Identification Capacity of Correlation-Assisted Discrete Memoryless Channels: Analytical Properties and Representations

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

  • Holger Boche - , Technical University of Munich, Munich Center for Quantum Science and Technology (MCQST) (Author)
  • Rafael F. Schaefer - , Technical University of Berlin (Author)
  • H. Vincent Poor - , Princeton University (Author)

Abstract

The problem of identification is considered, in which it is of interest for the receiver to decide only whether a certain message has been sent or not. Identification via correlation-assisted discrete memoryless channels is studied, where the transmitter and the receiver further have access to correlated source observations. Analytical properties and representations of the corresponding identification capacity are studied. In this paper, it is shown that the identification capacity cannot be represented as a maximization of a single-letter (or multi-letter with fixed length) expression of entropic quantities. Further, it is shown that the identification capacity is not Banach-Mazur computable and therewith not Turing computable. Consequently, there is no algorithm that can simulate or compute the identification capacity, even if there are no limitations on computational complexity and computing power.

Details

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages470-474
Number of pages5
ISBN (electronic)978-1-5386-9291-2
Publication statusPublished - Jul 2019
Peer-reviewedYes
Externally publishedYes

Publication series

SeriesIEEE International Symposium on Information Theory
Volume2019-July
ISSN2157-8095

Conference

Title2019 IEEE International Symposium on Information Theory, ISIT 2019
Duration7 - 12 July 2019
CityParis
CountryFrance

External IDs

ORCID /0000-0002-1702-9075/work/165878304