Greenly offloading traffic in stochastic heterogeneous cellular networks

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    1 Citation (Scopus)

    Abstract

    This paper puts forwards an on-line reinforcement learning framework for the problem of traf?c of?oading in a stochastic Markovian heterogeneous cellular network (HCN), where the time-varying traf?c demand of mobile terminals (MTs) can be of?oaded from macrocells to small-cells. Our aim is to minimize the average energy consumption of the HCN while maintaining the Quality-of-Service (QoS) experienced by MTs. For each cell (i.e., a macrocell or a small-cell), the energy consumption is determined by its system load which is coupled with the system loads served in other cells due to the sharing over a common frequency band. We model the energy-aware traf?c of?oading in such HCNs as a constrained Markov decision process (C-MDP). The statistics of the C-MDP depends on a selected traf?c of?oading strategy and thus, the actions performed by a network controller have a long-term impact on the network state evolution. Based on the traf?c demand observations and the traf?c of?oading operations, the controller gradually optimizes the strategy with no prior knowledge of the process statistics. Numerical experiments are conducted to show the effectiveness of the proposed learning framework in balancing the tradeoff between energy saving and QoS satisfaction
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publication1st International Workshop on Cognitive Cellular Systems, CCS 2014
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Number of pages5
    ISBN (Electronic)978-1-4799-4139-1
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    EventIEEE International Workshop on Cognitive Cellular Systems CCS 2014 - Rhine River, Germany
    Duration: 2 Sep 20144 Sep 2014

    Conference

    ConferenceIEEE International Workshop on Cognitive Cellular Systems CCS 2014
    Abbreviated titleCCS 2014
    CountryGermany
    CityRhine River
    Period2/09/144/09/14

    Keywords

    • energy consumption
    • macrocell networks
    • scattering
    • quality of service
    • telecommunication traffic
    • interference
    • switches

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