This paper addresses the problem of cell zooming in green networks. We apply a state-of-the-art methodology, distributed optimization, to solve the privacy-preserved cell zooming issue in green networks. To this end, we approximate the cell zooming problem by a certain convex problem. We also develop a data masking technique, under which we can still obtain a correct solution of the convex problem. The proposed method outperforms a Q-learning-based approach in terms of energy efficiency and the charging rate of batteries.


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    Titel :

    Privacy-Preserved Cell Zooming with Distributed Optimization in Green Networks


    Beteiligte:
    Wakaiki, Masashi (Autor:in) / Suto, Katsuya (Autor:in) / Masubuchi, Izumi (Autor:in)


    Erscheinungsdatum :

    01.09.2019


    Format / Umfang :

    386414 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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