In this paper, we investigate the outage performance of an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) uplink, in which a group of the surface reflecting elements are configured to boost the signal of one of the user equipments (UEs), while the remaining elements are used to boost the other UE. By approximating the received powers as Gamma random variables, tractable expressions for the outage probability under NOMA interference cancellation are obtained. We evaluate the outage over different splits of the elements and varying pathloss differences between the two UEs. The analysis shows that for small pathloss differences, the split should be chosen such that most of the IRS elements are configured to boost the stronger UE, while for large pathloss differences, it is more beneficial to boost the weaker UE. Finally, we investigate a robust selection of the elements’ split under the criterion of minimizing the maximum outage between the two UEs.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Outage Analysis of Uplink IRS-Assisted NOMA under Elements Splitting


    Beteiligte:
    Tahir, Bashar (Autor:in) / Schwarz, Stefan (Autor:in) / Rupp, Markus (Autor:in)


    Erscheinungsdatum :

    01.04.2021


    Format / Umfang :

    2383892 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Resource Allocation for NOMA Networks under Alternative Outage Constraints

    Cui, Fangyu / Qin, Zhijin / Cai, Yunlong et al. | IEEE | 2019


    Interference Modeling and Outage Analysis for 5G Downlink NOMA

    Anwar, Asim / Seet, Boon-Chong / Li, Xue Jun | IEEE | 2017



    Outage and Throughput Analysis of UAV-Assisted NOMA Relay Systems With Indoor and Outdoor Users

    Hoang, Tran Manh / Dung, Le The / Nguyen, Ba Cao et al. | IEEE | 2023


    optimizing IRS-Assisted Uplink NOMA System for Power Constrained IoT Networks

    AlaaEldin, Mahmoud / Alsusa, Emad / Seddik, Karim G. et al. | IEEE | 2022