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Optimizing radio resource management in energy-efficient cognitive radio networks

Published:03 November 2013Publication History

ABSTRACT

This paper elaborates on two radio resource management (RRM) algorithms exploited to optimally allocate radio spectrum and maintain maximum energy in cognitive radio (CR) network nodes of a centralized system architecture. Both RRM algorithms allow for effective TV White Spaces (TVWS) exploitation, using a radio spectrum broker. This broker orchestrates TVWS trading, between several secondary systems, based on an energy-efficient process, as well as the real time secondary spectrum market policy. The proposed TVWS allocation process follows, either a fixed-price or an auction-based trading approach. The efficiency of both algorithms is validated through a number of experimental tests, conducted under controlled simulation conditions. More specifically, their performance was evaluated, in terms of spectrum broker benefit, energy consumption level and throughput response, during TVWS allocation process.

References

  1. First Report and Order, "Federal Communication Commission Std., 2010. Available: http://fjallfoss.fcc.gov/edocs_public/attachmatch/FCC-10-196A1_Rcd.pdf.Google ScholarGoogle Scholar
  2. The Economics of Spectrum management: A Review, Australian Communication and Media Authority (ACMA), 2007.Google ScholarGoogle Scholar
  3. OFCOM, "Digital Dividend Review: geographic interleaved awards 470 - 550 MHz and 630 - 790 MHz - Consultation on detailed award design", June 2008.Google ScholarGoogle Scholar
  4. 3GGPP LTE: http://www.3gpp.org/LTEGoogle ScholarGoogle Scholar
  5. Unlicensed Operation in the TV Broadcast Bands, Final Rules, Available: http://edocket.access.gpo.gov/2009/pdf/E9-3279.pdf.Google ScholarGoogle Scholar
  6. A. Bourdena, E. Pallis, G. Kormentzas, C. Skianis, G. Mastorakis, "Real-Time TVWS Trading Based on a Centralised CR Network Architecture", in proc. IEEE Globecom2011, Texas, Houston, USA, 2011, pp. 964--969.Google ScholarGoogle Scholar
  7. I. F. Akyildiz, W. Y. Lee, M. C. Vuran, S. Mohanty, "A Survey on Spectrum Management in Cognitive Radio Networks", IEEE Coms. Mag. 46, 40--48, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. F. Cavalcanti, S. Andersson, "Optimizing Wireless Communications Systems", Springer, 2009.Google ScholarGoogle Scholar
  9. A. Bourdena, E. Pallis, G. Kormentzas, G. Mastorakis, "A prototype cognitive radio architecture for TVWS exploitation under the real time secondary spectrum market policy", Physical Communications Journal, Elsevier, (to appear).Google ScholarGoogle Scholar
  10. A. Bourdena, E. Pallis, G. Kormentzas, G. Mastorakis, "A centralised broker-based CR network architecture for TVWS exploitation under the RTSSM policy", in proc. IEEE ICC2012, Ottawa, Canada, 10-15 June, 2012, pp. 7243--7247.Google ScholarGoogle Scholar
  11. A. Bourdena, E. Pallis, G. Kormentzas, H. Skianis, G. Mastorakis, "QoS provisioning and policy management in a broker-based CR network architecture", in Proc. IEEE Globecom 2012, Anaheim, California, USA, 03-07 December, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  12. A. Bourdena, E. Pallis, G. Kormentzas, G. Mastorakis, "Radio Resource Management Algorithms for Efficient QoS Provisioning over Cognitive Radio Networks", in proc IEEE ICC2013, Budapest, Hungary, 09-13 June, 2013 (accepted).Google ScholarGoogle Scholar
  13. A. Wyglynski, M. Nekovee, and T. Hou, Cognitive Radio Communications and Networks: Principles and Practice, Academic Press, 2009.Google ScholarGoogle Scholar
  14. I. F. Akyildiz, W. Y. Lee, M. C. Vuran, S. Mohanty, "A Survey on Spectrum Management in Cognitive Radio Networks", IEEE Communications Magazine, April 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. E. Hossain, D. Niyato and Z. Han, "Dynamic spectrum access and management in cognitive radio networks", first ed. Cambridge University Press, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. C. X. Mavromoustakis, C. D. Dimitriou, G. Mastorakis, "Using Real-Time Backward Traffic Difference Estimation for Energy Conservation in Wireless Devices", in proc. of 4th International Conference on Advances in P2P Systems (AP2PS 2012), September 23-28, 2012 - Barcelona, Spain, pp. 18--23.Google ScholarGoogle Scholar
  17. C. X. Mavromoustakis, K. G. Zerfiridis, "On the diversity properties of wireless mobility with the user-centered temporal capacity awareness for EC in wireless devices", in proc. of 6th IEEE International Conference on Wireless and Mobile Communications, ICWMC 2010, September 20-25, 2010-Valencia, Spain, pp. 367--372. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Y. Choi, H. Kim, S. Han, and Y. Han, "Joint resource allocation for parallel multi-radio access in heterogeneous wireless networks," IEEE Trans. Wireless Commun. vol. 9, no. 11, pp. 3324--3329, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. A. Bourdena, G. Mastorakis, E. Pallis, C. Mavromoustakis, G. Kormentzas and E. Karditsis "A Radio Resource Management Framework for Opportunistic TVWS Access", in proc. of 15th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM' 12), October 21-25 2012, Paphos, Cyprus, pp. 33--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. C. Dimitriou, C. X. Mavromoustakis, G. Mastorakis, E. Pallis, "On the performance response of delay-bounded energy-aware bandwidth allocation scheme in wireless networks", IEEE ICC2013, 9-13 June 2013, Budapest, Hungary.Google ScholarGoogle ScholarCross RefCross Ref
  21. S. S. Skiena: The Algorithm Design Manual, Springer.Google ScholarGoogle Scholar
  22. C. X. Mavromoustakis, "On the impact of caching and a model for storage-capacity measurements for energy conservation in asymmetrical wireless devices", IEEE Communication Society (COMSOC), 16th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2008), September 2008, pp. 243--247.Google ScholarGoogle Scholar
  23. C. X. Mavromoustakis, "Mitigating file-sharing misbehavior with movement synchronization to increase end-to-end availability for delay sensitive streams in vehicular P2P devices", International Journal of Communication Systems, Wiley, to appear.Google ScholarGoogle Scholar
  24. COGEU-ICT-FP7-248560, COGnitive radio systems for efficient sharing of TV white spaces in EU context, http://www.ict-cogeu.eu.Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Conferences
      HP-MOSys '13: Proceedings of the 2nd ACM workshop on High performance mobile opportunistic systems
      November 2013
      98 pages
      ISBN:9781450323727
      DOI:10.1145/2507908

      Copyright © 2013 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 3 November 2013

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      HP-MOSys '13 Paper Acceptance Rate13of35submissions,37%Overall Acceptance Rate13of35submissions,37%

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