Abstract
Cognitive radio (CR) is wireless communication system that aims to introduce service to unlicensed users or secondary users (SUs) without harming operation of licensed users or primary users (PUs). Hence, the idea behind CR is to exploit unused resources of PUs at time or frequency at which PUs is not effected. Spectrum utilization can be accomplished by sharing of spectrum holes from (PUs) or primary service providers (PSPs) to (SUs) or secondary service provider (SSPs). Actually, spectrum sharing is considered as trading process in which spectrum seller charge free spectrum holes for spectrum buyers whom willing to buy spectrum for specified taxation called price. In this paper, pricing or (taxation) issue will be investigated through two different pricing schemes, namely, market-equilibrium and Bertrand competitive market. In market-equilibrium, the pricing depends on satisfying spectrum demand from SSPs/SUs by spectrum supply of PSPs. It is solved and analyzed in simplified way that reduces computational. Moreover, effect of bandwidth requirement of PUs on spectrum sharing will be studied. In Bertrand competitive market, PSPs tries to accomplish highest gain or payoff regarding to others by manipulating in price. In addition, genetic algorithm (GA) will be proposed with Bertrand competitive model to optimize pricing process to unique Nash Equilibrium by convergence with reducing abrupt change in price. GA improves best response strategy selection through reproduction process. Also, it reduces average pricing charged to SSP/SUs and this considered as attractive parameter for more spectrum selling and more gain to PSPs comparing round-robin algorithm.
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References
Haykin, S. (2005). Cognitive Radio: Brain-empowered wireless communications. IEEE Journal Select Area Communications, 23(2), 201–220.
Sakran, H., & Shokair, M. (2013). Hard and softened combination for cooperative spectrum sensing over imperfect channels in cognitive radio networks. Telecommunication Systems, 52(1), 61–71.
Sakran, H., Shokair, M., Nasr, O., El-Rabaie, S., & El-Azm, A. A. (2012). Proposed relay selection scheme for physical layer security in cognitive radio networks. IET Communications, 6(16), 2676–2687.
Sakran, H., & Shokair, M. (2011). “Proposed STBC with alamouti scheme in cognitive radio networks.” In 28th National Radio Science Conference (NRSC), pp. 192–199, Cairo, Egypt.
Niyato, D., & Hossain, E. (2008). Competitive pricing for spectrum sharing in cognitive radio networks: Dynamic game, inefficiency of nash equilibrium, and collusion. IEEE Journal on Selected Areas in Communications, 26(1), 192–202.
Pandit, S & Singh, G. (2013). “Spectrum sharing in Cognitive Radio using game theory,” In Advance Computing Conference (IACC), 2013 IEEE 3rd International, pp. 1503–1506.
Mackenzie & DaSilva, L. (2006). “Game Theory for wireless Engineers,” publication in the Morgan & Claypool publishers’ series.
Shoham, Y., & Leyton-Brown, K. (2008). Multiagent systems: Algorithmic, game-theoretic and logical foundations. Cambridge: Cambridge University Press.
Yu, F.R. (2011). “Cognitive Radio Mobile Ad Hoc Networks”, Carleton University, Ottawa, K1S 5B6 ON, Canada, Springer New York Dordrecht Heidelberg London, pp. 405–420.
Li, L., & Yu, L. (2011). “Pricing models based on Bertrand game under Dual-channel Environment,” Business Management and Electronic Information (BMEI), In International Conference, IEEE 2011, vol 3, (pp. 669–672).
Qun, Yu. (2013). A survey of cooperative games for cognitive radio networks. Wireless Personal Communications, 73(3), 949–966.
Niyato, D., Hossain, E., & Han, Z. (2009). Dynamic spectrum access and management in cognitive radio networks (pp. 186–188). Cambridge: Cambridge University Press.
Salem, A. A., Shokair, M., Elkordy, M., & El Halafawy, S. (2015). Profit of price with supermodular game for spectrum sharing in cognitive radio using genetic algorithm. Wireless Personal Communications. doi:10.1007/s11277-015-2367-5.
Goldsmith, A. J., & Chua, S.-G. (1997). Variable rate variable power MQAM for fading channels. IEEE Transactions on Communications, 45(10), 1218–1230.
Singh, N., & Vives, X. (1984). Price and quality competition in a differentiated duopoly. RAND Journal of Economics, 15, 546–554.
Levin, J. (2006). Supermodular games. Palo Alto: Stanford University.
Topkis, D. (1998). Supermodular and complementarity. Princeton: Princeton University Press.
Sharkey, W. W., & Sibley, D. S. (1993). A Bertrand model of pricing and entry. Economics Letterers, 41, 199–206.
Cheng, H., Yang, Q., Fu, F.,& Kwak, K.S. (2011). Spectrum sharing with smooth supermodular game in cognitive radio networks. In The 11th International Symposium on Communications & Information Technologies (ISCIT), IEEE, pp. 543–547.
Mitchell, M. (1999). An introduction to genetic algorithms,” Cambridge, Massachusetts, London, England, Fifth printing.
Sivanandam, S.N., & Deepa, S.N. (2008). Introduction to Genetic Algorithms. ISBN 978-3-540-73189-4 Springer, Berlin.
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Abdelaziz Salem, A., Shokair, M. Investigation of Pricing Issue Using Different Game Models in Cognitive Radio Network. Wireless Pers Commun 96, 4237–4249 (2017). https://doi.org/10.1007/s11277-017-4383-0
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DOI: https://doi.org/10.1007/s11277-017-4383-0