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AuthorHashemi, Hadi
AuthorFard, Sina Mohammadi
AuthorTaherpour, Abbas
AuthorKhattab, Tamer
Available date2022-10-31T19:21:55Z
Publication Date2015
Publication NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
ResourceScopus
URIhttp://dx.doi.org/10.1007/978-3-319-24540-9_1
URIhttp://hdl.handle.net/10576/35662
AbstractIn this paper, we study the problem of cyclostationary spectrum sensing in cognitive radio networks based on cyclic properties of linear modulations. For this purpose, we use fractional order of observations in cyclic autocorrelation function (CAF).We derive the generalized likelihood ratio (GLR) for designing the detector. Therefore, the performance of this detector has been improved compared to previous detectors. We also find optimum value of the fractional order of observations in additive Gaussian noise. The exact performance of the GLR detector is derived analytically as well. The simulation results are presented to evaluate the performance of the proposed detector and compare its performance with their counterpart, so to illustrate the impact of the optimum value of fractional order over performance improvement of these detectors. Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015.
Languageen
PublisherSpringer Verlag
SubjectCognitive radio
Cyclostationary signal
Fractional low order
Spectrum sensing
TitleFractional low order cyclostationary-based spectrum sensing in cognitive radio networks
TypeConference Paper
Pagination16-Mar
Volume Number156
dc.accessType Abstract Only


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