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    A QoE-Aware Joint Resource Allocation and Dynamic Pricing Algorithm for Heterogeneous Networks

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    Date
    2017
    Author
    Trakas, Panagiotis
    Adelantado, Ferran
    Zorba, Nizar
    Verikoukis, Christos
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    Abstract
    The rise of third-party content providers and the introduction of numerous applications has been driving the growth of mobile data traffic in the past few years. The applications' various Quality of Service (QoS) requirements as well as the use of multiple devices per user have increased the traffic heterogeneity, pressing the telecommunications industry to the deployment of dense Heterogeneous Networks (HetNets). At the same time, the content providers' rise has also led to the decrease of the Mobile Network Operators' (MNOs) revenues. Under these circumstances, the MNOs need to guarantee the users' Quality of Experience (QoE) requirements, while ensuring the sustainability of HetNet investments. To this end, we consider a HetNet deployment where MNOs offer a multitude of services with diverse pricing. We propose a heuristic, joint QoE-aware resource allocation and dynamic pricing algorithm with overall user satisfaction constraints to maximize the MNO profit, while providing high QoE. Simulation results show that the proposed algorithm can handle traffic heterogeneity by achieving substantial profit and QoE gains, compared to a state of the art algorithm. Moreover, we demonstrate the benefits of our dynamic pricing scheme and its applicability on other resource allocation algorithms.
    DOI/handle
    http://dx.doi.org/10.1109/GLOCOM.2017.8254131
    http://hdl.handle.net/10576/17509
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    • Electrical Engineering [‎2840‎ items ]

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