In this work, we propose SVDNet, a novel deep learning (DL) architecture that utilizes singular value decomposition (SVD), for transmit power control in a multiuser multiple input multiple output (MU-MIMO) system. We propose a novel method of training SVDNet in a supervised manner for the power control task by using binary cross-entropy loss functions. SVDNet requires fewer computations than traditional power control algorithms such as weighted minimum mean squared error (WMMSE). Our simulation results show that the proposed SVDNet provides over a 50% increase in sum-rate performance as compared to similar supervised DL-based power control schemes while being significantly more computationally efficient than WMMSE.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    SVDNet: Deep Power Control for Multiuser MIMO


    Beteiligte:


    Erscheinungsdatum :

    2023-06-01


    Format / Umfang :

    2407483 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Blind Iterative Receiver for Multiuser MIMO Systems

    Khan, E. / Slock, D. / IEEE | British Library Conference Proceedings | 2003





    Multiuser MIMO Indoor Visible Light Communication System Using Spatial Multiplexing

    Lian, J. / Brandt-Pearce, M. | British Library Online Contents | 2017