Strong Converses using Change of Measure and Asymptotic Markov Chains

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Abstract

The main contribution of this paper is a strong converse result for K-hop distributed hypothesis testing against independence with multiple (intermediate) decision centers under a Markov condition. Our result shows that the set of type-II error exponents that can simultaneously be achieved at all the terminals does not depend on the maximum permissible type-I error probabilities. Our strong converse proof is based on a change of measure argument and on the asymptotic proof of specific Markov chains. This proof method seems to be useful also in other applications, and is appealing because it does not require resorting to variational characterizations or blowing-up methods as in previous related proofs.

Original languageEnglish
Title of host publication2022 IEEE Information Theory Workshop, ITW 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages535-540
Number of pages6
ISBN (Electronic)9781665483414
DOIs
Publication statusPublished - 1 Jan 2022
Event2022 IEEE Information Theory Workshop, ITW 2022 - Mumbai, India
Duration: 1 Nov 20229 Nov 2022

Publication series

Name2022 IEEE Information Theory Workshop, ITW 2022

Conference

Conference2022 IEEE Information Theory Workshop, ITW 2022
Country/TerritoryIndia
CityMumbai
Period1/11/229/11/22

Keywords

  • K hops
  • Strong converse
  • change of measure
  • hypothesis testing

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