Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage

Aniket Basu (), Hooman Oroojeni, Georgios Samakovitis and Mohammad Majid Al-Rifaie ()
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Aniket Basu: School of Computing and Mathematical Sciences, University of Greenwich, Park Row, London SE10 9LS, UK
Hooman Oroojeni: School of Computing and Mathematical Sciences, University of Greenwich, Park Row, London SE10 9LS, UK
Georgios Samakovitis: School of Computing and Mathematical Sciences, University of Greenwich, Park Row, London SE10 9LS, UK
Mohammad Majid Al-Rifaie: School of Computing and Mathematical Sciences, University of Greenwich, Park Row, London SE10 9LS, UK

Future Internet, 2024, vol. 16, issue 11, 1-25

Abstract: Using drone cells to optimize Radio Access Networks is an exemplary way to enhance the capabilities of terrestrial Radio Access Networks. Drones fitted with communication and relay modules can act as drone cells to provide an unobtrusive network connection. The multi-drone-cell placement problem is solved using adapted Dispersive Flies Optimization alongside other meta-heuristic algorithms such as Particle Swarm Optimization and differential evolution. A home-brewed simulator has been used to test the effectiveness of the different implemented algorithms. Specific environment respective parameter tuning has been explored to better highlight the possible advantages of one algorithm over the other in any particular environment. Algorithmic diversity has been explored, leading to several modifications and improvements in the implemented models. The results show that by using tuned parameters, there is a performance uplift in coverage probability when compared to the default meta-heuristic parameters while still remaining within the constraints implied by the problem’s requirements and resource limitation. This paper concludes by offering a study and comparison between multiple meta-heuristic approaches, investigating the impact of parameter tuning as well as analyzing the impact of intermittent restarts for the algorithms’ persistent diversity.

Keywords: drone-assisted radio access network; drone cell placement; hyper-heuristic; parameter tuning; dispersive flies optimization; particle swarm optimization; differential evolution (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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