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dc.contributor.authorMondal, Riaz
dc.contributor.authorRistaniemi, Tapani
dc.contributor.authorTurkka, Jussi
dc.date.accessioned2017-12-14T11:40:46Z
dc.date.available2017-12-14T11:40:46Z
dc.date.issued2015
dc.identifier.citationMondal, R., Ristaniemi, T., & Turkka, J. (2015). Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Outdoor Signals. In <i>ICICS 2015 : Proceedings of the 10th International conference on information, communications and signal processing, December 2-4, 2015, Singapore</i> (pp. 1-5). IEEE. <a href="https://doi.org/10.1109/ICICS.2015.7459987" target="_blank">https://doi.org/10.1109/ICICS.2015.7459987</a>
dc.identifier.otherCONVID_25560868
dc.identifier.otherTUTKAID_69252
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/56332
dc.description.abstractIn this paper we evaluate user-equipment (UE) positioning performance of three cluster-based RF fingerprinting methods using LTE and WLAN signals. Real-life LTE and WLAN data were collected for the evaluation purpose using consumer cellular-mobile handset utilizing ‘Nemo Handy’ drive test software tool. Test results of cluster-based methods were compared to the conventional grid-based RF fingerprinting. The cluster-based methods do not require grid-cell layout and training signature formation as compared to the gridbased method. They utilize LTE cell-ID searching technique to reduce the search space for clustering operation. Thus UE position estimation is done in short time with less computational cost. Among the cluster-based methods Agglomerative Hierarchical Cluster based RF fingerprinting provided best positioning accuracy using a single LTE and six WLAN signal strengths. This method showed an improvement of 42.3 % and 39.8 % in the 68th percentile and 95th percentile of positioning error (PE) over the grid-based RF fingerprinting.
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofICICS 2015 : Proceedings of the 10th International conference on information, communications and signal processing, December 2-4, 2015, Singapore
dc.subject.otherLTE
dc.subject.othercell-ID
dc.subject.othergrid-based RF fingerprinting
dc.subject.otherK-nearest neighbor
dc.subject.otherhierarchical clustering
dc.subject.otherfuzzy C-means
dc.subject.otherminimization of drive tests
dc.titleCluster-Based RF Fingerprint Positioning Using LTE and WLAN Outdoor Signals
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201712114592
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2017-12-11T07:15:08Z
dc.relation.isbn978-1-4673-7216-9
dc.type.coarconference paper
dc.description.reviewstatuspeerReviewed
dc.format.pagerange1-5
dc.type.versionacceptedVersion
dc.rights.copyright© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational conference on information, communications and signal processing
dc.relation.doi10.1109/ICICS.2015.7459987


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