Access point selection game based on bandwidth restrictions
Keywords:
Bandwidth, nash equilibrium, noncooperative games, 802.11 wireless networks, access point selection, game theory
Abstract
This article describes the results of the selection of a access point in 802.11 wireless networks multicell, which are currently facing the progressive saturation of the radio spectrum due to overcrowding User. This problem is addressed from the perspective of the theory of noncooperative games where users (transmitter devices) are the players and the possible discrete values of bandwidth defined in the system, strategies that they have to play, whereby, for the channeling defined in 802.11g, and considering only the nonoverlapping channels, three cases are identified depending on the number of channels or amount of bandwidth the user to choose. For game solution concept of Nash Equilibrium (NE) is introduced, the existence of the proposed model is verified and the computational algorithm designed in Matlab mathematical tool proposed, that solves the problem of association under this concept. Particularly, in this game seeks to maximize the utility for each user, in order to find from this perspective, the solution to the problem raised, in this scenario, it is verified that selected access point from perspective of Nash equilibrium will be the one to present the best channel conditions gain using the strategy of using the maximum available bandwidth.Downloads
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References
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[3] Perlaza, S. Belmega, E. Lasaulce, S. Debbah, M. “On the base station selection and base station sharing in self-configuring networks,” in 3rd ICST/ACM International Workshop on Game Theory in Communication Networks. Pisa, Italy, October 2009.
[4] Li-Hsing Yen, Jia-Jun Li, and Che-Ming Lin, “Stability and fairness of native AP selection games in IEEE 802.11 access networks,” in Wireless and Optical Communications Networks (WOCN), Colombo, pp. 1-5, 2010. DOI: 10.1109/WOCN.2010.5587341.
[5] Lin Gao, Xinbing Wang, Gaofei Sun and Youyun Xu, “A game approach for cell selection and resource allocation in heterogeneous wireless networks,” in Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 8th Annual IEEE Communications Society Conference, Salt Lake City, UT., pp. 530-538, 2011. DOI: 10.1109/SAHCN.2011.5984939.
[6] E. Jocelyne, F. Martignon and E. Altman, “Joint pricing and cognitive radio network selection: a game theoretical approach,” in Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), 10th International Symposium, Paderborn, Germany, pp. 49-53, 2012.
[7] D. L. Trujillo, “Selección de Access Point en redes 802.11 garantizando mínima capacidad para QoS: una perspectiva desde la teoría de juegos no cooperativos,” thesis, Universidad del Quindío, Armenia, Colombia. 2012.
[8] D. Monderer, “Potential Games.” Games and Economic Behavior, vol. 14, pp.124-143, 1996.
[9] S. Ross and B, Chaib-Draa, “Learning to play a satisfaction equilibrium,” in Computer Science Department. PLT Bdg, Laval University, Quebec, PQ, Canada, 2010.
[10] I. Menache and A. “Network games. Theory, models, and dynamics,” Jean Walrand, Series Editor, pp. 69, 2010.
[11] D. Amzallag, R. Bar-Yehuda, D. Raz, and G. Scalosub, “Cell Selection in 4G Cellular Networks,” in Proceeding of the Annual IEEE 27th INFOCOM, Hong Kong, pp. 700-708, 2008.
[12] P. Mertikopoulos, E. Belmega, A. Moustakas, and S. Lasaulce, “Dynamic power allocation games in parallel multiple access channels,” in VALUETOOLS ‘11 Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools, Brussels, Belgium, pp. 332-341, 2011.
[13] Grupo de Investigación Eumednet. Universidad de Málaga, Introducción a la teoría de juegos. 2012 [Online]. Available: http://www.eumed.net/cursecon/juegos/index.htm
[14] J. Pérez, J. Jimeno, and E. Cerdá, “El equilibrio de Nash” Teoría de Juegos, Cap. 2, Madrid, España: Pearson, 2004, p. 89.
[15] H. Rohling, OFDM Concepts for Future Communication Systems, New York: Springer Heidelberg, 2011, p. 5.
[16] R. Nee, R. Prasad, OFDM for Wireless Multimedia Communications. Artech House, 2000, p. 229.
[17] M. Rodríguez, Introducción Rápida a Matlab y Simulink para Ciencia e Ingeniería. Ediciones Díaz de Santos, S.A. Madrid, 2003.
[18] S. Lasaulce, M. Debbah and E. Altman, “Methodologies for analyzing equilibria in wireless games,” Signal Processing Magazine, IEEE, vol. 26, no. 5, pp. 41-52, 2009. DOI 10.1109/MSP.2009.933496
[19] J. Pérez, J. Jimeno, and E. Cerdá, “Teoremas de existencia del equilibrio de Nash”, Teoría de Juegos, Cap. 3. Madrid, España: Pearson, 2004, pp.170-175.
[20] E. Astaiza. “Introducción a la teoría de juegos en comunicaciones inalámbricas, Cap. 5 Existencia del Equilibrio de Nash”, Univ. del Quindío, Armenia, Quindío, 2013, pp. 25-26.
[21] D. Monderer, “Potential games,” Games and Economic Behavior, vol. 14, pp. 124-143, 1996.
[22] R. Cheng and S. Verdu, “Gaussian multiaccess channels with isi: capacity region and multiuser water-filling,” IEEE Trans. On Info. Theory, vol. 39, no. 3, pp. 773-785, May. 1993.
[23] C. E. Shannon. Communication theory of secrecy systems. Bell Syst. Tech.J., vol. 28, pp. 656-715, 1949.
[24] M. S. Pinsker. Information and Stability of Random Variables and Processes. Izd. Akad. Nauk, 1960. Translated by A. Feinstein, 1964.
Published
2016-04-04
How to Cite
Astaiza-Hoyos, E., Bermúdez-Orozco, H., & Muñoz-Sanabria, L. (2016). Access point selection game based on bandwidth restrictions. ITECKNE, 13(1), 74-82. https://doi.org/https://doi.org/10.15332/iteckne.v13i1.1384
Issue
Section
Research and Innovation Articles
