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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.issn0930-8989
dc.identifier.issn1867-4941
dc.identifier.urihttps://hdl.handle.net/20.500.12469/1245
dc.identifier.urihttps://link.springer.com/chapter/10.1007/3-540-30636-6_37
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.
dc.language.isoEnglish
dc.publisherSpringer-Verlag Berlin
dc.titleAdvanced signal processing algorithms for wireless communications
dc.typeProceedings Paper
dc.identifier.startpage333
dc.relation.journalComplex Computing-Networks: Brain-Like And Wave-Oriented Electrodynamic Algorithms
dc.identifier.volume104
dc.identifier.wosWOS:000237287400037
dc.contributor.khasauthorPanayırcı, Erdal


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