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An Improved Particle Swarm Optimization Algorithm for UAV Base Station Placement

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Abstract

In cellular networks, a set of Base Stations (BSs) might be out of service and failed in the aftermath of natural disasters. One of the promising solutions to fix this situation is to send low altitude drones equipped with a small cellular BS (DBSs) to the target locations. This can provide cellular networks with vital communication links and make available temporary coverage for the users in unexpected circumstances. However, finding the minimum number of DBSs and their optimal locations are highly challenging issues. In this paper, a Mixed-Integer Non-Linear Programming formulation is provided, in which the DBSs’ location and the proper number of DBSs are jointly determined. An improved PSO-based algorithm is proposed to jointly optimize DBSs’ locations and find the minimum number of DBSs. As in the original PSO algorithm, the particles are randomly distributed in the initialization phase and a K-means-based clustering method is employed to generate the positions of the first-generation particles (DBSs). In addition, a custom communication protocol is presented for data exchange between the users’ equipment (UE) and the network controller. The proposed approach is evaluated through four simulation experiments implemented using Mininet-Wifi integrated with CopelliaSim. The acquired results show that the proposed solution based on the integration of PSO and K-means algorithms provides a low packet loss and latency. Moreover, it indicates that most of the users in the considered scenarios are covered by the DBSs.

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Code or data availability

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Notes

  1. https://www.coppeliarobotics.com/.

  2. https://github.com/ecwolf/SDN-DBS-p1/tree/PSO_continue/fig/select.

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Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001 and in part by Conselho Nacional de Desenvolvimento Científico e Tecnológico—Brasil (CNPq) Projects 309505/2020-8 and 420109/2018-8, and partially funded by Grant #2021/00199-8, São Paulo Research Foundation (FAPESP).

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Authors and Affiliations

  1. Department of Computer Science, Federal University Rio Grande do Sul (UFRGS), Porto Alegre, Brazil

    Faezeh Pasandideh & Edison Pignaton de Freitas

  2. Department 2 Lippstadt, Hamm-Lippstadt, University of Applied Sciences, Hamm, Germany

    Faezeh Pasandideh

  3. Department of “Technology and Systems”, Pk Nrw, Germany

    Faezeh Pasandideh

  4. Department of Electrical Engineering, Federal University Rio Grande do Sul (UFRGS), Porto Alegre, Brazil

    Pedro Henrique Morgan Pereira

  5. School of Electrical and Computer Engineering (FEEC), University of UNICAMP, Campinas, Brazil

    Fabricio E. Rodriguez Cesen & Christian Esteve Rothenberg

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  1. Faezeh Pasandideh
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Correspondence to Faezeh Pasandideh.

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Pasandideh, F., E. Rodriguez Cesen, F., Henrique Morgan Pereira, P. et al. An Improved Particle Swarm Optimization Algorithm for UAV Base Station Placement. Wireless Pers Commun 130, 1343–1370 (2023). https://doi.org/10.1007/s11277-023-10334-2

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