Distributed estimation based on observations prediction in wireless sensor networks

Handle URI:
http://hdl.handle.net/10754/564200
Title:
Distributed estimation based on observations prediction in wireless sensor networks
Authors:
Bouchoucha, Taha ( 0000-0001-7818-3757 ) ; Ahmed, Mohammed F A; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process. In this letter, the correlation between observations is exploited to reduce the mean-square error (MSE) of the distributed estimation. Specifically, sensor nodes generate local predictions of their observations and then transmit the quantized prediction errors (innovations) to the FC rather than the quantized observations. The analytic and numerical results show that transmitting the innovations rather than the observations mitigates the effect of quantization noise and hence reduces the MSE. © 2015 IEEE.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Electrical Engineering Program; Communication Theory Lab
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Signal Processing Letters
Issue Date:
19-Mar-2015
DOI:
10.1109/LSP.2015.2411852
Type:
Article
ISSN:
10709908
Sponsors:
This work was supported by the King Abdulaziz City of Science and Technology (KACST) under Grant AT-34-345. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Vincenzo Matta.
Appears in Collections:
Articles; Electrical Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorBouchoucha, Tahaen
dc.contributor.authorAhmed, Mohammed F Aen
dc.contributor.authorAl-Naffouri, Tareq Y.en
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2015-08-03T12:36:10Zen
dc.date.available2015-08-03T12:36:10Zen
dc.date.issued2015-03-19en
dc.identifier.issn10709908en
dc.identifier.doi10.1109/LSP.2015.2411852en
dc.identifier.urihttp://hdl.handle.net/10754/564200en
dc.description.abstractWe consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process. In this letter, the correlation between observations is exploited to reduce the mean-square error (MSE) of the distributed estimation. Specifically, sensor nodes generate local predictions of their observations and then transmit the quantized prediction errors (innovations) to the FC rather than the quantized observations. The analytic and numerical results show that transmitting the innovations rather than the observations mitigates the effect of quantization noise and hence reduces the MSE. © 2015 IEEE.en
dc.description.sponsorshipThis work was supported by the King Abdulaziz City of Science and Technology (KACST) under Grant AT-34-345. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Vincenzo Matta.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectCorrelationen
dc.subjectmean square erroren
dc.subjectpredictionen
dc.subjectquantizationen
dc.subjectwireless sensor networksen
dc.titleDistributed estimation based on observations prediction in wireless sensor networksen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentElectrical Engineering Programen
dc.contributor.departmentCommunication Theory Laben
dc.identifier.journalIEEE Signal Processing Lettersen
dc.contributor.institutionElectrical Engineering Department, Assiut UniversityAssiut, Egypten
kaust.authorBouchoucha, Tahaen
kaust.authorAl-Naffouri, Tareq Y.en
kaust.authorAlouini, Mohamed-Slimen
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