Show simple item record

dc.contributor.authorAbdi Mahmoudaliloo, Younes
dc.contributor.authorRistaniemi, Tapani
dc.date.accessioned2014-12-03T07:09:40Z
dc.date.available2014-12-03T07:09:40Z
dc.date.issued2014fi
dc.identifier.citationAbdi Mahmoudaliloo, Y., & Ristaniemi, T. (2014). Joint local quantization and linear cooperation in spectrum sensing for cognitive radio networks. <em>IEEE transactions on signal processing</em>, 62 (17), 4349-4362. <a href="http://dx.doi.org/10.1109/TSP.2014.2330803">doi:10.1109/TSP.2014.2330803</a>fi
dc.identifier.otherTUTKAID_63706
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/44801
dc.description.abstract—In designing cognitive radio networks (CRNs), protecting the license holders from harmful interference while maintaining acceptable quality-of-service (QoS) levels for the secondary users is a challenge effectively mitigated by cooperative spectrum sensing schemes. In this paper, cooperative spectrum sensing in CRNs is studied as a three-phase process composed of local sensing, reporting, and decision/data fusion. Then, a significant tradeoff in designing the reporting phase, i.e., the effect of the number of bits used in local sensing quantization on the overall sensing performance is identified and formulated. In addition, a novel approach is proposed to jointly optimize the linear soft-combining scheme at the fusion phase with the number of quantization bits used by each sensing node at the reporting phase. The proposed optimization is represented using the conventional false alarm and missed detection probabilities, in the form of a mixed-integer nonlinear programming (MINLP) problem. The solution is developed as a branch-and-bound procedure based on convex hull relaxation, and a low-complexity suboptimal approach is also provided. Finally, the performance improvement associated with the proposed joint optimization scheme, which is due to better exploitation of spatial/user diversities in CRNs, is demonstrated by a set of illustrative simulation results.fi
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relation.ispartofseriesIEEE transactions on signal processing
dc.subject.othercognitive radio (CR)fi
dc.subject.othercooperative spectrum sensingfi
dc.subject.otherdecision fusionfi
dc.subject.othernon-ideal reporting channelfi
dc.subject.otherquantizationfi
dc.titleJoint local quantization and linear cooperation in spectrum sensing for cognitive radio networksfi
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201411243349
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.oppiaineTietotekniikka
dc.type.urihttp://purl.org/eprint/type/SubmittedJournalArticle
dc.date.updated2014-11-24T16:30:03Z
dc.type.coarjournal article
dc.description.reviewstatuspeerReviewed
dc.format.pagerange4349-4362
dc.relation.issn1053-587X
dc.relation.numberinseries17
dc.relation.volume62
dc.type.versionacceptedVersion
dc.rights.copyright© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.rights.accesslevelopenAccessfi
dc.relation.doi10.1109/TSP.2014.2330803


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record