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dc.contributor.authorGhazzai, Hakim
dc.contributor.authorYaacoub, Elias E.
dc.contributor.authorAlouini, Mohamed-Slim
dc.contributor.authorAbu-Dayya, Adnan A.
dc.date.accessioned2015-08-03T12:15:48Z
dc.date.available2015-08-03T12:15:48Z
dc.date.issued2014-11
dc.identifier.citationGhazzai, H., Yaacoub, E., Alouini, M.-S., & Abu-Dayya, A. (2014). Optimized Smart Grid Energy Procurement for LTE Networks Using Evolutionary Algorithms. IEEE Transactions on Vehicular Technology, 63(9), 4508–4519. doi:10.1109/tvt.2014.2312380
dc.identifier.issn00189545
dc.identifier.doi10.1109/TVT.2014.2312380
dc.identifier.urihttp://hdl.handle.net/10754/563826
dc.description.abstractEnergy efficiency aspects in cellular networks can contribute significantly to reducing worldwide greenhouse gas emissions. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Moreover, introducing renewable energy as an alternative power source has become a real challenge among network operators. In this paper, we formulate an optimization problem that aims to maximize the profit of Long-Term Evolution (LTE) cellular operators and to simultaneously minimize the CO2 emissions in green wireless cellular networks without affecting the desired quality of service (QoS). The BS sleeping strategy lends itself to an interesting implementation using several heuristic approaches, such as the genetic (GA) and particle swarm optimization (PSO) algorithms. In this paper, we propose GA-based and PSO-based methods that reduce the energy consumption of BSs by not only shutting down underutilized BSs but by optimizing the amounts of energy procured from different retailers (renewable energy and electricity retailers), as well. A comparison with another previously proposed algorithm is also carried out to evaluate the performance and the computational complexity of the employed methods.
dc.description.sponsorshipThis work was supported in part by the Qatar National Research Fund (a member of Qatar Foundation) under NPRP Grant 6-001-2-001. The review of this paper was coordinated by Dr. Y. Ji.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectBase station (BS) sleeping strategy
dc.subjectenergy efficiency
dc.subjectevolutionary algorithms
dc.subjectgreen network
dc.subjectsmart grid
dc.titleOptimized smart grid energy procurement for LTE networks using evolutionary algorithms
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentCommunication Theory Lab
dc.identifier.journalIEEE Transactions on Vehicular Technology
dc.contributor.institutionQatar Mobility Innovations CenterDoha, Qatar
kaust.personGhazzai, Hakim
kaust.personAlouini, Mohamed-Slim


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