Show simple item record

dc.contributor.authorÖzgör, Mehmet
dc.contributor.authorErküçük, Serhat
dc.contributor.authorÇırpan, Hakan Ali
dc.date.accessioned2019-06-27T08:02:14Z
dc.date.available2019-06-27T08:02:14Z
dc.date.issued2015
dc.identifier.issn1018-4864
dc.identifier.issn1572-9451
dc.identifier.urihttps://hdl.handle.net/20.500.12469/579
dc.identifier.urihttps://dx.doi.org/10.1007/s11235-014-9902-7
dc.description.abstractDue to the sparse structure of ultra-wideband (UWB) channels compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered. In this paper we study the channel estimation performance of Bayesian CS (BCS) for various UWB channel models and noise conditions. Specifically we investigate the effects of (i) sparse structure of standardized IEEE 802.15.4a channel models (ii) signal-to-noise ratio (SNR) regions and (iii) number of measurements on the BCS channel estimation performance and compare them to the results of -norm minimization based estimation which is widely used for sparse channel estimation. We also provide a lower bound on mean-square error (MSE) for the biased BCS estimator and compare it with the MSE performance of implemented BCS estimator. Moreover we study the computation efficiencies of BCS and -norm minimization in terms of computation time by making use of the big- notation. The study shows that BCS exhibits superior performance at higher SNR regions for adequate number of measurements and sparser channel models (e.g. CM-1 and CM-2). Based on the results of this study the BCS method or the -norm minimization method can be preferred over the other one for different system implementation conditions.
dc.language.isoEnglish
dc.publisherSpringer
dc.subjectBayesian compressive sensing (BCS)
dc.subjectIEEE 802.15.4a channel models
dc.subjectl(1)-norm minimization
dc.subjectMean-square error (MSE) lower bound
dc.subjectUltra-wideband (UWB) channel estimation
dc.titleBayesian compressive sensing for ultra-wideband channel estimation: algorithm and performance analysis
dc.typeArticle
dc.identifier.startpage417
dc.identifier.endpage427
dc.relation.journalTelecommunication Systems
dc.identifier.issue4
dc.identifier.volume59
dc.identifier.wosWOS:000356933400002
dc.identifier.doi10.1007/s11235-014-9902-7
dc.contributor.khasauthorErküçük, Serhat


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record