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Drone Base Stations Transmission Power Control and Localization

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Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2022)

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Abstract

We target the problem of deploying drone base stations (DBSs) to serve a set of users with known locations after dividing it into two problems: users clustering along with 2D localization of drones, and transmission power control. For clustering, we propose an algorithm inspired by the expectation-maximization (EM) algorithm that boosts link reliability. As for transmission power control, we utilize the Monte Carlo tree search (MCTS) algorithm. Furthermore, we show that the resulting mechanism can also adapt to user changes without rebuilding the search tree, and it also intrinsically avoids collision between DBSs. Also, our simulations show that our proposed algorithm improves the link reliability and system energy efficiency substantially in comparison to another mechanism mentioned in the literature. The results show that controlling the power of DBSs does not only reduce power consumption but also improves the users’ links quality. Finally, we show the improvement in system performance relative to the baseline method where DBSs are randomly distributed and users are changing their location according to the random waypoint mobility model.

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Authors and Affiliations

  1. Institute of Radiocommunications, Poznan University of Technology, Poznań, Poland

    Salim Janji & Adrian Kliks

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  1. Salim Janji
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  2. Adrian Kliks
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Correspondence to Salim Janji .

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Editors and Affiliations

  1. University of Pittsburgh, Pittsburgh, PA, USA

    Shangguan Longfei

  2. Microsoft Research, Redmond, WA, USA

    Priyantha Bodhi

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Janji, S., Kliks, A. (2023). Drone Base Stations Transmission Power Control and Localization. In: Longfei, S., Bodhi, P. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 492. Springer, Cham. https://doi.org/10.1007/978-3-031-34776-4_19

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  • DOI: https://doi.org/10.1007/978-3-031-34776-4_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34775-7

  • Online ISBN: 978-3-031-34776-4

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