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Realizing the Broker Based Dynamic Spectrum Allocation through LTE Virtualization and Uniform Auctioning

  • Yasir Zaki
  • Manzoor Ahmed Khan
  • Liang Zhao
  • Carmelita Görg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6827)

Abstract

The next generation wireless networks are envisioned to follow the philosophy of buy when required, when it comes to the CApital EXpenditure (CAPEX) of operators over the infrastructure installation or extending new and dynamic resources. The dream of open market for new entrants and their coexistence with giant operators can be realized by the fancy concept of virtualization, which will be one of the key technologies in the future networks specially in the wireless part. Future virtualized mobile networks will comprise of a large number of (small) operators all competing for the spectrum resources. Such a scenario motivates and provisions the dynamic resource trading framework. This paper aims at presenting the realization concept of a dynamic spectrum trade market of future. We use the virtualized Long Term Evolution (LTE) as a realization framework for the proposed auctioned based dynamic spectrum sharing. We also investigate the profit function of spectrum broker and operators. We also study the realization of dynamic spectrum allocation on very small time instances (seconds) and investigate how the reservation price tunes the stake-holders’ profit and resource allocation efficiency. The spectrum trade is based on the single auction multi-bid format and the paper further studies the impact of false bidding on the profit of spectrum broker (or network infrastructure provider).

Keywords

LTE Wireless virtualization Spectrum sharing Uniform auctioning format 

References

  1. 1.
    Bavier, A., Bowman, M., Culler, D., Chun, B., Karlin, S., Muir, S., Peterson, L., Roscoe, T., Spalink, T., Wawrzoniak, M.: Operating system support for planetary-scale network services (March 2004)Google Scholar
  2. 2.
    Paul, S., Seshan, S.: Geni technical document on wireless virtualization (September 2006)Google Scholar
  3. 3.
    AKARI architecture conceptual design for new generation networkGoogle Scholar
  4. 4.
    Bauck, S., Görg, C.: Virtualisation as a co-existence tool in a future internet. In: ICT Mobile Summit - 4WARD Workshop, Stockholm, Sweden (June 2008)Google Scholar
  5. 5.
    Zaki, Y., Zhao, L., Timm-Giel, A., Görg, C.: A Novel LTE Wireless Virtualization Framework. In: Second International ICST Conference on Mobile Networks And Management (Monami), Santander, Spain, pp. 1–13 CD publication (September 2010)Google Scholar
  6. 6.
    Zaki, Y., Zhao, L., Timm-Giel, A., Görg, C.: LTE Wireless Virtualization and Spectrum Management. In: Third Joint IFIP Wireless and Mobile Networking Conference (WMNC), Budapest, Hungary (October 2010)Google Scholar
  7. 7.
  8. 8.
    Buddhikot, M.M., Kolodzy, P., Miller, S., Ryan, K., Evans, J.: Dimsumnet: New directions in wireless networking using coordinated dynamic spectrum access. In: IEEE WoWMoM 2005, pp. 78–85 (2005)Google Scholar
  9. 9.
    Rodriguez, V., Moessner, K., Tafazolli, R.: Market-driven dynamic spectrum allocation: Optimal end-user pricing and admission control for cdma. In: The Proceedings of IST Mobile and Wireless Communication Summit (2005)Google Scholar
  10. 10.
    Rodriguez, V., Moessner, K., Tafazolli, R.: Auction driven dynamic spectrum allocation: optimal bidding, pricing and service priorities for multi-rate, multi-class cdma. In: The Proceedings of 16th Internationalymposium on Personal, Indoor and Mobile Radio Communications (PIMRC), pp. 1850–1854 (2005)Google Scholar
  11. 11.
    Subramanian, A.P., Al-Ayyoub, M., Gupta, H., Das, S.R., Buddhikot, M.M.: Near-optimal dynamic spectrum allocation in cellular networks. In: 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN, pp. 1–11 (2008)Google Scholar
  12. 12.
    Yang, L., Cao, L., Zheng, H.: Physical interference driven dynamic spectrum management. In: Proc. of IEEE DySPAN (2008)Google Scholar
  13. 13.
    Zhou, X., Gandhi, S., Suri, S., Zheng, H.: ebay in the sky: strategy-proof wireless spectrum auctions. In: Proceedings of the 14th ACM International Conference on Mobile Computing and Networking, MobiCom 2008, pp. 2–13. ACM, New York (2008)CrossRefGoogle Scholar
  14. 14.
    Sorabh, G., Buragohain, C., Cao, L., Zheng, H., Suri, S.: A general framework for wireless spectrum.Google Scholar
  15. 15.
    Sengupta, S., Chatterjee, M., Ganguly, S.: An economic framework for spectrum allocation and service pricing with competitive wireless service providers. In: 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN, pp. 89–98 (2007)Google Scholar
  16. 16.
    Cramton, P.: The efficiency of the fcc spectrum auctions. Journal of Law and Economics 41 (October 1998)Google Scholar
  17. 17.
    Spectrum auctions. Auction design issues for spectrum awards market analysis Ltd.Google Scholar
  18. 18.
    French, R.: Spectrum auctions 101. The Journal of Public Sector Management (2008)Google Scholar
  19. 19.
    Sandholm, T., Suri, S.: Market clearability. In: Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pp. 1145–1151 (2001)Google Scholar
  20. 20.
    Williams, D.E., Garcia, J.: Virtualization with XenTM: Including XenEnterpriseTM, XenServerTM, and XenExpressTM. In: SYNGRESS 2007 (2007)Google Scholar
  21. 21.

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Yasir Zaki
    • 1
  • Manzoor Ahmed Khan
    • 2
  • Liang Zhao
    • 1
  • Carmelita Görg
    • 1
  1. 1.ComNetsUniversity of BremenGermany
  2. 2.DAI-Labor/Technical UniversityBerlinGermany

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