Show simple item record

dc.contributor.authorKocak, F.en_US
dc.contributor.authorCelebi, H.en_US
dc.contributor.authorGezici, S.en_US
dc.contributor.authorQaraqe, K. A.en_US
dc.contributor.authorArslan, H.en_US
dc.contributor.authorPoor, H. V.en_US
dc.date.accessioned2016-02-08T09:55:41Z
dc.date.available2016-02-08T09:55:41Z
dc.date.issued2010en_US
dc.identifier.issn1687-6172
dc.identifier.urihttp://hdl.handle.net/11693/22113
dc.description.abstractTime-delay estimation is studied for cognitive radio systems, which facilitate opportunistic use of spectral resources. A two-step approach is proposed to obtain accurate time-delay estimates of signals that occupy multiple dispersed bands simultaneously, with significantly lower computational complexity than the optimal maximum likelihood (ML) estimator. In the first step of the proposed approach, an ML estimator is used for each band of the signal in order to estimate the unknown parameters of the signal occupying that band. Then, in the second step, the estimates from the first step are combined in various ways in order to obtain the final time-delay estimate. The combining techniques that are used in the second step are called optimal combining, signal-to-noise ratio (SNR) combining, selection combining, and equal combining. It is shown that the performance of the optimal combining technique gets very close to the Cramer-Rao lower bound at high SNRs. These combining techniques provide various mechanisms for diversity combining for time-delay estimation and extend the concept of diversity in communications systems to the time-delay estimation problem in cognitive radio systems. Simulation results are presented to evaluate the performance of the proposed estimators and to verify the theoretical analysis.en_US
dc.language.isoEnglishen_US
dc.source.titleEurasip Journal on Advances in Signal Processingen_US
dc.relation.isversionofhttp://dx.doi.org/10.1155/2010/675959en_US
dc.subjectCognitive radioen_US
dc.subjectCombining techniquesen_US
dc.subjectCommunications systemsen_US
dc.subjectCramer Rao lower bounden_US
dc.subjectDiversity combiningen_US
dc.subjectMaximum likelihood estimatoren_US
dc.subjectML estimatorsen_US
dc.subjectOptimal combiningen_US
dc.subjectSelection combiningen_US
dc.subjectSignal to noiseen_US
dc.subjectSimulation resulten_US
dc.subjectTime delay estimationen_US
dc.subjectTwo-step approachen_US
dc.subjectUnknown parametersen_US
dc.subjectCognitive systemsen_US
dc.subjectComputational complexityen_US
dc.subjectCramer-Rao boundsen_US
dc.subjectEstimationen_US
dc.subjectFrequency shift keyingen_US
dc.subjectMaximum likelihood estimationen_US
dc.subjectOptimizationen_US
dc.subjectRadioen_US
dc.subjectRadio systemsen_US
dc.subjectSignal to noise ratioen_US
dc.subjectTime delayen_US
dc.titleTime-delay estimation in dispersed spectrum cognitive radio systemsen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineering
dc.citation.spage1en_US
dc.citation.epage10en_US
dc.citation.volumeNumber2010en_US
dc.identifier.doi10.1155/2010/675959en_US
dc.publisherSpringerOpenen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record