Decentralized detection in sensor network architectures with feedback

We investigate a decentralized detection problem in which a set of sensors transmit a summary of their observations to a fusion center, which then decides which one of two hypotheses is true. The focus is on determining the value of feedback in improving performance in the regime of asymptotically many sensors. We formulate the decentralized detection problem for different network configurations of interest under both the Neyman-Pearson and the Bayesian criteria. In a configuration with feedback, the fusion center would make a preliminary decision which it would pass on back to the local sensors; a related configuration, the daisy chain, is introduced: the first fusion center passes the information from a first set of sensors on to a second set of sensors and a second fusion center. Under the Neyman-Pearson criterion, we provide both an empirical study and theoretical results. The empirical study assumes scalar linear Gaussian binary sensors and analyzes asymptotic performance as the signal-to-noise ratio of the measurements grows higher, to show that the value of feeding the preliminary decision back to decision makers is asymptotically negligible. This motivates two theoretical results: first, in the asymptotic regime (as the number of sensors tends to infinity), the performance of the "daisy chain" matches the performance of a parallel configuration with twice as many sensors as the classical scheme; second, it is optimal (in terms of the exponent of the error probability) to constrain all decision rules at the first and second stage of the "daisy chain" to be equal.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2009

Author dc:creator

• Zoumpoulis, Spyridon Ilias

Advisor dc:contributor.advisor

• John N. Tsitsiklis and O. Patrick Kreidl.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/52775

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/52775