In this paper, we delve into the domain of heterogeneous drone-enabled aerial base stations, each equipped with varying transmit powers, serving as downlink wireless providers for ground users. A central challenge lies in strategically selecting and deploying a subset from the available drone base stations (DBSs) to meet the downlink data rate requirements while minimizing the overall power consumption. To tackle this, we formulate an optimization problem to identify the optimal subset of DBSs, ensuring wireless coverage with an acceptable transmission rate in the downlink path. Moreover, we determine their 3D positions for power consumption optimization. Assuming DBSs operate within the same frequency band, we introduce an innovative, computationally efficient beamforming method to mitigate intercell interference in the downlink. We propose a Kalai–Smorodinsky bargaining solution to establish the optimal beamforming strategy, compensating for interference-related impairments. Our simulation results underscore the efficacy of our solution and offer valuable insights into the performance intricacies of heterogeneous drone-based small-cell networks.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction


    Beteiligte:
    Nima Namvar (Autor:in) / Fatemeh Afghah (Autor:in) / Ismail Guvenc (Autor:in)


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Optimal Deployment Density for Maximum Coverage of Drone Small Cells

    Xie, Jiejie / Dong, Chao / Li, Aijing et al. | IEEE | 2017


    Dynamic base station repositioning to improve spectral efficiency of drone small cells

    Fotouhi, Azade / Ding, Ming / Hassan, Mahbub | IEEE | 2017


    Optimal Placement of Drone Delivery Stations and Demand Allocation using Bio-inspired Algorithms

    Elsaid, Feras / Sanchez, Enrique Torres / Li, Yilun et al. | IEEE | 2023


    Orchestration in heterogeneous drone swarms

    VAUGHN ROBERT LAWSON / CARBIN PAUL / WOUHAYBI RITA H | Europäisches Patentamt | 2021

    Freier Zugriff

    ORCHESTRATION IN HETEROGENEOUS DRONE SWARMS

    VAUGHN ROBERT LAWSON / CARBIN PAUL / WOUHAYBI RITA H | Europäisches Patentamt | 2019

    Freier Zugriff