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Economic Approaches in Cognitive Radio Networks

  • Sabita MaharjanEmail author
  • Yan Zhang
  • Stein Gjessing
Chapter

Abstract

Efficient resource allocation is one of the key concerns of implementing cognitive radio networks. Game theory has been extensively used to study the strategic interactions between primary and secondary users for effective resource llocation. The concept of spectrum trading has introduced a new direction for the coexistence of primary and secondary users through economic benefits to primary users. The use of price theory and market theory from economics has played a vital role to facilitate economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks.

With this motivation, we present an extensive summary of the related work that uses economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks.

Keywords

Nash Equilibrium Cognitive Radio Primary User Secondary User Cognitive Radio Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Akyildiz IF, Lee WY, Vuran MC, Mohanty S (2006) NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey, computer networks, Vol. 50, no. 13, pp. 2127–2159zbMATHGoogle Scholar
  2. 2.
    Alpca T, Basar T, Dey S (2006) A power control game based on outage probabilities for multicell wireless data networks. IEEE Transactions on Wireless Communications, Vol. 5, no. 4, pp. 890–899CrossRefGoogle Scholar
  3. 3.
    Cao L, Zheng H (2005) Distributed spectrum allocation via local bargaining. Proceedings, IEEE Sensor and Ad Hoc Communications and Networks (SECON) 2005, Santa Clara, CA, pp. 475–486Google Scholar
  4. 4.
    Gandhi S, Buragohain C, Cao L, Zheng H, Suri S (2007) A general framework for wireless spectrum auctions. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Dublin, Ireland, 2007Google Scholar
  5. 5.
    Gibbons R (1992) A Primer in Game Theory. Harvester Wheatsheaf, Hemel Hempstead, UKzbMATHGoogle Scholar
  6. 6.
    Han Z, Liu KJR (2005) Non-cooperative power-control game and throughput game over wireless networks. IEEE Transactions on Communications, Vol. 53, no. 10, pp. 1625–1629CrossRefGoogle Scholar
  7. 7.
    Han Z, Ji Z, Liu KJR (2007) Non-cooperative resource competition game by virtual referee in multi-cell OFDMA networks. IEEE Journal on Selected Areas in Communications, Vol. 25, no. 6, pp. 1079–1090CrossRefGoogle Scholar
  8. 8.
    Han Z, Poor HV (2009) Coalition games with cooperative transmission: a cure for the curse of boundary nodes in selfish packet-forwarding wireless networks. IEEE Transactions on Communications, Vol. 57, no. 1, pp. 203–213CrossRefGoogle Scholar
  9. 9.
    Haykins S (2005) Cognitive radio: brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, Vol. 23, no. 2, pp. 201–220CrossRefGoogle Scholar
  10. 10.
    Hosseinabadi G, Manshaei H, Hubaux JP (2008) Spectrum sharing games of infrastructure-based cognitive radio networks, Technical Report LCA-REPORT-2008-027Google Scholar
  11. 11.
    Huang J, Berry RA, Honig ML (2006) Auction-based spectrum sharing. ACM Mobile Networks and Applications J., Vol. 11, no. 3, pp. 405–418CrossRefGoogle Scholar
  12. 12.
    Husheng L, Zhu H (2010) Catching attacker(s) for collaborative spectrum sensing in cognitive radio systems:an abnormality detection approach. IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Singapore, 2010Google Scholar
  13. 13.
    Jayaweera SK, Tianming L (2009) Dynamic spectrum leasing in cognitive radio networks via primary-secondary user power control games. IEEE Transactions on Wireless Communications, Vol. 8, no. 6, pp. 3300–3310CrossRefGoogle Scholar
  14. 14.
    Ji Z, Liu KJR (2008) Multi-stage pricing game for collusion-resistant dynamic spectrum allocation. IEEE Journal on Selected Areas in Communications, Vol. 26, no. 1, pp. 182–191CrossRefGoogle Scholar
  15. 15.
    Jia J, Zhang Q, Zhang Q, Liu M (2009) Revenue generation for truthful spectrum auction in dynamic spectrum access. Proceedings of the tenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, New Orleans, LA, pp. 3–12Google Scholar
  16. 16.
    Kosut O, Tong L (2006) Capacity of cooperative fusion in the presence of byzantine sensors. Proceedings of the 44th Annual Allerton Conference on Communication, Control and Computation, Ithaca, NYGoogle Scholar
  17. 17.
    Krishna V (2002) Auction Theory. Academic, LondonGoogle Scholar
  18. 18.
    Maille P, Tuffin B (2008) Analysis of price competition in a slotted resource allocation game. Proceedings, IEEE Infocom 2008, Phoenix, AZ, pp. 1561–1569Google Scholar
  19. 19.
    Marshalla RC, Marx LM (2006) Bidder Collusion. Journal of Economic Theory, Elsevier, Vol. 133 (available online: 3rd Feb. 2006, published: 2007) pp. 374–402Google Scholar
  20. 20.
    Maskery M, Krishnamurthy V, Zhao Q (2009) Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game. IEEE Transactions on Communications, Vol. 57, no. 2, pp. 459–469CrossRefGoogle Scholar
  21. 21.
    Mitola J (1999) Cognitive radio for flexible mobile multimedia communications. Proceedings, IEEE Workshop on Mobile Multimedia Communication, San Diego, CA, pp. 3–10Google Scholar
  22. 22.
    Monderer D, Shapley L (1996) Potential games. Games and economic behavior, Vol. 14, no. 1, pp. 124–143MathSciNetzbMATHCrossRefGoogle Scholar
  23. 23.
    Nie N, Comaniciu C (2005) Adaptive channel allocation spectrum etiquette for cognitive radio networks. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (Dyspan), Baltimore, MD, pp. 269–278Google Scholar
  24. 24.
    Niyato D, Hossain E (2007) A game-theoretic approach to competitive spectrum sharing in cognitive radio networks. Proceedings of IEEE WCNC, Hongkong, 2007Google Scholar
  25. 25.
    Niyato D, Hossain E (2007) Equilibrium and disequilibrium pricing for spectrum trading in cognitive radio: a control theoretic approach. Proceedings of IEEE GLOBECOM, Washington DC, 2007Google Scholar
  26. 26.
    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, Vol. 26, no. 1, pp. 192–202CrossRefGoogle Scholar
  27. 27.
    Niyato D, Hossain E (2008) Competitive spectrum sharing in cognitive radio networks: a dynamic game approach. IEEE Transactions on Wireless Communications, Vol. 7, no. 7, pp. 2651–2660CrossRefGoogle Scholar
  28. 28.
    Niyato D, Hossain E (2008) Market-equilibrium, competitive and cooperative pricing for spectrum sharing in cognitive radio networks: analysis and comparison. IEEE Transactions on Wireless Communications, Vol. 7, no. 11, pp. 4273–4283CrossRefGoogle Scholar
  29. 29.
    Niyato D, Hossain E (2008) Competitive pricing in heterogeneous wireless access networks: issues and approaches. IEEE Network, Vol. 22, no. 6, pp. 4–11CrossRefGoogle Scholar
  30. 30.
    Niyato D, Hossain E (2008) Spectrum trading in cognitive radio networks: a market-equilibrium based approach. IEEE Wireless Communications Magazine, Vol. 15, no. 6, pp. 71–80CrossRefGoogle Scholar
  31. 31.
    Niyato D, Hossain E, Han Z (2009) Dynamic spectrum access in IEEE 802.22-based cognitive wireless networks: a game theoretic model for competitive spectrum bidding and pricing. IEEE Wireless Communications, Vol. 16, no. 2, pp. 16–23CrossRefGoogle Scholar
  32. 32.
    Niyato D, Hossain E, Han Z (2009) Dynamics of multiple-seller and multiple-buyer spectrum trading in cognitive radio networks: a game theoretic modeling approach. IEEE Transactions on Mobile Computing, Vol. 8, no. 8, pp. 1009–1022CrossRefGoogle Scholar
  33. 33.
    Rodriguez V, Moessner K, Tafazolli R (2005) Auction driven dynamic spectrum allocation: optimal bidding, pricing and service priorities for multi-rate, multi-class CDMA. IEEE PIMRC 2005, Vol. 3, pp. 1850–1854Google Scholar
  34. 34.
    Saad W, Han Z, Debbah M, Hjrungnes A, Basar, T (2009) Coalitional game theory for communication networks: a tutorial. IEEE Signal Processing Magazine, Special Issue on Game Theory, Vol. 26, pp. 77–99Google Scholar
  35. 35.
    Saad W, Han Z, Debbah M, Hjrungnes A, Basar T (2009) Coalitional games for distributed collaborative spectrum sensing in cognitive radio networks. Proceedings, Annual IEEE Conference on Computer Communications, INFOCOM, Rio de Janeiro, Brazil, 2009Google Scholar
  36. 36.
    Sengupta S, Chandramouli R, Brahma S, Chatterjie M (2008) A game theoretic framework for distributed self-coexistence among IEEE 802.22 networks. IEEE Globecom, New Orleans, LA, 2008Google Scholar
  37. 37.
    Shapley L (1953) Stochastic games. Proceedings of the National Academy of Sciences of the United States of America, Vol. 39, no. 10, pp. 1095–1100MathSciNetCrossRefGoogle Scholar
  38. 38.
    Smith JM (1982) Evolution and the Theory of Games. Cambridge University Press, UKzbMATHCrossRefGoogle Scholar
  39. 39.
    Unnikrishnan J, Veeravalli VV (2007) Cooperative spectrum sensing and detection for cognitive radio. IEEE Globecom, Washington, DC, USA, 2007Google Scholar
  40. 40.
    Wang B, Liu KJR, Clancy TC (2010) Evolutionary cooperative spectrum sensing game: how to collaborate? IEEE Transactions on Communications Vol. 58, no. 3, pp. 890–900CrossRefGoogle Scholar
  41. 41.
    Wang B, Wu Y, Liu KJR (2010) An anti-jamming stochastic game for cognitive radio networks. http://www.rsc.org/dose/http://www.ece.umd.edu/ bebewang/jsac09_bw.pdf
  42. 42.
    Wang F, Krunz M, Cui S (2008) Price based spectrum management in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing, Vol. 2, no. 1, pp. 74–87CrossRefGoogle Scholar
  43. 43.
    Weibull, JW (1995) Evolutionary Game Theory. MIT Press, CambridgezbMATHGoogle Scholar
  44. 44.
    Xing Y, Chandramouli R, Cordeiro, CM (2007) Price dynamics in competitive agile spectrum access markets. IEEE Journal on Selected Areas in Communication, Vol. 25, no. 3, pp. 613–621CrossRefGoogle Scholar
  45. 45.
    Zhang J, Zhang Q (2009) Stackelberg game for utility-based cooperative cognitive radio networks, Proceedings of the tenth ACM International Symposium on Mobile Ad hoc Networking and computing (MobiHoc) 2009, New Orleans, LA, pp. 23–32Google Scholar
  46. 46.
    Zhou X, Gandhi S, Suri S, Zheng H (2008) eBay in the sky: Strategy-proof wireless spectrum auctions. Proceedings of the 14th ACM International Conference on Mobile Computing and Networking, San Francisco, CA, pp. 2–13Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Simula Research LaboratoryLysakerNorway
  2. 2.Simula Research LaboratoryLysakerNorway
  3. 3.University of OsloOsloNorway

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