Unmanned aerial vehicle (UAV) carrying intelligent reflecting surface (IRS) can serve as an aerial platform to improve the coverage area and transmission performance of traditional wireless network. In this paper, we investigate the weighted sum rate maximization problem for a UAV-assisted and IRS-based multi-user communication system. Specifically, by applying the alternating optimization approach, we propose a two-phase approach to effectively optimize the number of activated reflective elements, the precoding matrix, the phase shift, and the UAV location. Numerical results validate that the proposed approach can converge at a faster rate and improve the weighted sum rate performance.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    UAV-Based Intelligent Reflecting Surface Transmission: Weighted Sum Rate Maximization of Wireless Network


    Beteiligte:
    Wang, Wen-Jing (Autor:in) / Du, Ziyang (Autor:in) / Li, Sha (Autor:in) / Lu, Guangyue (Autor:in) / Chen, Long (Autor:in) / Qi, Nan (Autor:in)


    Erscheinungsdatum :

    01.09.2022


    Format / Umfang :

    1453704 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Multigroup Multicast Transmission via Intelligent Reflecting Surface

    Li, Ding / An, Qiaochu / Shi, Yuanming et al. | IEEE | 2020


    Transmission Rate Maximization in Self-Backhauled Wireless Small Cell Networks

    Lashgari, Maryam / Maham, Behrouz / Saad, Walid | IEEE | 2017


    Intelligent Reflecting Surfaces in Wireless Communication Systems

    Li, Yueheng | DataCite | 2024

    Freier Zugriff

    Intelligent Reflecting Surface Joint Uplink-Downlink Optimization for NOMA Network

    Samy, Mostafa / Abo-Zahhad, Mohammed / Muta, Osamu et al. | IEEE | 2022


    Intelligent Reflecting Surface assisted V2X Communication

    Dhruvakumar, T / Ojha, Abhijeet / Raj, Anant et al. | IEEE | 2024