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Analytical modelling of a cognitive IEEE 802.11 wireless local area network overlaid on a cellular network

Analytical modelling of a cognitive IEEE 802.11 wireless local area network overlaid on a cellular network

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In this study, the authors propose an analytical model to evaluate the maximum stable throughput and average delay of a cognitive IEEE 802.11-based wireless local area network (WLAN) overlaid on uplink band of a cellular network. The main feature of the proposed model is to include different status of the cognitive users, that is, different spectrum opportunities for different secondary users, as the result of dynamic nature of primary users as well as different locations of the cognitive users relative to primary ones. The proposed model has been founded on an open queueing network comprised of several queueing nodes equivalent to different states of a typical secondary user. By mapping the details of MAC scheme of the cognitive WLAN and dynamic nature of spectrum opportunities onto suitable parameters of the proposed analytical model and writing the corresponding traffic equations, the authors are able to find the maximum stable throughput, that is, the maximum rate of packet generation at the cognitive nodes guaranteeing the stability of all nodes. Below this rate, that is, at the rate when all cognitive nodes are in non-saturation mode, with resort to the proposed analytical model the authors are able to evaluate the average delay comprised of the queueing delay as well as the transmission delay. The authors also show the applicability of our approach in evaluating the effect of different parameters of the cognitive network scenario, for example, the number of users, activity factors etc., onto the maximum stable throughput and non-saturation average delay. Simulation results confirm the validity of the authors analytical approach.

References

    1. 1)
      • Federal Communications Commission (FCC), Spectrum Policy Task Force, November 15, 2002. ET Docket no. 02-135.
    2. 2)
    3. 3)
    4. 4)
      • Hsu, A., Wei, S., Kuo, C.: `A cognitive MAC protocol using statistical channel allocation for wireless ad-hoc networks', Proc. WCNC, 2007, p. 105–110.
    5. 5)
      • Wang, L., Chen, A., Wei, D.: `A cognitive MAC protocol for QoS provisioning in overlaying ad hoc networks', Proc. CCNC, 2007, p. 1139–1143.
    6. 6)
    7. 7)
      • Cheng, G., Liu, W., Cheng, W.: `Joint on-demand routing and spectrum assignment in cognitive radio networks', Proc. ICC'07, 2007, p. 6499–6503.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
      • Chen, Y., Cho, C., You, I., Chao, H.: `A cross-layer protocol of spectrum mobility and handover in cognitive LTE networks', Proc. Simulation Modeling Practice and Theory, 2011, p. 1723–1744.
    12. 12)
    13. 13)
      • Feizi-Khankandi, S., Ashtiani, F.: `Lower and upper bounds for throughput capacity of a cognitive ad hoc network overlaid on a cellular network', Proc. WCNC, 2008, p. 2759–2764.
    14. 14)
    15. 15)
      • X. Chao , M. Miyazawa , M. Pinedo . (1999) Queueing networks.
    16. 16)
    17. 17)
      • Moradian, M., Ashtiani, F.: `Throughput analysis of cognitive IEEE 802.11 WLAN sharing the downlink band of a cellular network', Proc. IEEE ICC'11, June 2011, Kyoto.
    18. 18)
    19. 19)
    20. 20)
      • Yeh, W.P., Hammond, J.L., Tipper, D.: `Sensitivity of bandwidth allocation algorithms for unidirectional networks to voice parameters', Proc. IEEE ICC'90, April 1990, p. 1295–1299.
    21. 21)
      • L. Kleinrock . (1975) Queueing systems.
    22. 22)
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