Skip to main content
SpringerLink
Log in

Queue Model Analysis for Spectrum-Sharing Cognitive Systems Under Outage Probability Constraint

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

This article investigates the behavior of the cognitive queueing system in a spectrum-sharing environment under the primary outage probability constraint. The queueing model is investigated under two cognitive transmit modes. A variable transmit rate that is equal to the cognitive channel’s capacity is first revisited, then the case of constant transmit rate is considered. Both transmit modes are found to lead to an \(M/G/1\) queueing model. The performance measures of the cognitive queue under these two modes are investigated and numerically compared. The performance measures include the mean transmit rate, mean service time, server utilization, mean waiting and transit times of the packets in the queue, mean number of waiting and transit packets in the queue, mean duration of the server’s busy period, and mean number of packets served during the server’s busy period. The effects of changing the primary outage probability constraint and the primary transmit rate on the performance measures are investigated as well.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. Part of Sect. 3.1 appeared in [18], and it is provided here for completeness.

References

  1. Federal Commununications Commission. (2002, November). Spectrum policy task force report. ET Docket No. 02-135.

  2. Mitola, J. (2000, December). Cognitive radio: An integrated agent architecture for software defined radio. Ph.D. thesis, Royal Institute of Technology (KTH), Stockholm, Sweden.

  3. Haykin, S. (2005). Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 23, 201–220.

    Article  Google Scholar 

  4. Farraj, A. K., & Hammad, E. M. (2013). Performance of primary users in spectrum sharing cognitive radio environment. Wireless Personal Communications, 68, 575–585.

    Article  Google Scholar 

  5. Kim, S. (2013). Cognitive radio bandwidth sharing scheme based on the two-way matching game. Wireless Personal Communications, 68, 893–905.

    Article  Google Scholar 

  6. da Costa, D., Aïssa, S., & Cavalcante, C. (2012). Performance analysis of partial relay selection in cooperative spectrum sharing systems. Wireless Personal Communications, 64, 79–92.

    Article  Google Scholar 

  7. Ciftci, S., & Torlak, M. (2013). A comparison of energy detectability models for cognitive radios in fading environments. Wireless Personal Communications, 68, 553–574.

    Article  Google Scholar 

  8. Farraj, A. K., & Hammad, E. M. (2013). Impact of quality of service constraints on the performance of spectrum sharing cognitive users. Wireless Personal Communications, 69, 673–688.

    Article  Google Scholar 

  9. Su, H., & Zhang, X. (2008). Cross-layer based opportunistic MAC protocols for QoS provisionings over cognitive radio wireless networks. IEEE Journal on Selected Areas in Communications, 26, 118–129.

    Article  Google Scholar 

  10. Su, H. & Zhang, X. (2009, October). Adaptive uplink MAC for CDMA-based cognitive radio networks. In IEEE military communications conference (MILCOM), pp. 1–7.

  11. Du, Q., & Zhang, X. (2010, May) Queue-aware spectrum sensing for interference-constrained transmissions in cognitive radio networks. In IEEE international conference on communications (ICC), pp. 1–5.

  12. Wang, L.-C., Wang, C.-W., & Adachi, F. (2011). Load-balancing spectrum decision for cognitive radio networks. IEEE Journal on Selected Areas in Communications, 29, 757–769.

    Article  Google Scholar 

  13. El-Sherif, A. A., & Liu, K. J. R. (2011). Joint design of spectrum sensing and channel access in cognitive radio networks. IEEE Transactions on Wireless Communications, 10, 1743–1753.

    Article  Google Scholar 

  14. Zhang, Y. (2008, May). Dynamic spectrum access in cognitive radio wireless Networks. In IEEE international conference on communications (ICC), pp. 4927–4932.

  15. Shiang, H.-P., & van der Schaar, M. (2008). Queuing-based dynamic channel selection for heterogeneous multimedia applications over cognitive radio networks. IEEE Transactions on Multimedia, 10, 896–909.

    Article  Google Scholar 

  16. Zhang, C. Wang, X., & Li, J. (2009, June). Cooperative cognitive radio with priority queueing analysis. In IEEE international conference on communications (ICC), pp. 1–5.

  17. Rashid, M. M., Hossain, M. J., Hossain, E., & Bhargava, V. K. (2009). Opportunistic spectrum scheduling for multiuser cognitive radio: A queueing analysis. IEEE Transactions on Wireless Communications, 8, 5259–5269.

    Article  Google Scholar 

  18. Farraj, A. K., Miller, S. L., & Qaraqe, K. A. (2011, December).Queue performance measures for cognitive radios in spectrum sharing systems. In IEEE international workshop on recent advances in cognitive communications and networking (RACCN)—Global telecommunications conference (GLOBECOM) workshop, pp. 997–1001.

  19. Chu, T. M. C., Phan, H., & Zepernick, H.-J. (2013). On the performance of underlay cognitive radio networks using M/G/1/K queueing model. IEEE Communications Letters, 99, 1–4.

    Google Scholar 

  20. Goldsmith, A. (2005). Wireless Communications (1st ed.). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  21. Bolch, G., Greiner, S., de Meer, H., & Trivedi, K. S. (2006). Queueing networks and Markov chains: Modeling and performance evaluation with computer science applications (2nd ed.). Hoboken, NJ: Wiley-Blackwell.

  22. Cover, T. M., & Thomas, J. A. (1991). Elements of information theory (1st ed.). New York: John Wiley & Sons.

    Book  MATH  Google Scholar 

  23. Miller, S. L., & Childers, D. G. (2004). Probability and random processes: With applications to signal processing and communications (1st ed.). Amsterdam: Elsevier Academic Press.

    Google Scholar 

  24. Giambene, G. (2005). Queuing theory and telecommunications: Networks and applications. New York: Springer-Verlag.

    Google Scholar 

  25. Adan, I., & Resing, J. (2001). Queueing theory. Available online at http://www.cs.duke.edu/~fishhai/misc/queue.pdf.

  26. Little, J. D. C. (1961). A proof of the queuing formula: \(L = \lambda W\). Operations Research, 9, 383–387.

    Article  MathSciNet  MATH  Google Scholar 

  27. Ma, Z., & Xu, Q. (2008). General decrementing service M/G/1 queue with multiple adaptive vacations. Applied Mathematics and Computation, 204, 478–484.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada

    Abdallah K. Farraj

Authors
  1. Abdallah K. Farraj
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abdallah K. Farraj.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Farraj, A.K. Queue Model Analysis for Spectrum-Sharing Cognitive Systems Under Outage Probability Constraint. Wireless Pers Commun 73, 1021–1035 (2013). https://doi.org/10.1007/s11277-013-1245-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-013-1245-2

Keywords

Search

Navigation