On the relationship between edge removal and strong converses

Document Type

Conference Proceeding

Publication Date

8-10-2016

Abstract

This paper explores the relationship between two ideas in network information theory: edge removal and strong converses. Edge removal properties state that if an edge of small capacity is removed from a network, the capacity region does not change too much. Strong converses state that, for rates outside the capacity region, the probability of error converges to 1. Various notions of edge removal and strong converse are defined, depending on how edge capacity and residual error probability scale with blocklength, and relations between them are proved. In particular, each class of strong converse implies a specific class of edge removal. The opposite direction is proved for deterministic networks, and some discussion is given for the noisy case.

Identifier

84985945074 (Scopus)

ISBN

[9781509018062]

Publication Title

IEEE International Symposium on Information Theory Proceedings

External Full Text Location

https://doi.org/10.1109/ISIT.2016.7541605

ISSN

21578095

First Page

1779

Last Page

1783

Volume

2016-August

Grant

1453718

Fund Ref

National Science Foundation

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