Unmanned aerial vehicle (UAV)-assisted communications is a promising solution to improve the performance of future wireless networks, where UAVs are deployed as base stations for enhancing the quality of service (QoS) provided to ground users when traditional terrestrial base stations are unavailable or not sufficient. An effective framework is proposed in this paper to manage the dynamic movement of multiple unmanned aerial vehicles (UAVs) in response to ground user mobility, with the objective to maximize the sum data rate of the ground users. First, we discuss the relationship between the air-to-ground (A2G) path loss (PL) and the location of UAVs. Then a deep Q-network (DQN) based method is proposed to adjust the locations of UAVs to maximize the sum data rate of the user equipment (UE). Finally, simulation results show that the proposed method is capable of adjusting UAV locations in a real-time condition to improve the QoS of the entire network.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Deep Q-Network Based Dynamic Movement Strategy in a UAV-Assisted Network


    Contributors:


    Publication date :

    2020-11-01


    Size :

    1283481 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Deep Learning-Based Throughput Estimation for UAV-Assisted Network

    Munaye, Yirga Yayeh / Adege, Abebe Belay / Tarekegn, Getaneh Berie et al. | IEEE | 2019


    Road network dynamic traffic distribution method based on Encoder-Decoder deep neural network

    XIA JINGXIN / CHENG MIN / WANG YINPU et al. | European Patent Office | 2021

    Free access


    Multi-objective optimization for autonomous driving strategy based on Deep Q Network

    Hu, Tianmeng / Luo, Biao / Yang, Chunhua | Springer Verlag | 2021

    Free access

    Deep Q‐network based multi‐layer safety lane changing strategy for vehicle platoon

    Zhang, Jinqi / Yan, Maode / Zuo, Lei | Wiley | 2024

    Free access