© The Institution of Engineering and Technology
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.
References
-
-
1)
-
22. Yucek, T., Arslan, H.: ‘A survey of spectrum sensing algorithms for cognitive radio applications’, IEEE Commun. Surv. Tutorials, 2009, 11, (1), pp. 116–130 (doi: 10.1109/SURV.2009.090109).
-
2)
-
16. Goldsmith, A.J.: ‘Wireless Communications’ (Cambridge University Press, New York, 2005, 1st edn.).
-
3)
-
3. Wang, S., Zhang, J., Tong, L.: ‘A characterization of delay performance of cognitive medium access’, IEEE Trans. Wirel. Commun., 2012, 11, (2), pp. 800–809 (doi: 10.1109/TWC.2012.010312.110765).
-
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. 630–643.
-
5)
-
19. Wang, L.-C., Wang, C.-W., Chang, C.-J.: ‘Modeling and analysis for spectrum handoffs in cognitive radio networks’, IEEE Trans. Mob. Comput., 2012, 11, (9), pp. 1499–1513 (doi: 10.1109/TMC.2011.155).
-
6)
-
15. Akin, S., Gursoy, M.C.: ‘Performance analysis of cognitive radio systems under QoS constraints and channel uncertainty’, IEEE Trans. Wirel. Commun., 2011, 10, (10), pp. 2883–2895 (doi: 10.1109/TWC.2011.062911.100743).
-
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)
-
20. Chang, C.-S.: ‘Performance Guarantees in communication networks’ (Springer-Verlag, London, 2000, 1st edn.).
-
9)
-
13. Xiao, X., Liu, K., Zhao, Q.: ‘Opportunistic spectrum access in self-similar primary traffic’, EURASIP J. Adv. Signal Process., 2009, 2009, (9), pp. 1–8 (doi: 10.1155/2009/762547).
-
10)
-
4. Akin, S., Gursoy, M.: ‘Effective capacity analysis of cognitive radio channels for quality of service provisioning’, IEEE Trans. Wirel. Commun., 2010, 9, (11), pp. 3354–3364 (doi: 10.1109/TWC.2010.092410.090751).
-
11)
-
18. Liu, Q., Zhou, S., Giannakis, G.: ‘Cross-layer combining of adaptive modulation and coding with truncated ARQ over wireless links’, IEEE Trans. Wirel. Commun., 2004, 3, (5), pp. 1746–1755 (doi: 10.1109/TWC.2004.833474).
-
12)
-
6. Wang, J., Huang, A., Cai, L., Wang, W.: ‘On the queue dynamics of multiuser multichannel cognitive radio networks’, IEEE Trans. Veh. Technol., 2013, 62, (3), pp. 1314–1328 (doi: 10.1109/TVT.2012.2229475).
-
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. 1–11.
-
14)
-
2. Mitola, J., Maguire, G.Q.: ‘Cognitive radio: making software radios more personal’, IEEE Pers. Commun., 1999, 6, (4), pp. 13–18 (doi: 10.1109/98.788210).
-
15)
-
8. Zhao, Q., Krishnamachari, B., Liu, K.: ‘On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance’, IEEE Trans. Wirel. Commun., 2008, 7, (12), pp. 5431–5440 (doi: 10.1109/T-WC.2008.071349).
-
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. 1–9.
-
17)
-
2. Wong, E.W., Foh, C.H.: ‘Analysis of cognitive radio spectrum access with finite user population’, IEEE Commun. Lett., 2009, 13, (5), pp. 294–296 (doi: 10.1109/LCOMM.2009.082113).
-
18)
-
7. Chen, R.-R., Liu, X.: ‘Delay performance of threshold policies for dynamic spectrum access’, IEEE Trans. Wirel. Commun., 2011, 10, (7), pp. 2283–2293 (doi: 10.1109/TWC.2011.050511.101292).
-
19)
-
14. Simeone, O., Bar-Ness, Y., Spagnolini, U.: ‘Stable throughput of cognitive radios with and without relaying capability’, IEEE Trans. Commun., 2007, 55, (12), pp. 2351–2360 (doi: 10.1109/TCOMM.2007.910699).
-
20)
-
9. Saad, W., Han, Z., Poor, H., Basar, T., Song, J.B.: ‘A cooperative Bayesian nonparametric framework for primary user activity monitoring in cognitive radio networks’, IEEE J. Sel. Areas Commun., 2012, 30, (9), pp. 1815–1822 (doi: 10.1109/JSAC.2012.121027).
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