Due to the rapid growth of mobile technology, unmanned aerial vehicles(UAV) is emerging as a promising solution to distribute wireless data for ground users as a base station (BS). Our study focuses on the analysis of UAV-based BS that assist aerial wireless network. We practically used the real data measurement from the UAVs connected with ground mobile users as air-to- ground(A2G) communication service. The main aim of our work is to analyze and estimate the UAV-BS user throughput with different parameters such as height and distance. In order to achieve our objective, we have estimated the locations of UAVs’ and mobile-users’, heights of UAV, elevation angle and nature of LoS/NLoS. The system performances are evaluated through long short term memory(LSTM) and comparison was made with multi- layer perceptron(MLP) algorithm. Finally, the evaluation result shows the system has accurate and motivated prediction performances of the user throughput.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Deep Learning-Based Throughput Estimation for UAV-Assisted Network




    Publication date :

    2019-09-01


    Size :

    864895 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    UAV-Assisted Hybrid Throughput Optimization Based on Deep Reinforcement Learning

    Zhang, Zhilan / Liu, Shuo / Luo, Yizhe et al. | IEEE | 2023


    Cognitive Radio Network Throughput Maximization with Deep Reinforcement Learning

    Ong, Kevin Shen Hoong / Zhang, Yang / Niyato, Dusit | IEEE | 2019


    THROUGHPUT ESTIMATION DEVICE AND THROUGHPUT ESTIMATION METHOD

    SUZUKI HIROSHI / ISHINO MASANORI / IGARASHI YUICHI et al. | European Patent Office | 2023

    Free access


    Machine-Learning-Based Throughput Estimation Using Images for mmWave Communications

    Okamoto, Hironao / Nishio, Takayuki / Morikura, Masahiro et al. | IEEE | 2017