This work compares the application of Reinforcement Learning (RL) and Swarm Intelligence (SI) based methods for resolving the problem of coordinating multiple High Altitude Platform Stations (HAPS) for communications area coverage. Swarm coordination techniques are essential for developing autonomous capabilities for multiple HAPS/UAS control and management. This paper examines the performance of artificial intelligence (AI) capabilities of RL and SI for autonomous swarm coordination. In this work, it was observed that the RL approach showed superior overall peak user coverage with unpredictable coverage dips; while the SI based approach demonstrated lower coverage peaks but better coverage stability and faster convergence rates.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Comparative Study for Coordinating Multiple Unmanned HAPS for Communications Area Coverage


    Beteiligte:


    Erscheinungsdatum :

    01.06.2019


    Format / Umfang :

    2587406 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Situation Awareness and Routing Challenges in Unmanned HAPS/UAV based Communications Networks

    Anicho, Ogbonnaya / Charlesworth, Philip B / Baicher, Gurvinder S et al. | IEEE | 2020


    A Study on Cell Configuration for HAPS Mobile Communications

    Shibata, Yohei / Kanazawa, Noboru / Hoshino, Kenji et al. | IEEE | 2019



    Cylindrical Massive MIMO System for HAPS: Capacity Enhancement and Coverage Extension

    Tashiro, Koji / Hoshino, Kenji / Nagate, Atsushi | IEEE | 2021


    UAVs and HAPs - potential convergence for military communications

    Tozer, T. / Grace, D. / Thompson, J. et al. | IET Digital Library Archive | 2000