On-demand deployment of multiple aerial base stations for traffic offloading and network recovery

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dc.contributor.author Sharafeddine, Sanaa
dc.contributor.author Islambouli, Rania
dc.date.accessioned 2019-05-07T08:31:37Z
dc.date.available 2019-05-07T08:31:37Z
dc.date.copyright 2019 en_US
dc.date.issued 2019-05-07
dc.identifier.issn 1389-1286 en_US
dc.identifier.uri http://hdl.handle.net/10725/10566
dc.description.abstract Unmanned aerial vehicles (UAVs) are being utilized for a wide spectrum of applications in wireless networks leading to attractive business opportunities. In the case of abrupt disruption to existing cellular network operation or infrastructure, e.g., due to an unexpected surge in user demand or a natural disaster, UAVs can be deployed to provide instant recovery via temporary wireless coverage in designated areas. A major challenge is to determine efficiently how many UAVs are needed and where to position them in a relatively large 3D search space. We first consider a discrete set of possible UAV locations distributed in a given 3D space and formulate the problem as a mixed integer linear program (MILP). Owing to the complexity of the MILP problem, we present an effective greedy approach that mimics the behavior of the MILP for small network scenarios and scales efficiently for large network scenarios. Afterwards, we propose and evaluate a more practical approach for multiple UAV deployment in a continuous 3D space, based on an unsupervised learning technique that relies on the notion of electrostatics with repulsion and attraction forces. We present performance results for the proposed algorithm as a function of various system parameters and demonstrate its effectiveness compared to the close-to-optimal greedy approach and its superiority compared to recent related work from the literature. en_US
dc.language.iso en en_US
dc.title On-demand deployment of multiple aerial base stations for traffic offloading and network recovery en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 200502746 en_US
dc.author.department Computer Science And Mathematics en_US
dc.description.embargo N/A en_US
dc.relation.journal Computer Networks en_US
dc.journal.volume 156 en_US
dc.article.pages 52-61 en_US
dc.keywords Aerial base station deployment and planning en_US
dc.keywords Drone cells en_US
dc.keywords Traffic offloading en_US
dc.keywords 4G/5G cellular systems en_US
dc.identifier.doi https://doi.org/10.1016/j.comnet.2019.03.016 en_US
dc.identifier.ctation Sharafeddine, S., & Islambouli, R. (2019). On-demand deployment of multiple aerial base stations for traffic offloading and network recovery. Computer Networks, 156, 52-61. en_US
dc.author.email sanaa.sharafeddine@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S1389128618304328 en_US
dc.orcid.id https://orcid.org/0000-0001-6548-1624 en_US
dc.author.affiliation Lebanese American University en_US

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