Scalable Source Coding With Causal Side Information and a Causal Helper

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Abstract

We consider a successive refinement source coding model in which each receiver observes its own side-information causally and is required to form its reconstruction in a causal manner. Furthermore, a one way conference link of given capacity allows Decoder 1 - the helper - to send causal descriptions of what it has received so far to Decoder 2. A complete characterization of the rate distortion region is provided. The optimal helper is a scalar quantizer of its side-information which depends on the corresponding first-stage message symbol sent by the encoder. Thus, the imposition of the causality constraint on the side informations as well as on the helper's conference both renders the problem tractable and simplifies the optimal code.

Original languageEnglish
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2405-2409
Number of pages5
ISBN (Electronic)9781728164328
DOIs
StatePublished - Jun 2020
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: 21 Jul 202026 Jul 2020

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2020-June
ISSN (Print)2157-8095

Conference

Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
Country/TerritoryUnited States
CityLos Angeles
Period21/07/2026/07/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

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