Optimizing fairness in cellular networks with mobile drone relays
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Title
Optimizing fairness in cellular networks with mobile drone relaysAuthor (s)
Date
2023-02-10Publisher
ElsevierBibliographic citation
Arribas, E., Mancuso, V., & Cholvi, V. (2023). Optimizing fairness in cellular networks with mobile drone relays. Computer Networks, 224, 109623.Type
info:eu-repo/semantics/articleVersion
info:eu-repo/semantics/publishedVersionSubject
Abstract
Aiding the ground cellular network with aerial base stations carried by drones has experienced an intensive raise of interest in the past years. Reconfigurable air-to-ground channels enable aerial stations to enhance ... [+]
Aiding the ground cellular network with aerial base stations carried by drones has experienced an intensive raise of interest in the past years. Reconfigurable air-to-ground channels enable aerial stations to enhance users’ access links by means of seeking good line-of-sight connectivity while hovering in the air. In this article, we propose an analytical framework for the 3D placement of a fleet of coordinated drone relays. This framework optimizes network performance in terms of user throughput fairness, expressed through the
-fairness metric. The optimization problem is formulated as a mixed-integer non-convex program, which is intractable. Hence, we propose an extremal-optimization-based algorithm, Parallelized Alpha-fair Drone Deployment (PADD), which solves the problem online, in low-degree polynomial time. We evaluate our proposal by means of numerical simulations over the real topology of a dense city. We discuss the advantages of integrating drone relay stations in current networks and test several resource scheduling approaches in both static and dynamic scenarios, including with progressively larger and denser crowds. [-]
Funder Name
Spanish Ministry of Education, Culture and Sports (MECD), Spain | Spanish Ministry of Science, Innovation and Universities | Regional Government of Madrid | European Union | European Regional Development Fund (ERDF)
Project code
FPU15/02051 | PID2019-109805RB-I00 (ECID) | REACT-CONTACT-CM-23479
Rights
© 2023 The Author(s). Published by Elsevier B.V.
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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