25 Jun 202330 Jun 2023

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2023-June
ISSN (Print)2157-8095

Conference

Conference2023 IEEE International Symposium on Information Theory, ISIT 2023
Country/TerritoryTaiwan, Province of China
CityTaipei
Period25/06/2330/06/23

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