On adversarial joint source channel coding

Arya Mazumdar, Ankit Singh Rawat

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In a joint source-channel coding scheme, a single mapping is used to perform both the tasks of data compression and channel coding in a combined way, rather than performing them separately. Usually for simple iid sources and channels, separation of the tasks is information theoretically optimal. In an adversarial joint source-channel coding scenario, instead of a stochastic channel, an adversary introduces a set of bounded number of errors/erasures. It has been shown recently that, even in the simplest cases of such adversarial models, separation is suboptimal and characterizing the fundamental limits is difficult. In this paper, we study several properties of such adversarial joint source-channel schemes. We show optimality of separation in some situations, provide simple joint schemes that beat separation in others, and give new bounds on the rate of such coding.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781467377041
StatePublished - Sep 28 2015
EventIEEE International Symposium on Information Theory, ISIT 2015 - Hong Kong, Hong Kong
Duration: Jun 14 2015Jun 19 2015

Publication series

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


OtherIEEE International Symposium on Information Theory, ISIT 2015
CountryHong Kong
CityHong Kong

Bibliographical note

Funding Information:
This work was supported by NSF grant CCF 1318093.

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