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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Adaptive Cooperative Spectrum Sharing Based on Fairness and Total Profit in Cognitive Radio Networks

  • Chen, Jian (School of Telecommunication Engineering, Xidian University) ;
  • Zhang, Xiao (School of Telecommunication Engineering, Xidian University) ;
  • Kuo, Yonghong (School of Telecommunication Engineering, Xidian University)
  • Received : 2009.11.06
  • Accepted : 2010.04.19
  • Published : 2010.08.30
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Abstract

A cooperative model is presented to enable sharing of the spectrum with secondary users. Compared with the optimal model and competitive model, the cooperative model could reach the maximum total profit for secondary users with better fairness. The cooperative model is built based on the Nash equilibrium. Then a conceding factor is introduced so that the total spectrum required from secondary users will decrease. It also results in a decrease in cost which the primary user charges to the secondary users. The optimum solution, which is the maximum total profit for the secondary users, is called the collusion state. It is possible that secondary users may leave the collusion state to pursue the maximum of individual profit. The stability of the algorithm is discussed by introducing a vindictive factor to inhabit the motive of deviation. In practice, the number of secondary users may change. Adaptive methods have been used to deal with the changing number of secondary users. Both the total profit and fairness are considered in the spectrum allocating. The shared spectrum is 11.3893 with a total profit of 65.2378 in the competitive model. In the cooperative model, the shared spectrum is 8.5856 with the total profit of 73.4963. The numerical results reveal the effectiveness of the cooperative model.

Keywords

References

  1. S. Haykin "Cognitive Radio: Brain-Empowered Wireless Communications," IEEE J. Select. Areas Commun., vol. 23, no. 2, 2005, pp. 201-220.
  2. I.F. Akyildiz et al., "A Survey on Spectrum Management in Cognitive Radio Networks," IEEE Commun. Mag., Apr. 2008, pp. 40-48.
  3. D. Niyato and E. Hossain, "Spectrum Trading in Cognitive Radio Networks: A Market-Equilibrium-based Approach," IEEE Wireless Commun., 2008, pp. 71-80.
  4. D. Niyato and E. Hossain, "Market-Equilibrium, Competitive, and Cooperative Pricing for Spectrum Sharing in Cognitive Radio Networks: Analysis and Comparison," IEEE Trans. Wireless Commun., vol. 7, no. 11, 2008, pp. 4273-4283. https://doi.org/10.1109/T-WC.2008.070546
  5. J. Neel, J.H. Reed, and R.P. Gilles, "The Role of Game Theory in the Analysis of Software Radio Networks," SDR Forum Technical Conf., vol. 2, 2002, pp. NP-3-02.
  6. J. Ned, J.H. Reed, and R.P. Gilles, "Convergence of Cognitive Radio Networks," Wireless Commun. Networking Conf., vol. 4, 2004, pp. 2250-2255.
  7. L. Cao and H. Zheng, "Distributed Spectrum Allocation via Logical Bargaining," Proc. IEEE SECON, 2005, pp. 475-486.
  8. W. Wang and X. Liu, "List-Coloring Based Channel Allocation for Open-Spectrum Wireless Networks," 62nd IEEE Vehicular Technol. Conf., vol. 1, 2005, pp. 690-694.
  9. D. Niyato and E. Hossain, "Competitive Pricing for Spectrum Sharing in Cognitive Radio Networks: Dynamic Game, Inefficiency of Nash Equilibrium, and Collusion," IEEE J. Select. Areas Commun., vol. 26, no. 1, 2008, pp. 192-202. https://doi.org/10.1109/JSAC.2008.080117
  10. D. Niyato and E. Hossain, "Competitive Spectrum Sharing in Cognitive Radio Networks: A Dynamic Game Approach," IEEE Trans. Wireless Commun., vol. 7, no. 7, 2008, pp. 2651-2660. https://doi.org/10.1109/TWC.2008.070073
  11. Z. Xie, Game Theory in Economics, 2nd ed., Shanghai People Publishing Press, 2002.
  12. A. Cournot, "Researches into the Mathematical Principles of the Theory of Wealth," NY, USA: MacMillan, 1927

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