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AuthorAlvi, Sheeraz A.
AuthorYounis, Muhammad S.
AuthorImran, Muhammad
AuthorAmin, Fazal-e-
AuthorGuizani, Mohsen
Available date2022-11-10T09:47:23Z
Publication Date2015
Publication NameIEEE Transactions on Wireless Communications
ResourceScopus
Resource2-s2.0-84937117339
URIhttp://dx.doi.org/10.1109/TWC.2015.2413873
URIhttp://hdl.handle.net/10576/36147
AbstractIn Cognitive Radio Ad Hoc Networks (CRAHNs), cooperative spectrum sensing schemes exploit spatial diversity of the Secondary Users (SUs), to reliably detect an unoccupied licensed spectrum. Soft energy combining schemes provide optimal detection performance by combining the actual sensed information from SUs. For reliable data fusion, these techniques mandate weight estimation for individual SUs in each sensing interval, resulting in high cooperation overhead in terms of time, processing and bandwidth. Alternately, a hard energy combining scheme offers lower cooperation overhead in which only local SU decisions are reported to the fusion center. However, it provides sub-optimal detection performance due to the information loss. In this paper, a Log-Likelihood Ratio (LLR) based cooperative spectrum sensing scheme is proposed in which each SU performs a local LLR based sensing test employing two threshold levels. The local decision and sequentially estimated SNR parameter values (for weight computation) are not reported to the fusion center if the local test result is in-between the two threshold levels. Thereby, cooperation overhead is reduced in proportion to the hard combining techniques; nevertheless simulation results show that the detection performance of the proposed scheme is close to the optimal soft combining techniques. 2002-2012 IEEE.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCognitive radio networks
cooperation overhead
cooperative spectrum sensing
optimal combining
TitleA near-optimal LLR based cooperative spectrum sensing scheme for CRAHNs
TypeArticle
Pagination3877-3887
Issue Number7
Volume Number14
dc.accessType Abstract Only


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