This paper studies distributed optimization of an uplink cell-free Massive MIMO (CF-mMIMO) network. By observing some interesting analogies between the CF network and an artificial neural network (ANN), we propose to relate the uplink CF network to a so-called quasi-neural network. Borrowing the idea of the back-propagation (BP) algorithm, we propose a novel scheme to optimize the central processing unit (CPU) and the access points (APs) of the network. The proposed scheme can achieve multi-AP cooperation using only the pilot sequences, but without the channel state information (CSI). To reduce the required throughput of the fronthaul, we let each AP beamform the received vector signals into scalar ones before passing them to the CPU. The effectiveness of the proposed scheme is verified by the simulations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Distributed optimization of Uplink Cell-Free Massive MIMO Networks


    Beteiligte:
    Wang, Rui (Autor:in) / Jiang, Yi (Autor:in)


    Erscheinungsdatum :

    2022-09-01


    Format / Umfang :

    364361 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Uplink Power Allocation Scheme for User-Centric Cell-free Massive MIMO Systems

    Sarker, Manobendu / Fapojuwo, Abraham O. | IEEE | 2022


    Evaluation of Uplink Capacity of User-Cluster-Centric Cell-Free massive MIMO

    Takahashi, Ryo / Matsuo, Hidenori / Xia, Sijie et al. | IEEE | 2022


    Design of Generalized Superimposed Training for Uplink Cell-free Massive MIMO Systems

    Ge, Hanxiao / Garg, Navneet / Ratnarajah, Tharmalingam | IEEE | 2022


    Fronthaul Load-Reduced Scalable Cell-Free massive MIMO by Uplink Hybrid Signal Processing

    Kanno, Issei / Ito, Masaaki / Ohseki, Takeo et al. | IEEE | 2022