This chapter provides the use of intelligent algorithms to determine the best position of unmanned aerial vehicles (UAVs) which can be used to enhance the capabilities of existing cellular networks. It presents an intelligent positioning algorithm based on reinforcement learning (RL) and evaluates its performance in an emergency communication network (ECN) scenario. The chapter also presents future applications of UAVs in cellular networks and the state‐of‐the‐art of positioning systems for UAVs in communication networks. It contains a brief summary of how RL works and results of simulations in an ECN scenario. It is clear from the simulations that using intelligent positioning algorithms based on RL is a viable strategy for that. However, more research is needed to design intelligent solutions which can improve multiple KPIs and generalize from past experiences at the same time.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Intelligent Positioning of UAVs for Future Cellular Networks




    Publication date :

    2019-08-12


    Size :

    16 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





    UAVs: The Future

    Online Contents | 2003


    Vision-based Positioning for UAVs

    Hu, Xiao | BASE | 2021

    Free access

    INTELLIGENT AUTONOMY FOR UAVs

    Pawlowski, A. / Pridmore, L. / Franke, J. et al. | British Library Conference Proceedings | 2003


    GPS Relative Positioning System for UAVs

    Chen, G. / Harigae, M. / Japan Society for Aeronautical and Space Services | British Library Conference Proceedings | 2000