Optimal base station sleeping in green cellular networks: A distributed cooperative framework based on game theory

Jianchao Zheng, Yueming Cai, Xianfu Chen, Rongpeng Li, Honggang Zhang

    Research output: Contribution to journalArticleScientificpeer-review

    52 Citations (Scopus)

    Abstract

    This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.
    Original languageEnglish
    Pages (from-to)4391-4406
    JournalIEEE Transactions on Wireless Communications
    Volume14
    Issue number8
    DOIs
    Publication statusPublished - 2015
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    Game theory
    Game Theory
    Cellular Networks
    Nash Equilibrium
    Base stations
    Game
    Energy Saving
    Traffic
    Potential Games
    Global Optimum
    Self-organization
    Energy Efficiency
    Iterative Algorithm
    Decentralized
    Energy Consumption
    Optimality
    Theoretical Analysis
    Energy conservation
    Optimal Solution
    Maximise

    Keywords

    • base station sleeping
    • decentralized algorithm
    • distributed cooperation
    • energy efficiency
    • generalized Nash equilibrium
    • green cellular networks
    • potential game

    Cite this

    @article{a253ff1dae74498c8ca610e6f0ed54d7,
    title = "Optimal base station sleeping in green cellular networks: A distributed cooperative framework based on game theory",
    abstract = "This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.",
    keywords = "base station sleeping, decentralized algorithm, distributed cooperation, energy efficiency, generalized Nash equilibrium, green cellular networks, potential game",
    author = "Jianchao Zheng and Yueming Cai and Xianfu Chen and Rongpeng Li and Honggang Zhang",
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    year = "2015",
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    language = "English",
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    pages = "4391--4406",
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    Optimal base station sleeping in green cellular networks : A distributed cooperative framework based on game theory. / Zheng, Jianchao; Cai, Yueming; Chen, Xianfu; Li, Rongpeng; Zhang, Honggang.

    In: IEEE Transactions on Wireless Communications, Vol. 14, No. 8, 2015, p. 4391-4406.

    Research output: Contribution to journalArticleScientificpeer-review

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    AU - Zheng, Jianchao

    AU - Cai, Yueming

    AU - Chen, Xianfu

    AU - Li, Rongpeng

    AU - Zhang, Honggang

    N1 - Project code: 101914

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    N2 - This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.

    AB - This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.

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