How dense should a sensor network be for detection applications?

Jean François Chamberland, Venugopal V. Veeravalli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A binary decentralized detection problem is studied in which a collection of wireless sensor nodes provides relevant information about their environment to a fusion center. The observations at the nodes are samples of a finite state Markov process under each hypothesis. The nodes transmit their data to a fusion center over a multiple access channel. Upon reception of the information, the fusion center selects one of the two possible hypotheses. It is assumed that the sensor system is constrained by the capacity of the multiple access channel over which the sensor nodes are transmitting. Thus, as the node density increases, the sensor observations get more correlated, and, furthermore, fewer bits can be transmitted by each sensor node. A framework is presented in this paper for deriving design guidelines relating sensor density to system performance under a total communication constraint. The framework is based on large deviation theory applied to the asymptotic regime where the number of sensor nodes is large. This framework is applied to a specific example to compare the gains offered by having a higher node density with the benefits of getting detailed information from each sensor.

Original languageEnglish (US)
Title of host publication2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions
PublisherInstitute of Electrical and Electronics Engineers Inc.
PagesV1049-V1052
ISBN (Print)0780388747, 9780780388741
DOIs
StatePublished - Jan 1 2005
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: Mar 18 2005Mar 23 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeV
ISSN (Print)1520-6149

Other

Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
CountryUnited States
CityPhiladelphia, PA
Period3/18/053/23/05

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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