Wireless Networks

, Volume 22, Issue 3, pp 755–764 | Cite as

Cooperative primary–secondary dynamic spectrum leasing game via decentralized bargaining

  • Seyyed Mohammadreza Azimi
  • Mohammad Hossein Manshaei
  • Faramarz Hendessi


Dynamic spectrum leasing (DSL) has been proposed as a solution for better spectrum utilization. Most of the work focused on non-cooperative game to model primary/secondary users interactions in DSL approach. Some others introduced cooperative game just for secondary users (SUs). In this paper, both primary users (PUs) and SUs incentives and level of satisfactions are considered. Nash bargaining is developed with both PUs and SUs as bargainers. A simple pricing approach is introduced which makes the proposed method practically feasible. On one hand, SUs adjust their power regarding to price and tolerable interference which are announced by PU. On the other hand, PU adjusts its tolerable interference to maximize its profit. Simulation results verify the viability of proposed method.


Cognitive radio Dynamic spectrum leasing Game theory Nash bargaining solution 


  1. 1.
    Simeone, O., Stanojev, I., Savazzi, S., Bar-Ness, Y., Spagnolini, U., & Pickholtz, R. (2008). Spectrum leasing to cooperating secondary ad hoc networks. IEEE Journal on Selected Areas in Communications, 26(1), 203–213.CrossRefGoogle Scholar
  2. 2.
    Yi, Y., Zhang, J., Zhang, Q., & Jiang, T. (2011). Spectrum leasing to multiple cooperating secondary cellular networks. In Proceedings of the IEEE ICC11 (p. 15).Google Scholar
  3. 3.
    Jayaweera, S., & Li, T. (2009). Dynamic spectrum leasing in cognitive radio networks via primary-secondary user power control games. IEEE Transactions on Wireless Communications, 8(6), 3300–3310.CrossRefGoogle Scholar
  4. 4.
    Alptekin, G. I., & Bener, A. B. (2011). Spectrum trading in cognitive radio networks with strict transmission power control. European Transactions on Telecommunications, 22(6), 282–295.CrossRefGoogle Scholar
  5. 5.
    Jayaweera, S., Vazquez-Vilar, G., & Mosquera, C. (2010). Dynamic spectrum leasing: A new paradigm for spectrum sharing in cognitive radio networks. IEEE Transactions on Vehicular Technology, 59(5), 2328–2339.CrossRefGoogle Scholar
  6. 6.
    Hakim, K., Jayaweera, S., El-howayek, G., & Mosquera, C. (2010). Efficient dynamic spectrum sharing in cognitive radio networks: Centralized dynamic spectrum leasing (C-DSL). IEEE Transactions on Wireless Communications, 9(9), 2956–2967.CrossRefGoogle Scholar
  7. 7.
    El-howayek, G., & Jayaweera, S. (2011). Distributed dynamic spectrum leasing (D-DSL) for spectrum sharing over multiple primary channels. IEEE Transactions on Wireless Communications, 10(1), 55–60.CrossRefGoogle Scholar
  8. 8.
    Yang, C., Li, J., & Tian, Z. (2010). Optimal power control for cognitive radio networks under coupled interference constraints: A cooperative game-theoretic perspective. IEEE Transactions on Vehicular Technology, 59(4), 1696–1706.CrossRefGoogle Scholar
  9. 9.
    Bayat, S., Louie, R. H. Y., Vucetic, B., & Li, Y. (2013). Dynamic decentralised algorithms for cognitive radio relay networks with multiple primary and secondary users utilising matching theory. Transactions on Emerging Telecommunications Technologies, 24(5), 486–502.CrossRefGoogle Scholar
  10. 10.
    Murawski, R., & Ekici, E. (2011). Utilizing dynamic spectrum leasing for cognitive radios in 802.11-based wireless networks. Computer Networks, 55(5), 2646–2657.CrossRefGoogle Scholar
  11. 11.
    Bourdena, A., Pallis, E., Kormentzas, G., & Mastorakis, G. (2013). Efficient radio resource management algorithms in opportunistic cognitive radio networks. Transactions on Emerging Telecommunications Technologies. doi: 10.1002/ett.2687.
  12. 12.
    Huang, J., Berry, R., & Honig, M. (2006). Auction-based spectrum sharing. Mobile Networks and Applications, 11, 405–418.CrossRefGoogle Scholar
  13. 13.
    Chen, L., Iellamo, S., Coupechoux, M., & Godlewski, F. (2010). An auction framework for spectrum allocation with interference constraint in cognitive radio networks. In Proceedings of the IEEE INFOCOM (p. 19).Google Scholar
  14. 14.
    Wu, Y., Wang, B., Liu, K., & Clancy, T. (2009). A scalable collusion-resistant multi-winner cognitive spectrum auction game. IEEE Transactions on Communications, 57(12), 3805–3816.CrossRefGoogle Scholar
  15. 15.
    Adian, G. M., & Aghaeinia, H. (2013). An auction-based approach for spectrum leasing in cooperative cognitive radio networks: When to lease and how much to be leased. Wireless Networks, 19(7), 3805–3816.MathSciNetGoogle Scholar
  16. 16.
    Osborne, M., & Rubinstein, A. (1990). Bargaining and markets. New York: Academic Press Inc.MATHGoogle Scholar
  17. 17.
    Attar, A., Nakhai, M., & Aghvami, A. (2009). Cognitive radio game for secondary spectrum access problem. IEEE Transactions on Wireless Communications, 8(4), 2121–2131.CrossRefGoogle Scholar
  18. 18.
    Suris, J., DaSilva, L., Han, Z., MacKenzie, A., & Komali, R. (2009). Asymptotic optimality for distributed spectrum sharing using bargaining solutions. IEEE Transactions on Communications, 8(10), 5225–5237.Google Scholar
  19. 19.
    Ni, Q., & Zarakovitis, C. C. (2012). Nash bargaining game theoretic scheduling for joint channel and power allocation in cognitive radio systems. IEEE Journal on Selected Areas in Communications, 30(1), 70–81.CrossRefGoogle Scholar
  20. 20.
    Guan, X., Wang, X., Ma, K., Liu, Z., & Han, Q. (2014). Spectrum leasing based on Nash Bargaining Solution in cognitive radio networks. Telecommunication Systems. doi: 10.1007/s11235-013-9860-5.
  21. 21.
    Toroujeni, S. M. M., Sadough, S. M., & Ghorashi, S. A. (2012). On time-frequency resource leasing in cognitive radio networks. Wireless Personal Communication. doi: 10.1007/s11277-011-0274.
  22. 22.
    Saraydar, C., Mandayam, N., & Goodman, D. (2002). Efficient power control via pricing in wireless data networks. IEEE Transactions on Communications, 50(2), 291–303.CrossRefGoogle Scholar
  23. 23.
    Azimi, S. M. (2014). Pareto optimal primarysecondary user dynamic spectrum leasing game. Electronics Letters, 50(12), 874–876.CrossRefGoogle Scholar
  24. 24.
    Zhao, Y., Mao, S., Neel, J., & Reed, J. (2009). Performance evaluation of cognitive radios: Metrics, utility functions, and methodology. Proceeding of IEEE, 97(4), 642–659.CrossRefGoogle Scholar
  25. 25.
    Cao, X., Shen, H., Milito, R., & Wirth, P. (2002). Internet pricing with a game theoretical approach: Concepts and examples. IEEE/ACM Transactions on Networking, 10(2), 208–216.CrossRefGoogle Scholar
  26. 26.
    Boyd, S., & Vandenberghe, L. (2004). Convex optimization. Cambridge: Cambridge University Press.CrossRefMATHGoogle Scholar
  27. 27.
    Bertsekas, D. (1999). Nonlinear programming. Nashua, NH: Athena Scientific.MATHGoogle Scholar
  28. 28.
    Saad, W., Han, Z., Debbah, M., Hjrungnes, A., & Basar, T. (2009). Coalitional game theory for communication networks. IEEE Signal Processing Magazine, 26(5), 77–97.CrossRefGoogle Scholar
  29. 29.
    Myerson, R. B. (1991). Game theory, analysis of conflict. Cambridge, MA: Harvard University Press.MATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Seyyed Mohammadreza Azimi
    • 1
  • Mohammad Hossein Manshaei
    • 1
  • Faramarz Hendessi
    • 1
  1. 1.Electrical and Computer Engineering DepartmentIsfahan University of TechnologyIsfahanIran

Personalised recommendations