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dc.contributor.authorPanayırcı, Erdal
dc.contributor.authorÇırpan, Hakan Ali
dc.date.accessioned2019-06-27T08:06:56Z
dc.date.available2019-06-27T08:06:56Z
dc.date.issued2006
dc.identifier.isbn3-540-30635-8
dc.identifier.issn0930-8989en_US
dc.identifier.issn1867-4941en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/1245
dc.description.abstractTraditional wireless technologies are not well suited to meet the extremely demanding requirements of providing the very high data rates with the ubiquity mobility and portability characteristic of cellular systems. Some fundamental barriers related to the nature of the radio channel as well as the limited bandwidth availability at the frequencies of interest stand in the way. Unique sets of efficient advanced signal processing algorithms and techniques is the one of the primary enablers that will allow lifting these limits primarily due to the impressive advent of low cost and low power digital signal processors. As an application of advanced signal processing techniques we will consider the solution of blind phase noise estimation and data detection problem via a computationally efficient sequential Monte Carlo (SMC) methodology in this paper.en_US]
dc.language.isoengen_US
dc.publisherSpringer-Verlag Berlinen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectN/Aen_US
dc.titleAdvanced signal processing algorithms for wireless communicationsen_US
dc.typeconferenceObjecten_US
dc.identifier.startpage333en_US
dc.relation.journalComplex Computing-Networks: Brain-Like And Wave-Oriented Electrodynamic Algorithmsen_US
dc.identifier.volume104en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000237287400037en_US
dc.institutionauthorPanayırcı, Erdalen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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