Average Error Probability in Wireless Sensor Networks With Imperfect Sensing and Communication for Different Decision Rules

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dc.contributor.authorJuliano Nardelli, Pedro Henrique
dc.contributor.authorRamezanipour, Iran
dc.contributor.authorAlves, Hirley
dc.contributor.authorLima, Carlos H. M. de [UNESP]
dc.contributor.authorLatva-Aho, Matti
dc.contributor.institutionUniv Oulu
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-11-26T15:29:17Z
dc.date.available2018-11-26T15:29:17Z
dc.date.issued2016-05-15
dc.description.abstractThis paper presents a framework to evaluate the probability that a decision error event occurs in wireless sensor networks, including sensing and communication errors. We consider a scenario where sensors need to identify whether a given event has occurred based on its periodic, noisy, and observations of a given signal. Such information about the signal needs to be sent to a fusion center that decides about the actual state at that specific observation time. The communication links-singleor multi-hop-are modeled as binary symmetric channels, which may have different error probabilities. The decision at the fusion center is based on OR, AND, K-OUT-OF-N, and MAJORITY Boolean operations on the received signals associated to individual sensor observations. We derive closed-form equations for the average decision error probability as a function of the system parameters (e.g., number of sensors and hops) and the input signal characterization. Our analyses show the best decision rule is closely related to the frequency that the observed events occur and the number of sensors. In our numerical example, we show that the AND rule outperforms MAJORITY if such an event is rare and there is only a handful number of sensors. Conversely, if there are a large number of sensors or more evenly distributed event occurrences, the MAJORITY is the best choice. We further show that, while the error probability using the MAJORITY rule asymptotically goes to 0 with increasing number of sensors, it is also more susceptible to higher channel error probabilities.en
dc.description.affiliationUniv Oulu, Ctr Wireless Commun, Oulu 90014, Finland
dc.description.affiliationSao Paulo State Univ, BR-15054000 Sao Paulo, Brazil
dc.description.affiliationUnespSao Paulo State Univ, BR-15054000 Sao Paulo, Brazil
dc.description.sponsorshipSuomen Akatemia within the Strategic Research Council through the Aka BC-DC Project
dc.description.sponsorshipLuonnontieteiden ja Tekniikan Tutkimuksen Toimikunta
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipIdSuomen Akatemia within the Strategic Research Council through the Aka BC-DC Project: 292854
dc.description.sponsorshipIdLuonnontieteiden ja Tekniikan Tutkimuksen Toimikunta: 271150
dc.description.sponsorshipIdCNPq: 490235/2012-3
dc.format.extent3948-3957
dc.identifierhttp://dx.doi.org/10.1109/JSEN.2016.2536148
dc.identifier.citationIeee Sensors Journal. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 10, p. 3948-3957, 2016.
dc.identifier.doi10.1109/JSEN.2016.2536148
dc.identifier.fileWOS000374239600074.pdf
dc.identifier.issn1530-437X
dc.identifier.urihttp://hdl.handle.net/11449/158812
dc.identifier.wosWOS:000374239600074
dc.language.isoeng
dc.publisherIeee-inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Sensors Journal
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectData fusion
dc.subjectdistributed detection
dc.subjectwireless sensor networks
dc.titleAverage Error Probability in Wireless Sensor Networks With Imperfect Sensing and Communication for Different Decision Rulesen
dc.typeArtigo
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee-inst Electrical Electronics Engineers Inc
unesp.author.orcid0000-0002-8689-5313[3]

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