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dc.contributor.authorŞenol, Habib
dc.contributor.authorTepedelenlioğlu, Cihan
dc.date.accessioned2019-06-27T08:06:11Z
dc.date.available2019-06-27T08:06:11Z
dc.date.issued2008
dc.identifier.isbn978-1-4244-1483-3
dc.identifier.issn1520-6149en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/1166
dc.identifier.urihttps://doi.org/10.1109/ICASSP.2008.4518357
dc.description.abstractWe consider distributed estimation of a source observed by sensors in additive Gaussian noise where the sensors are connected to a fusion center with unknown orthogonal (parallel) flat Rayleigh fading channels. We adopt a two-phase approach of (i) channel estimation with training and (ii) source estimation given the channel estimates where the total power is fixed. We prove that allocating half the total power into training is optimal and show that compared to the perfect channel case a performance loss of at least 6 dB is incurred. In addition we show that unlike the perfect channel case increasing the number of sensors will lead to an eventual degradation in performance. We characterize the optimum number of sensors as a function of the total power and noise statistics. Simulations corroborate our analytical findings.en_US]
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSensor networksen_US
dc.subjectDistributed estimationen_US
dc.subjectFading channelsen_US
dc.subjectChannel estimationen_US
dc.titleDistributed estimation over parallel fading channels with channel estimation erroren_US
dc.typeconferenceObjecten_US
dc.identifier.startpage3305en_US
dc.identifier.endpage+
dc.relation.journal2008 IEEE International Conference On Acoustics, Speech And Signal Processing, Vols 1-12en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000257456702149en_US
dc.identifier.doi10.1109/ICASSP.2008.4518357en_US
dc.identifier.scopus2-s2.0-51449085196en_US
dc.institutionauthorŞenol, Habiben_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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