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dc.contributor.authorSboui, Lokman
dc.contributor.authorGhazzai, Hakim
dc.contributor.authorRezki, Zouheir
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2018-03-15T06:26:39Z
dc.date.available2018-03-15T06:26:39Z
dc.date.issued2018-02-12
dc.identifier.citationSboui L, Ghazzai H, Rezki Z, Alouini M-S (2017) Energy-Efficient Power Allocation for UAV Cognitive Radio Systems. 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall). Available: http://dx.doi.org/10.1109/vtcfall.2017.8287971.
dc.identifier.doi10.1109/vtcfall.2017.8287971
dc.identifier.urihttp://hdl.handle.net/10754/627307
dc.description.abstractWe study the deployment of unmanned aerial vehicles (UAV) based cognitive system in an area covered by the primary network (PN). An UAV shares the spectrum of the PN and aims to maximize its energy efficiency (EE) by optimizing the transmit power. We focus on the case where the UAV simultaneously communicates with the ground receiver (G), under interference limitation, and with another relaying UAV (A), with a minimal required rate. We analytically develop the power allocation framework that maximizes the EE subject to power budget, interference, and minimal rate constraints. In the numerical results, we show that the minimal rate may cause a transmission outage at low power budget values. We also highlighted the existence of optimal altitudes given the UAV location with respect to the different other terminals.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/8287971/
dc.rights(c) 2017 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.titleEnergy-Efficient Power Allocation for UAV Cognitive Radio Systems
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journal2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)
dc.eprint.versionPost-print
dc.contributor.institutionQatar Mobility Innovations Center (QMIC), Qatar University, Doha, Qatar
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Idaho, Moscow, ID 83844, USA
kaust.personSboui, Lokman
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2018-06-14T03:41:20Z
dc.date.published-online2018-02-12
dc.date.published-print2017-09


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