On Decentralized Detection with Partial Information Sharing among Sensors
Author(s)
Kreidl, Olivier Patrick; Tsitsiklis, John N.; Zoumpoulis, Spyridon Ilias
DownloadTsitsiklis_On decentralized.pdf (557.7Kb)
OPEN_ACCESS_POLICY
Open Access Policy
Creative Commons Attribution-Noncommercial-Share Alike
Terms of use
Metadata
Show full item recordAbstract
We study a decentralized detection architecture in which each of a set of sensors transmits a highly compressed summary of its observations (a binary message) to a fusion center, which then decides on one of two alternative hypotheses. In contrast to the star (or “parallel”) architecture considered in most of the literature, we allow a subset of the sensors to both transmit their messages to the fusion center and to also broadcast them to the remaining sensors. We focus on the following architectural question: Is there a significant performance improvement when we allow such a message broadcast? We consider the error exponent (asymptotically, in the limit of a large number of sensors) for the Neyman-Pearson formulation of the detection problem. We prove that the sharing of messages does not improve the optimal error exponent.
Date issued
2011-04Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Laboratory for Information and Decision SystemsJournal
IEEE transactions on signal processing
Publisher
Institute of Electrical and Electronics Engineers
Citation
Kreidl, O.P., J.N. Tsitsiklis, and S.I. Zoumpoulis. “On Decentralized Detection With Partial Information Sharing Among Sensors.” Signal Processing, IEEE Transactions On 59.4 (2011) : 1759-1765. Copyright (c) 2010 IEEE
Version: Author's final manuscript
ISSN
1053-587X