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dc.contributor.authorBuyuksar, Ayse Betul
dc.contributor.authorŞenol, Habib
dc.contributor.authorErküçük, Serhat
dc.contributor.authorCirpan, Hakan Ali
dc.date.accessioned2019-06-27T08:02:01Z
dc.date.available2019-06-27T08:02:01Z
dc.date.issued2016
dc.identifier.isbn97815090-20614
dc.identifier.issn2154-0217
dc.identifier.urihttps://hdl.handle.net/20.500.12469/529
dc.identifier.urihttps://doi.org/10.1109/ISWCS.2016.7600941
dc.description.abstractIn order to meet future communication system requirements channel estimation over fast fading and frequency selective channels is crucial. In this paper Space Alternated Generalized Expectation Maximization Maximum a Posteriori (SAGE-MAP) based channel estimation algorithm is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems for Autoregressive (AR) modeled time-varying sparse channels. Also an initialization algorithm has been developed from the widely used sparse approximation algorithm Orthogonal Matching Pursuit (OMP) since the performance of SAGE algorithm strictly depends on initialization. The results show that multipath delay positions can be tracked successfully for every time instant using the proposed SAGE-MAP based approach.
dc.language.isoEnglish
dc.publisherIEEE
dc.subjectOFDM
dc.subjectAutoregressive Model
dc.subjectFast Time-Varying
dc.subjectSage-Map
dc.subjectOMP
dc.subjectSparse Channel Estimation
dc.titleData-Aided Autoregressive Sparse Channel Tracking for OFDM Systems
dc.typeProceedings Paper
dc.identifier.startpage424
dc.identifier.endpage428
dc.relation.journal2016 13th International Symposium on Wireless Communication Systems (ISWCS)
dc.identifier.wosWOS:000386654000078
dc.identifier.doi10.1109/ISWCS.2016.7600941
dc.contributor.khasauthorŞenol, Habib
dc.contributor.khasauthorErküçük, Serhat


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