The need for load balancing in 5th generation (5G) networks is evident from the fact that the traffic load can vary over time and space. When the traffic demand varies over time and space, it can put a strain on certain parts of the network, and can lead to congestion, delays, and other performance issues. If one RRU or cell becomes overloaded with traffic, it can result in reduced performance and degraded user experience for the users connected to that RRU or cell. The need for less complex, simple, and flexible load balancing solutions in 5G networks is driven by the need to support and manage high volume of data under dynamic network conditions of complex 5G mobile networks. In this paper, we propose a simple-to-implement, flexible and fast-convergent algorithm for load balancing in scalable user-centric massive MIMO system. The evaluation results show that the proposed solution has very good load balancing capability and can converge to the desired solution very fast, for example, 3-5 iterations. The proposed load balancing framework is adaptable to many different types of networks such as conventional systems, coordinated joint transmission systems as well as clustered (overlapping, non-overlapping cluster of cells) cellular systems.


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    Titel :

    Low Cost Dynamic Load Balancing for User-Centric Wireless Systems


    Beteiligte:
    Kibria, Mirza Golam (Autor:in) / Jie, Xiong (Autor:in)


    Erscheinungsdatum :

    01.06.2023


    Format / Umfang :

    2782301 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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