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dc.contributor.authorSboui, Lokman
dc.contributor.authorRezki, Zouheir
dc.contributor.authorSalem, Ahmed Sultan
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2017-05-31T11:23:08Z
dc.date.available2017-05-31T11:23:08Z
dc.date.issued2017-03-20
dc.identifier.citationSboui L, Rezki Z, Sultan A, Alouini M-S (2016) Energy-Efficient Power Allocation for Cognitive MIMO Channels. 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall). Available: http://dx.doi.org/10.1109/vtcfall.2016.7880994.
dc.identifier.doi10.1109/vtcfall.2016.7880994
dc.identifier.urihttp://hdl.handle.net/10754/623830
dc.description.abstractDue to the massive data traffic in wireless networks, energy consumption has become a crucial concern, especially with the limited power supply of the mobile terminals and the increasing CO2 emission of the cellular industry. In this context, we study the energy efficiency (EE) of MIMO spectrum sharing cognitive radio (CR) systems under power and interference constraints. We present an energy-efficient power allocation framework based on maximizing the average EE per parallel channel resulting from the singular value decomposition (SVD) eigenmode transmission. We also present a sub-optimal low-complexity power allocation scheme based on the water-filling power allocation. In the numerical results, we show that the sub-optimal power allocation achieves at least 95% of the optimal performance. In addition, we show that adopting more antennas is more energy efficient for a given power budget. Finally, we show that the interference threshold has a significant effect on both the EE and the spectral efficiency at high-power regime.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/7880994/
dc.subjectEnergy efficiency
dc.subjectMIMO-SVD channels
dc.subjectSpectrum sharing CR
dc.titleEnergy-Efficient Power Allocation for Cognitive MIMO Channels
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Division
dc.identifier.journal2016 IEEE 84th Vehicular Technology Conference (VTC-Fall)
dc.conference.date2016-09-18 to 2016-09-21
dc.conference.name84th IEEE Vehicular Technology Conference, VTC Fall 2016
dc.conference.locationMontreal, QC, CAN
kaust.personSboui, Lokman
kaust.personRezki, Zouheir
kaust.personSalem, Ahmed Sultan
kaust.personAlouini, Mohamed-Slim
dc.date.published-online2017-03-20
dc.date.published-print2016-09


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