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Multi-terminal Strong Coordination with Degraded Source Observations
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0003-4237-6949
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-0036-9049
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-7926-5081
2024 (English)In: 2024 IEEE INFORMATION THEORY WORKSHOP, ITW 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024, p. 103-108Conference paper, Published paper (Refereed)
Abstract [en]

We investigate the problem of multi-terminal strong coordination over a network of noiseless links with degraded source observations. In this setup, independent and identically distributed (i.i.d.) copies of correlated sources are observed by two transmitters, with one of the source observations being common while the other one is private. The transmitters communicate their source descriptions over noiseless links to the receiver, which must produce approximately i.i.d. copies of an output random variable jointly distributed with the two sources. This is aided by the presence of common randomness shared between all three parties. The communication and common randomness rate tuples which permit such channel simulation are of interest. We derive a complete characterization for this multi-terminal strong coordination problem. It is observed that the optimal scheme is based on a superposition structure, where the common source description forms the base layer and the private source description forms the top layer.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. p. 103-108
Series
Information Theory Workshop, ISSN 2475-420X
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-362935DOI: 10.1109/ITW61385.2024.10806964ISI: 001433908800018Scopus ID: 2-s2.0-85211820950OAI: oai:DiVA.org:kth-362935DiVA, id: diva2:1955419
Conference
2024 Information Theory Workshop, NOV 24-28, 2024, Shenzhen, PEOPLES R CHINA
Note

Part of ISBN 979-8-3503-4894-1, 979-8-3503-4893-4

QC 20250430

Available from: 2025-04-30 Created: 2025-04-30 Last updated: 2025-06-03Bibliographically approved

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Ramachandran, ViswanathanOechtering, Tobias J.Skoglund, Mikael

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