Distributed hypothesis testing over discrete memoryless channels
File(s)
Accepted version
Author(s)
Sreekumar, Sreejith
Gunduz, Deniz
Type
Journal Article
Abstract
A distributed binary hypothesis testing (HT) problem involving two parties, one referred to as the observer and the other as the detector is studied. The observer observes a discrete memoryless source (DMS) and communicates its observations to the detector over a discrete memoryless channel (DMC). The detector observes another DMS correlated with that at the observer, and performs a binary HT on the joint distribution of the two DMS’s using its own observed data and the information received from the observer. The trade-off between the type I error probability and the type II error-exponent of the HT is explored. Single-letter lower bounds on the optimal type II errorexponent are obtained by using two different coding schemes, a separate HT and channel coding scheme and a joint HT and channel coding scheme based on hybrid coding for the matched bandwidth case. Exact single-letter characterization of the same is established for the special case of testing against conditional independence, and it is shown to be achieved by the separate HT and channel coding scheme. An example is provided where the joint scheme achieves a strictly better performance than the separation based scheme.
Date Issued
2019-11-15
Date Acceptance
2019-11-07
Citation
IEEE Transactions on Information Theory, 2019, 66 (4), pp.2044-2066
ISSN
0018-9448
Publisher
Institute of Electrical and Electronics Engineers
Start Page
2044
End Page
2066
Journal / Book Title
IEEE Transactions on Information Theory
Volume
66
Issue
4
Copyright Statement
© 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Sponsor
Commission of the European Communities
Identifier
https://ieeexplore.ieee.org/document/8902074
Grant Number
677854
Subjects
Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Computer Science
Engineering
Distributed hypothesis testing
noisy channel
error-exponents
reliability
statistical inference
separate scheme
unequal error protection
joint scheme
hybrid coding
STATISTICAL-INFERENCE
0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
1005 Communications Technologies
Networking & Telecommunications
Publication Status
Published
Date Publish Online
2019-11-15