Skip to main content

Forced Spectrum Access Termination Probability Analysis under Restricted Channel Handoff

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7405))

Abstract

Most existing works on cognitive radio networks assume that cognitive (or secondary) users are capable of switching/jumping to any available channel, regardless of the frequency gap between the target and the current channels. Due to hardware limitations, cognitive users can actually jump only so far from where the operating frequency of their current channel is, given an acceptable switching delay that users are typically constrained by. This paper studies the performance of cognitive radio networks with dynamic multichannel access capability, but while considering realistic channel handoff assumptions, where cognitive users can only move/jump to their immediate neighboring channels.

Specifically, we consider a cognitive access network with m channels in which a cognitive user, currently using a particular channel, can only switch to one of its k immediate neighboring channels. This set of 2k channels is referred to as the target handoff channel set. We first model this cognitive access network with restricted channel handoff as a continuous-time Markov process, and then analytically derive the forced termination probability of cognitive users. Finally, we validate and analyze our derived results via simulations. Our obtained results show that the forced access termination probability of cognitive users decreases significantly as the number k increases.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ahmad, S.H.A., Liu, M., Javidi, T., Zhao, Q., Krishnamachari, B.: Optimality of myopic sensing in multi-channel opportunistic access. IEEE Transactions on Information Theory (2009)

    Google Scholar 

  2. Chen, L., Iellamo, S., Coupechoux, M., Godlewski, P.: An auction framework for spectrum allocation with interference constraint in cognitive radio networks. In: Proceedings of IEEE INFOCOM (2010)

    Google Scholar 

  3. Feng, Z., Yang, Y.: Throughput analysis of secondary networks in dynamic spectrum access networks. In: Proceedings of IEEE INFOCOM (2010)

    Google Scholar 

  4. Gur, G., Bayhan, S., Alagoz, F.: Cognitive femtocell networks: an overlay architecture for localized dynamic spectrum access. IEEE Wireless Communications 17(4) (2010)

    Google Scholar 

  5. Hamdaoui, B.: Adaptive spectrum assessment for opportunistic access in cognitive radio networks. IEEE Transactions on Wireless Communications 8(2), 922–930 (2009)

    Article  Google Scholar 

  6. Hamdaoui, B., Shin, K.G.: OS-MAC: An efficient MAC protocol for spectrum-agile wireless networks. IEEE Transactions on Mobile Computing (August 2008)

    Google Scholar 

  7. Harada, H.: A software defined cognitive radio prototype. In: Proc. of IEEE PIMRC (2007)

    Google Scholar 

  8. Harada, H.: A feasibility study on software defined cognitive radio equipment. In: Proc. of IEEE DySPAN (2008)

    Google Scholar 

  9. Mitola III, J.: Cognitive radio: an integrated agent architecture for software-defined radio. Dissertation, Computer Comm. System Lab, Dept. of Teleinformatics, Royal Inst. Tech., Sotckholm, Sweden (2000)

    Google Scholar 

  10. Kim, H., Shin, K.G.: Efficient discovery of spectrum oppotunities with MAC-layer sensing in cognitive radio networks. IEEE Transactions on Mobile Computing (May 2008)

    Google Scholar 

  11. Li, X., Zhao, Q.C., Guan, X., Tong, L.: Optimal cognitive access of markovian channels under tight collision constraints. IEEE Journal on Selected Areas in Communications, Special Issue on Advances in Cognitive Radio Networks and Communications (to appear, 2011)

    Google Scholar 

  12. Liu, K., Zhao, Q.: Distributed learning in cognitive radio networks: multi-armed brandit with distributed multiple players. Submitted to IEEE Int. Conf. on Acousitcs, Speech, and Signal Processing (2010)

    Google Scholar 

  13. Ma, M., Tsang, D.H.K.: Joint design of spectrum sharing and routing with channel heterogeneity in cognitive radio networks. Physical Communication 2(1-2) (2009)

    Google Scholar 

  14. Ma, Y., Kim, D.I., Wu, Z.: Optimization of OFDMA-based cellular cognitive radio networks. IEEE Transactions on Communications 58(8) (2010)

    Google Scholar 

  15. Marshall, P.F.: Dynamic spectrum access as a mechanism for transition to interference tolerant systems. In: Proceedings of IEEE DySPAN (2010)

    Google Scholar 

  16. NoroozOliaee, M., Hamdaoui, B., Tumer, K.: Efficient objective functions for coordinated learning in large-scale distributed osa systems. IEEE Transactions on Mobile Computing (to appear)

    Google Scholar 

  17. Sahin, M.E., Arslan, H.: System design for cognitive radio communications. In: Proceedings of Int’l Conference on Cognitive Radio Oriented Wireless Networks and Communications (June 2006)

    Google Scholar 

  18. Sutton, P., et al: Iris: an architecture for cognitive radio networking testbeds. IEEE Communications Magazine 48(9) (2010)

    Google Scholar 

  19. Teleghan, M.A., Hamdaoui, B.: Efficiency-revenue optimality tradeoffs in dynamic spectrum allocation. In: Proc. of IEEE GLOBECOM (2010)

    Google Scholar 

  20. Timmers, M., Pollin, S., Dejonghe, A., der Perre, L.V., Catthoor, F.: A distributed multichannel MAC protocol for multihop cognitive radio networks. IEEE Transactions on Vehicular Technology 59(1) (2010)

    Google Scholar 

  21. Unnikrishnan, J., Veeravalli, V.V.: Algorithms for dynamic spectrum access with learning for cognitive radio. IEEE Transactions on Signal Processing 58(2) (August 2010)

    Google Scholar 

  22. Xiaorong Zhu, L.S., Yum, T.S.P.: Analysis of cognitive radio spectrum access with optimal channel reservation. IEEE Communications Letters 11(4), 304–306 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

NoroozOliaee, M., Hamdaoui, B., Znati, T., Guizani, M. (2012). Forced Spectrum Access Termination Probability Analysis under Restricted Channel Handoff. In: Wang, X., Zheng, R., Jing, T., Xing, K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2012. Lecture Notes in Computer Science, vol 7405. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31869-6_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31869-6_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31868-9

  • Online ISBN: 978-3-642-31869-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics