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Access Point Selection Game with Mobile Users Using Correlated Equilibrium

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  • Insoo Sohn

Abstract

One of the most important issues in wireless local area network (WLAN) systems with multiple access points (APs) is the AP selection problem. Game theory is a mathematical tool used to analyze the interactions in multiplayer systems and has been applied to various problems in wireless networks. Correlated equilibrium (CE) is one of the powerful game theory solution concepts, which is more general than the Nash equilibrium for analyzing the interactions in multiplayer mixed strategy games. A game-theoretic formulation of the AP selection problem with mobile users is presented using a novel scheme based on a regret-based learning procedure. Through convergence analysis, we show that the joint actions based on the proposed algorithm achieve CE. Simulation results illustrate that the proposed algorithm is effective in a realistic WLAN environment with user mobility and achieves maximum system throughput based on the game-theoretic formulation.

Suggested Citation

  • Insoo Sohn, 2015. "Access Point Selection Game with Mobile Users Using Correlated Equilibrium," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-13, March.
  • Handle: RePEc:plo:pone00:0116592
    DOI: 10.1371/journal.pone.0116592
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    References listed on IDEAS

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    1. Sergiu Hart & Andreu Mas-Colell, 2013. "A Simple Adaptive Procedure Leading To Correlated Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 2, pages 17-46, World Scientific Publishing Co. Pte. Ltd..
    2. Sergiu Hart & Andreu Mas-Colell, 2013. "A General Class Of Adaptive Strategies," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 3, pages 47-76, World Scientific Publishing Co. Pte. Ltd..
    3. Zhi-Qin Ma & Cheng-Yi Xia & Shi-Wen Sun & Li Wang & Huai-Bin Wang & Juan Wang, 2011. "Heterogeneous Link Weight Promotes The Cooperation In Spatial Prisoner'S Dilemma," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 22(11), pages 1257-1268.
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    Cited by:

    1. Insoo Sohn & Huaping Liu & Nirwan Ansari, 2015. "Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-13, July.

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