access icon free Queue performance of cognitive radio networks with general primary user activity model

The quality of service (QoS) performance analysis is of great guiding significance for a QoS guarantee of secondary users (SUs). However, the QoS performance of SUs has not been well studied, especially how it is impacted by the traffic property of primary users (PUs). In this study, the authors propose a method to analyse the queue performance of the SU when the active and inactive durations of PUs follow general distributions. To characterise the non-memoryless property of the channel when the distributions of PUs active/inactive durations are general distributions, they propose a two-dimensional Markov chain to model the states of the channel. By using this Markov chain, they derive the effective capacity (EC) function of the cognitive radio network. On the basis of the EC function and the effective bandwidth function, the queue performance of the SU, that is, the stationary tail distribution of the queue length, is estimated. The author's result can not only be used to calculate other QoS metrics, such as the buffer overflow probability and throughput, but also provide some guidelines for QoS guarantee of the SU. Finally, they verify their work by comparing the analytical results with simulation results.

Inspec keywords: statistical distributions; quality of service; wireless channels; queueing theory; cognitive radio; Markov processes

Other keywords: inactive PU duration distribution; queue performance analysis; QoS guarantee; queue length; throughput; buffer overflow probability; effective bandwidth function; channel state model; cognitive radio networks; effective capacity function; channel nonmemoryless property; 2D Markov chain; stationary tail distribution estimation; EC function; general primary user activity model; active PU duration distribution

Subjects: Radio links and equipment; Queueing theory; Markov processes

References

    1. 1)
    2. 2)
      • 16. Goldsmith, A.J.: ‘Wireless Communications’ (Cambridge University Press, New York, 2005, 1st edn.).
    3. 3)
    4. 4)
      • 19. Wu, D., Negi, R.: ‘Effective capacity: a wireless link model for support of quality of service’, IEEE Trans. Wirel. Commun., 2003, 2, (4), pp. 630643.
    5. 5)
    6. 6)
    7. 7)
      • 17. Bolch, G., Greiner, S., Meer, H.D., Trivedi, K.S.: ‘Queueing networks and Markov chains: modeling and performance evaluation with computer science applications’ (John Wiley & Sons, Hoboken, New Jersey, 2006, 2nd edn.).
    8. 8)
      • 20. Chang, C.-S.: ‘Performance Guarantees in communication networks’ (Springer-Verlag, London, 2000, 1st edn.).
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
      • 10. Willkomm, D., Machiraju, S., Bolot, J., Wolisz, A.: ‘Primary users in cellular networks: a large-scale measurement study’. Proc. IEEE DySPAN, Chicago, IL, USA, October 2008, pp. 111.
    14. 14)
    15. 15)
    16. 16)
      • 5. Laourine, A., Chen, S., Tong, L.: ‘Queuing analysis in multichannel cognitive spectrum access: a large deviation approach’. Proc. IEEE INFOCOM, San Diego, USA, March 2010, pp. 19.
    17. 17)
    18. 18)
    19. 19)
    20. 20)
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