Forced Spectrum Access Termination Probability Analysis under Restricted Channel Handoff

  • MohammadJavad NoroozOliaee
  • Bechir Hamdaoui
  • Taieb Znati
  • Mohsen Guizani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7405)


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.


Cognitive Radio Primary User Termination Probability Cognitive Radio Network Dynamic Spectrum Access 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 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. 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. 3.
    Feng, Z., Yang, Y.: Throughput analysis of secondary networks in dynamic spectrum access networks. In: Proceedings of IEEE INFOCOM (2010)Google Scholar
  4. 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. 5.
    Hamdaoui, B.: Adaptive spectrum assessment for opportunistic access in cognitive radio networks. IEEE Transactions on Wireless Communications 8(2), 922–930 (2009)CrossRefGoogle Scholar
  6. 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. 7.
    Harada, H.: A software defined cognitive radio prototype. In: Proc. of IEEE PIMRC (2007)Google Scholar
  8. 8.
    Harada, H.: A feasibility study on software defined cognitive radio equipment. In: Proc. of IEEE DySPAN (2008)Google Scholar
  9. 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. 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. 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. 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. 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. 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. 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. 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. 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. 18.
    Sutton, P., et al: Iris: an architecture for cognitive radio networking testbeds. IEEE Communications Magazine 48(9) (2010)Google Scholar
  19. 19.
    Teleghan, M.A., Hamdaoui, B.: Efficiency-revenue optimality tradeoffs in dynamic spectrum allocation. In: Proc. of IEEE GLOBECOM (2010)Google Scholar
  20. 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. 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. 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)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • MohammadJavad NoroozOliaee
    • 1
  • Bechir Hamdaoui
    • 1
  • Taieb Znati
    • 2
  • Mohsen Guizani
    • 3
  1. 1.Oregon State UniversityUSA
  2. 2.University of PittsburghUSA
  3. 3.Qatar UniversityQatar

Personalised recommendations