Distributed Hypothesis Testing over Noisy Broadcast Channels

This paper studies binary hypothesis testing with a single sensor that communicates with two decision centers over a memoryless broadcast channel. The main focus lies on the tradeoff between the two type-II error exponents achievable at the two decision centers. In our proposed scheme, we can partia...

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Main Authors: Sadaf Salehkalaibar, Michèle Wigger
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/12/7/268
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spelling doaj-fb65bcbbbbb74c3689209d4ba694b5f32021-07-23T13:47:09ZengMDPI AGInformation2078-24892021-06-011226826810.3390/info12070268Distributed Hypothesis Testing over Noisy Broadcast ChannelsSadaf Salehkalaibar0Michèle Wigger1Department of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 1433957131, IranLTCI, Telecom Paris, IP Paris, 91120 Paris, FranceThis paper studies binary hypothesis testing with a single sensor that communicates with two decision centers over a memoryless broadcast channel. The main focus lies on the tradeoff between the two type-II error exponents achievable at the two decision centers. In our proposed scheme, we can partially mitigate this tradeoff when the transmitter has a probability larger than <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></semantics></math></inline-formula> to distinguish the alternate hypotheses at the decision centers, i.e., the hypotheses under which the decision centers wish to maximize their error exponents. In the cases where these hypotheses cannot be distinguished at the transmitter (because both decision centers have the same alternative hypothesis or because the transmitter’s observations have the same marginal distribution under both hypotheses), our scheme shows an important tradeoff between the two exponents. The results in this paper thus reinforce the previous conclusions drawn for a setup where communication is over a common noiseless link. Compared to such a noiseless scenario, here, however, we observe that even when the transmitter can distinguish the two hypotheses, a small exponent tradeoff can persist, simply because the noise in the channel prevents the transmitter to perfectly describe its guess of the hypothesis to the two decision centers.https://www.mdpi.com/2078-2489/12/7/268hypothesis testingbroadcast channelerror exponents
collection DOAJ
language English
format Article
sources DOAJ
author Sadaf Salehkalaibar
Michèle Wigger
spellingShingle Sadaf Salehkalaibar
Michèle Wigger
Distributed Hypothesis Testing over Noisy Broadcast Channels
Information
hypothesis testing
broadcast channel
error exponents
author_facet Sadaf Salehkalaibar
Michèle Wigger
author_sort Sadaf Salehkalaibar
title Distributed Hypothesis Testing over Noisy Broadcast Channels
title_short Distributed Hypothesis Testing over Noisy Broadcast Channels
title_full Distributed Hypothesis Testing over Noisy Broadcast Channels
title_fullStr Distributed Hypothesis Testing over Noisy Broadcast Channels
title_full_unstemmed Distributed Hypothesis Testing over Noisy Broadcast Channels
title_sort distributed hypothesis testing over noisy broadcast channels
publisher MDPI AG
series Information
issn 2078-2489
publishDate 2021-06-01
description This paper studies binary hypothesis testing with a single sensor that communicates with two decision centers over a memoryless broadcast channel. The main focus lies on the tradeoff between the two type-II error exponents achievable at the two decision centers. In our proposed scheme, we can partially mitigate this tradeoff when the transmitter has a probability larger than <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></semantics></math></inline-formula> to distinguish the alternate hypotheses at the decision centers, i.e., the hypotheses under which the decision centers wish to maximize their error exponents. In the cases where these hypotheses cannot be distinguished at the transmitter (because both decision centers have the same alternative hypothesis or because the transmitter’s observations have the same marginal distribution under both hypotheses), our scheme shows an important tradeoff between the two exponents. The results in this paper thus reinforce the previous conclusions drawn for a setup where communication is over a common noiseless link. Compared to such a noiseless scenario, here, however, we observe that even when the transmitter can distinguish the two hypotheses, a small exponent tradeoff can persist, simply because the noise in the channel prevents the transmitter to perfectly describe its guess of the hypothesis to the two decision centers.
topic hypothesis testing
broadcast channel
error exponents
url https://www.mdpi.com/2078-2489/12/7/268
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