Adaptive mechanism design and game theoretic analysis of auction-driven dynamic spectrum access in cognitive radio networks

Wei Zhong, Youyun Xu, Jiaheng Wang, Dapeng Li, Huaglory Tianfield

    Research output: Contribution to journalArticle

    Abstract

    This paper studies the auction-driven dynamic spectrum access in cognitive radio networks with heterogeneous secondary users, who have different risk attitudes. First, a game theoretic framework is established for auction-driven dynamic spectrum access in cognitive radio networks. The utility functions and bidding strategies of heterogeneous secondary users are defined, and the parameterized auction mechanisms of primary user are also introduced. Then, we formulate the auction-driven dynamic spectrum access problem as a finite discrete game with a mixed- or pure-strategy Nash equilibrium solution. We study the existence and uniqueness properties of the pure-strategy Nash equilibrium in the defined game. Next, we propose a distributed learning automata algorithm (DLA) to attain the Nash equilibrium of the defined game with limited feedback. The adaptive mechanism design is realized in the updating procedure of our DLA algorithm. We further prove that our DLA algorithm converges to a Nash equilibrium of the defined game. Finally, simulation results show that our DLA algorithm is efficient and outperforms the dynamic spectrum access schemes with fixed auction mechanism.
    Original languageEnglish
    Article number44
    Number of pages14
    JournalEURASIP Journal on Wireless Communications and Networking
    Volume2014
    Issue number1
    Early online date24 Mar 2014
    DOIs
    Publication statusPublished - Dec 2014

    Fingerprint

    Cognitive radio
    Feedback

    Keywords

    • adaptive mechanism design
    • cognitive radio networks
    • Nash Equilibrium
    • wireless networks

    Cite this

    @article{56b0d84102ff4d56a5dc7dc628ff0cd5,
    title = "Adaptive mechanism design and game theoretic analysis of auction-driven dynamic spectrum access in cognitive radio networks",
    abstract = "This paper studies the auction-driven dynamic spectrum access in cognitive radio networks with heterogeneous secondary users, who have different risk attitudes. First, a game theoretic framework is established for auction-driven dynamic spectrum access in cognitive radio networks. The utility functions and bidding strategies of heterogeneous secondary users are defined, and the parameterized auction mechanisms of primary user are also introduced. Then, we formulate the auction-driven dynamic spectrum access problem as a finite discrete game with a mixed- or pure-strategy Nash equilibrium solution. We study the existence and uniqueness properties of the pure-strategy Nash equilibrium in the defined game. Next, we propose a distributed learning automata algorithm (DLA) to attain the Nash equilibrium of the defined game with limited feedback. The adaptive mechanism design is realized in the updating procedure of our DLA algorithm. We further prove that our DLA algorithm converges to a Nash equilibrium of the defined game. Finally, simulation results show that our DLA algorithm is efficient and outperforms the dynamic spectrum access schemes with fixed auction mechanism.",
    keywords = "adaptive mechanism design, cognitive radio networks, Nash Equilibrium, wireless networks",
    author = "Wei Zhong and Youyun Xu and Jiaheng Wang and Dapeng Li and Huaglory Tianfield",
    year = "2014",
    month = "12",
    doi = "10.1186/1687-1499-2014-44",
    language = "English",
    volume = "2014",
    journal = "EURASIP Journal on Wireless Communications and Networking",
    issn = "1687-1472",
    publisher = "Springer Open",
    number = "1",

    }

    Adaptive mechanism design and game theoretic analysis of auction-driven dynamic spectrum access in cognitive radio networks. / Zhong, Wei; Xu, Youyun; Wang, Jiaheng; Li, Dapeng; Tianfield, Huaglory.

    In: EURASIP Journal on Wireless Communications and Networking , Vol. 2014, No. 1, 44, 12.2014.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Adaptive mechanism design and game theoretic analysis of auction-driven dynamic spectrum access in cognitive radio networks

    AU - Zhong, Wei

    AU - Xu, Youyun

    AU - Wang, Jiaheng

    AU - Li, Dapeng

    AU - Tianfield, Huaglory

    PY - 2014/12

    Y1 - 2014/12

    N2 - This paper studies the auction-driven dynamic spectrum access in cognitive radio networks with heterogeneous secondary users, who have different risk attitudes. First, a game theoretic framework is established for auction-driven dynamic spectrum access in cognitive radio networks. The utility functions and bidding strategies of heterogeneous secondary users are defined, and the parameterized auction mechanisms of primary user are also introduced. Then, we formulate the auction-driven dynamic spectrum access problem as a finite discrete game with a mixed- or pure-strategy Nash equilibrium solution. We study the existence and uniqueness properties of the pure-strategy Nash equilibrium in the defined game. Next, we propose a distributed learning automata algorithm (DLA) to attain the Nash equilibrium of the defined game with limited feedback. The adaptive mechanism design is realized in the updating procedure of our DLA algorithm. We further prove that our DLA algorithm converges to a Nash equilibrium of the defined game. Finally, simulation results show that our DLA algorithm is efficient and outperforms the dynamic spectrum access schemes with fixed auction mechanism.

    AB - This paper studies the auction-driven dynamic spectrum access in cognitive radio networks with heterogeneous secondary users, who have different risk attitudes. First, a game theoretic framework is established for auction-driven dynamic spectrum access in cognitive radio networks. The utility functions and bidding strategies of heterogeneous secondary users are defined, and the parameterized auction mechanisms of primary user are also introduced. Then, we formulate the auction-driven dynamic spectrum access problem as a finite discrete game with a mixed- or pure-strategy Nash equilibrium solution. We study the existence and uniqueness properties of the pure-strategy Nash equilibrium in the defined game. Next, we propose a distributed learning automata algorithm (DLA) to attain the Nash equilibrium of the defined game with limited feedback. The adaptive mechanism design is realized in the updating procedure of our DLA algorithm. We further prove that our DLA algorithm converges to a Nash equilibrium of the defined game. Finally, simulation results show that our DLA algorithm is efficient and outperforms the dynamic spectrum access schemes with fixed auction mechanism.

    KW - adaptive mechanism design

    KW - cognitive radio networks

    KW - Nash Equilibrium

    KW - wireless networks

    U2 - 10.1186/1687-1499-2014-44

    DO - 10.1186/1687-1499-2014-44

    M3 - Article

    VL - 2014

    JO - EURASIP Journal on Wireless Communications and Networking

    JF - EURASIP Journal on Wireless Communications and Networking

    SN - 1687-1472

    IS - 1

    M1 - 44

    ER -