Distributed hypothesis testing over noisy channels

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Title: Distributed hypothesis testing over noisy channels
Authors: Sreekumar, S
Gunduz, D
Item Type: Conference Paper
Abstract: A distributed binary hypothesis testing problem, in which multiple observers transmit their observations to a detector over noisy channels, is studied. Together with its own observations, the goal of the detector is to decide between two hypotheses for the joint distribution of the data. Single-letter upper and lower bounds on the optimal type 2 error exponent (T2-EE), when the type 1 error probability vanishes with the block-length are obtained. These bounds coincide and characterize the optimal T2-EE when only a single helper is involved. Our result shows that the optimal T2-EE depends on the marginal distributions of the data and the channels rather than their joint distribution. However, an operational separation between HT and channel coding does not hold, and the optimal T2-EE is achieved by generating channel inputs correlated with observed data.
Issue Date: 25-Jun-2017
Date of Acceptance: 1-Apr-2017
URI: http://hdl.handle.net/10044/1/46228
Publisher: IEEE
Copyright Statement: This paper is embargoed until publication.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 677854
Conference Name: 2017 IEEE International Symposium on Information Theory (ISIT)
Publication Status: Accepted
Start Date: 2017-06-25
Finish Date: 2017-06-30
Conference Place: Aachen, Germany
Embargo Date: publication subject to indefinite embargo
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering

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