IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v86y2024i4d10.1007_s11235-024-01153-2.html
   My bibliography  Save this article

Communication coverage maximization in stadium environments using UAVs

Author

Listed:
  • Hamid Jafaripour

    (University of Kurdistan)

  • Mohammad Fathi

    (University of Kurdistan)

  • Ali Shariatpanah

    (University of Kurdistan)

Abstract

Maximizing the communication coverage with the minimum number of unmanned aerial vehicles (UAVs) in a telecommunication system is investigated in this paper. In particular, the problem of maximizing the coverage area in stadium environments using UAVs is modeled mathematically as a multi-objective optimization problem. While the problem is solved using state-of-the-art solvers, to address the problem complexity and achieve the results for real-time applications, we propose a heuristic algorithm. The performance evaluation done in three crowding levels demonstrates that the performance with the heuristic algorithm is comparable to the mathematical model in terms of the number of coverage users. Moreover, the running time is significantly smaller in the proposed heuristic algorithm. This shows the efficiency of the model and solution. Moreover, we compare the heuristic algorithm with the non-dominated sorting genetic algorithm (NSGAII). The results of the paper show that the use of the heuristic algorithm speeds up the processing and decision making, and at the same time maximizes the communication coverage in stadium environments.

Suggested Citation

  • Hamid Jafaripour & Mohammad Fathi & Ali Shariatpanah, 2024. "Communication coverage maximization in stadium environments using UAVs," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 86(4), pages 691-703, August.
    • Handle: RePEc:spr:telsys:v:86:y:2024:i:4:d:10.1007_s11235-024-01153-2
    DOI: 10.1007/s11235-024-01153-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-024-01153-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-024-01153-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:86:y:2024:i:4:d:10.1007_s11235-024-01153-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.