The value of feedback for decentralized detection in large sensor networks

We consider the decentralized binary hypothesis testing problem in networks with feedback, where some or all of the sensors have access to compressed summaries of other sensors' observations. We study certain two-message feedback architectures, in which every sensor sends two messages to a fusi...

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Main Authors: Tay, Wee Peng, Tsitsiklis, John N.
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers (IEEE) 2012
Online Access:http://hdl.handle.net/1721.1/73559
https://orcid.org/0000-0003-2658-8239
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author Tay, Wee Peng
Tsitsiklis, John N.
author2 Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
author_facet Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Tay, Wee Peng
Tsitsiklis, John N.
author_sort Tay, Wee Peng
collection MIT
description We consider the decentralized binary hypothesis testing problem in networks with feedback, where some or all of the sensors have access to compressed summaries of other sensors' observations. We study certain two-message feedback architectures, in which every sensor sends two messages to a fusion center, with the second message based on full or partial knowledge of the first messages of the other sensors. Under either a Neyman-Pearson or a Bayesian formulation, we show that the asymptotically optimal (in the limit of a large number of sensors) detection performance (as quantified by error exponents) does not benefit from the feedback messages.
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spelling mit-1721.1/735592022-10-01T07:39:34Z The value of feedback for decentralized detection in large sensor networks Tay, Wee Peng Tsitsiklis, John N. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Laboratory for Information and Decision Systems Tsitsiklis, John N. We consider the decentralized binary hypothesis testing problem in networks with feedback, where some or all of the sensors have access to compressed summaries of other sensors' observations. We study certain two-message feedback architectures, in which every sensor sends two messages to a fusion center, with the second message based on full or partial knowledge of the first messages of the other sensors. Under either a Neyman-Pearson or a Bayesian formulation, we show that the asymptotically optimal (in the limit of a large number of sensors) detection performance (as quantified by error exponents) does not benefit from the feedback messages. 2012-10-03T13:59:05Z 2012-10-03T13:59:05Z 2011-04 2011-02 Article http://purl.org/eprint/type/ConferencePaper 978-1-4244-9867-3 978-1-4244-9868-0 http://hdl.handle.net/1721.1/73559 Tay, Wee Peng, and John N. Tsitsiklis. “The Value of Feedback for Decentralized Detection in Large Sensor Networks.” 6th International Symposium on Wireless and Pervasive Computing (ISWPC), 2011. 1–6. https://orcid.org/0000-0003-2658-8239 en_US http://dx.doi.org/10.1109/ISWPC.2011.5751320 Proceedings of the 6th International Symposium on Wireless and Pervasive Computing (ISWPC), 2011 Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT web domain
spellingShingle Tay, Wee Peng
Tsitsiklis, John N.
The value of feedback for decentralized detection in large sensor networks
title The value of feedback for decentralized detection in large sensor networks
title_full The value of feedback for decentralized detection in large sensor networks
title_fullStr The value of feedback for decentralized detection in large sensor networks
title_full_unstemmed The value of feedback for decentralized detection in large sensor networks
title_short The value of feedback for decentralized detection in large sensor networks
title_sort value of feedback for decentralized detection in large sensor networks
url http://hdl.handle.net/1721.1/73559
https://orcid.org/0000-0003-2658-8239
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