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dc.contributor.authorAbdelgawwad, Ahmed
dc.contributor.authorPätzold, Matthias Uwe
dc.date.accessioned2019-04-17T08:28:02Z
dc.date.available2019-04-17T08:28:02Z
dc.date.created2018-07-02T14:08:16Z
dc.date.issued2018
dc.identifier.citationAbdelgawwad, A. & Patzold, M. (2018). A Framework for Activity Monitoring and Fall Detection Based on the Characteristics of Indoor Channels. IEEE Vehicular Technology Conference (VTC) Proceedings.
dc.identifier.isbn978-1-5386-6355-4
dc.identifier.urihttp://hdl.handle.net/11250/2594883
dc.descriptionAuthor´s accepted manuscript
dc.description© 2018 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.description.abstractThis paper concerns the Doppler power spectrum of three-dimensional non-stationary indoor fixed-to- fixed channels with moving people. In this paper, we model each moving person as a moving scatterer with time-variant (TV) speed, TV vertical angles of motion, and TV horizontal angles of motion of the moving scatterers. Furthermore, we derive the TV angular parameters of each moving scatterer such as the elevation angle of departure, the azimuth angle of departure, the elevation angle of arrival, and the azimuth angle of arrival. In addition, the TV unit vectors of the departure of the transmitted wave planes and unit vectors of the arrival of the received wave planes are derived. Furthermore, to present the Doppler power spectrum characteristics of such channels, we provide the closed-form solution of the spectrogram of the complex channel gain. The correctness of the analysis is approved by simulations. The contribution of this paper is an initiative for the development of device-free indoor activity monitoring and fall detection systems.nb_NO
dc.language.isoengnb_NO
dc.publisherIEEE
dc.relation.ispartof2018 IEEE 87th Vehicular Technology Conference (VTC Spring)
dc.titleA Framework for Activity Monitoring and Fall Detection Based on the Characteristics of Indoor Channelsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.rights.holder© 2018 IEEE
dc.source.journalIEEE Vehicular Technology Conference (VTC) Proceedings
dc.identifier.doihttps://doi.org/10.1109/VTCSpring.2018.8417468
dc.identifier.cristin1595224
dc.relation.projectNorges forskningsråd: 261895nb_NO
cristin.qualitycode1


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