Low latency is a critical requirement of beyond 5G services. Previously, the aspect of latency has been extensively analyzed in conventional and modern wireless networks. With the rapidly growing research interest in wireless-powered ambient backscatter communications, it has become ever more important to meet the delay constraints, while maximizing the achievable data rate. Therefore, to address the issue of latency in backscatter networks, this paper provides a deep Q-learning based framework for delay constrained ambient backscatter networks. To do so, a Q-learning model for ambient backscatter scenario has been developed. In addition, an algorithm has been proposed that employ deep neural networks to solve the complex Q-network. The simulation results show that the proposed approach not only improves the network performance but also meets the delay constraints for a dense backscatter network.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Low Latency Ambient Backscatter Communications with Deep Q-Learning for Beyond 5G Applications


    Beteiligte:
    Jameel, Furqan (Autor:in) / Jamshed, Muhammad Ali (Autor:in) / Chang, Zheng (Autor:in) / Jantti, Riku (Autor:in) / Pervaiz, Haris (Autor:in)


    Erscheinungsdatum :

    01.05.2020


    Format / Umfang :

    290920 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Performance Analysis of IRS-assisted Multi-tag Ambient Backscatter Communications

    Altuwairgi, Khaled Humaid / Khel, Ahmad Massud Tota / Hamdi, Khairi Ashour | IEEE | 2022




    Integration of Visible Light and Backscatter Communications for Ambient Internet of Things

    Xie, Boxuan / Dowhuszko, Alexis / Koskinen, Kalle et al. | IEEE | 2024


    Ambient RF backscatter communication for vehicle remote control

    ELANGOVAN VIVEKANANDH / DELONG AARON M / VAN WIEMEERSCH JOHN R | Europäisches Patentamt | 2020

    Freier Zugriff