Game Theory for Networks. 2nd International ICST Conference, GAMENETS 2011, Shanghai, China, April 16-18, 2011, Revised Selected Papers

Research Article

Channel Assignment on Wireless Mesh Network Backbone with Potential Game Approach

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  • @INPROCEEDINGS{10.1007/978-3-642-30373-9_4,
        author={Pedro Duarte and Zubair Fadlullah and Athanasios Vasilakos and Nei Kato},
        title={Channel Assignment on Wireless Mesh Network Backbone with Potential Game Approach},
        proceedings={Game Theory for Networks. 2nd International ICST Conference, GAMENETS 2011, Shanghai, China, April 16-18, 2011, Revised Selected Papers},
        proceedings_a={GAMENETS},
        year={2012},
        month={10},
        keywords={Wireless Mesh Networks channel assignment problem partially overlapped channels game theory potential games},
        doi={10.1007/978-3-642-30373-9_4}
    }
    
  • Pedro Duarte
    Zubair Fadlullah
    Athanasios Vasilakos
    Nei Kato
    Year: 2012
    Channel Assignment on Wireless Mesh Network Backbone with Potential Game Approach
    GAMENETS
    Springer
    DOI: 10.1007/978-3-642-30373-9_4
Pedro Duarte1,*, Zubair Fadlullah1, Athanasios Vasilakos2, Nei Kato1
  • 1: Tohoku University
  • 2: University of Western Macedonia
*Contact email: burjack@it.ecei.tohoku.ac.jp

Abstract

The Wireless Mesh Network (WMN) has already been recognized as a promising technology as broadband access network from both academic and industry points of view. In order to improve its performance, research has been carried on how to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. Considering WMNs based upon IEEE 802.11 b/g standards, lately most of researchers have been relying on the usage of orthogonal channels for solving the Channel Assignment (CA) problem. However, in this paper, we introduce a novel CA algorithm exploiting partially overlapped channels (POC) that overcome the common orthogonal channel approach. This algorithm is derived based on Game Theory framework using Potential Games and yields near optimum CA.