Heterogeneous network (HetNet) has been proposed as a promising solution for handling the wireless traffic explosion in future fifth-generation (5G) system. In this paper, a joint subchannel and power allocation problem is formulated for HetNets to maximize the energy efficiency (EE). By decomposing the original problem into a classification subproblem and a regression subproblem, a convolutional neural network (CNN) based approach is developed to obtain the decisions on subchannel and power allocation with a much lower complexity than conventional iterative methods. Numerical results further demonstrate that the proposed CNN can achieve similar performance as the Exhaustive method, while needs only 6.76% of its CPU runtime.


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    Titel :

    Energy-Efficient Subchannel and Power Allocation for HetNets Based on Convolutional Neural Network


    Beteiligte:
    Xu, Di (Autor:in) / Chen, Xiaojing (Autor:in) / Wu, Changhao (Autor:in) / Zhang, Shunqing (Autor:in) / Xu, Shugong (Autor:in) / Cao, Shan (Autor:in)


    Erscheinungsdatum :

    01.04.2019


    Format / Umfang :

    836242 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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