access icon free Spectrum trading in cognitive radio networks with uncertainty in primary service requirements

© The Institution of Engineering and Technology
Received 18/01/2013, Accepted 19/10/2013, Revised 18/10/2013, Published 28/11/2013

This study addresses the problem of spectrum trading in a cognitive radio network with multiple primary users (PUs) competing to sell spectrum to a secondary user (SU). The spectrum trading process is modelled using a ‘Cournot game model’ of competition by which the PUs set the size of spectrum to sell. In this study, the spectrum requirements for the PUs’ services are not fixed but time varying, and the spectrum trading process is carried out before the realisation of these values. If the spectrum retained for a PU after selling is less than the spectrum requirement for the PU's service, a cost must be charged to the PU. The Nash equilibrium (NE) for a static game when the PUs have complete knowledge on the utility functions of other PUs is studied first. A dynamic game, in which the players adaptively change their strategies to reach the NE, is discussed subsequently. Finally, the trading problem is extended to a scenario which involves multiple SUs.

Inspec keywords: game theory; cognitive radio; radio spectrum management

Other keywords: cognitive radio networks; Nash equilibrium; spectrum trading; SU; multiple primary users; primary service requirements; PU; Cournot game model; secondary user

Subjects: Game theory; Radio links and equipment

References

    1. 1)
    2. 2)
      • 21. Slotine, J., Li, W.: ‘Applied nonlinear control’ (Prentice-Hall Englewood Cliffs, NJ, 1991), vol. 199.
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
      • 16. Jia, J., Zhang, Q., Zhang, Q., Liu, M.: ‘Revenue generation for truthful spectrum auction in dynamic spectrum access’. Proc. ACM Mobile Ad Hoc Networking and Computing, 2009, pp. 3–12.
    12. 12)
      • 15. Groves, T.: ‘Incentives in teams’, Econ., J. Econ. Soc., 1973, 41, pp. 617–631.
    13. 13)
      • 13. Zhou, X., Gandhi, S., Suri, S., Zheng, H.: ‘eBay in the sky: strategy-proof wireless spectrum auctions’. Proc. ACM Mobile Computing and Networking, 2008, pp. 2–13.
    14. 14)
      • 6. Scutari, G., Barbarossa, S., Palomar, D.: ‘Potential games: a framework for vector power control problems with coupled constraints’, Proc. IEEE ICASSP, 2006, 4, p. IV.
    15. 15)
      • 2. Duong, N., Madhukumar, A.: ‘Non-cooperative power control and spectrum allocation in cognitive radio networks: a game theoretic perspective’. Wireless Communications and Mobile Computing, 2012.
    16. 16)
      • 12. Gandhi, S., Buragohain, C., Cao, L., Zheng, H., Suri, S.: ‘A general framework for wireless spectrum auctions’. Proc. IEEE DySPAN, April 2007, pp. 22–33.
    17. 17)
      • 11. Niyato, D., Hossain, E.: ‘Competitive pricing for spectrum sharing in cognitive radio networks: dynamic game, inefficiency of Nash equilibrium, and collusion’, IEEE J. Sel. Areas Commun., 2008, 26, pp. 192–202 (doi: 10.1109/JSAC.2008.080117).
    18. 18)
      • 4. Neel, J., Reed, J., Gilles, R.: ‘Convergence of cognitive radio networks’. Proc. IEEE WCNC, 2004, 4, pp. 2250–2255.
    19. 19)
      • 8. Scutari, G., Palomar, D., Barbarossa, S.: ‘Asynchronous iterative water-filling for Gaussian frequency-selective interference channels’, IEEE Trans. Inf. Theory, 2008, 54, pp. 2868–2878 (doi: 10.1109/TIT.2008.924723).
    20. 20)
      • 5. Del Re, E., Gorni, G., Ronga, L., Suffritti, R.: ‘A power allocation strategy using game theory in cognitive radio networks’. Proc. IEEE Game Theory for Networks (GameNets), May 2009, pp. 117–123.
    21. 21)
      • 17. Niyato, D., Hossain, E., Han, Z.: ‘Dynamics of multiple-seller and multiple-buyer spectrum trading in cognitive radio networks: a game-theoretic modeling approach’, IEEE Trans. Mob. Comput., 2009, 8, pp. 1009–1022 (doi: 10.1109/TMC.2008.157).
    22. 22)
      • 22. Boyd, S., Vandenberghe, L.: ‘Convex optimization’ (Cambridge Univ Pr, 2004).
    23. 23)
      • 7. Yu, W., Ginis, G., Cioffi, J.: ‘Distributed multiuser power control for digital subscriber lines’, IEEE J. Sel. Areas Commun., 2002, 20, pp. 1105–1115 (doi: 10.1109/JSAC.2002.1007390).
    24. 24)
      • 21. Slotine, J., Li, W.: ‘Applied nonlinear control’ (Prentice-Hall Englewood Cliffs, NJ, 1991), vol. 199.
    25. 25)
      • 10. Niyato, D., Hossain, E.: ‘Competitive spectrum sharing in cognitive radio networks: a dynamic game approach’, IEEE Trans. Wirel. Commun., 2008, 7, pp. 2651–2660 (doi: 10.1109/TWC.2008.070073).
    26. 26)
      • 3. Nie, N., Comaniciu, C.: ‘Adaptive channel allocation spectrum etiquette for cognitive radio networks’. Proc. IEEE DySPAN, November 2005, pp. 269–278.
    27. 27)
      • 18. Lin, P., Jia, J., Zhang, Q., Hamdi, M.: ‘Dynamic spectrum sharing with multiple primary and secondary users’, IEEE Trans. Veh. Technol., 2011, 60, pp. 1756–1765 (doi: 10.1109/TVT.2011.2132156).
    28. 28)
      • 20. Rosen, J.B.: ‘Existence and uniqueness of equilibrium points for concave n-person games’, Econ., J. Econ. Soc., 1965, 33, pp. 520–534.
    29. 29)
      • 1. Osborne, M.: ‘An introduction to game theory’ (Oxford University Press, New York, NY, 2004) vol. 3.
    30. 30)
      • 14. Clarke, E.: ‘Multipart pricing of public goods’, Public Choice, 1971, 11, (1), pp. 17–33 (doi: 10.1007/BF01726210).
    31. 31)
      • 19. Niyato, D., Hossain, E.: ‘Market-equilibrium, competitive, and cooperative pricing for spectrum sharing in cognitive radio networks: analysis and comparison’, IEEE Trans. Wirel. Commun., 2008, 7, pp. 4273–4283 (doi: 10.1109/T-WC.2008.070546).
    32. 32)
      • 9. Singh, N., Vives, X.: ‘Price and quantity competition in a differentiated duopoly’, RAND J. Econ., 1984, 15, pp. 546–554 (doi: 10.2307/2555525).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-spr.2012.0396
Loading

Related content

content/journals/10.1049/iet-spr.2012.0396
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading