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Conclusions and Future Directions

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Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

The objective of this Brief is to study the voice capacity of CRNs and the mean response time of elastic/interactive data traffic over the CRNs with different service processes. As there is an uncertainty in spectrum resource availability, rather than a strict delay requirement, a stochastic delay requirement is considered as the main QoS parameter for voice capacity analysis. For data applications, we have shown that the variations of the mean channel available/non-available durations have a significant impact on the mean response time even when the mean channel availability is constant. Therefore, the mean response time evaluations based on the mean channel availability are not suitable in the context of the CRNs. We have obtained a relationship between the mean response times of elastic data traffic and interactive data traffic under the Poisson approximation of the request arrivals at the base station, which can be used for QoS provisioning in Web traffic over CRNs.

Keywords

  • Cooperative Spectrum
  • Service Discipline
  • Primary Network
  • Secondary Network
  • Channel Availability

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.

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  • DOI: 10.1007/978-3-319-04645-7_5
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Notes

  1. 1.

    When the primary network is time-slotted, as the worst case scenario, whole information frame is assumed to be lost due an interference caused by the secondary network. However, the actual interference duration depends on how the information packets are organized and transmitted within the time-slot (by a PU).

References

  1. Pei, Y., Hoang, A.T., Liang, Y.C.: Sensing throughput trade-off in cognitive radio networks: how frequently should spectrum sensing be carried out? In: Proc. IEEE PIMRC, pp. 5330–5335 (2007)

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  2. Mallik, R.K., Letaief, K.: Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks. IEEE Trans. Wireless Commun. 8(12), 5761–5766 (2009)

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Gunawardena, S., Zhuang, W. (2014). Conclusions and Future Directions. In: Modeling and Analysis of Voice and Data in Cognitive Radio Networks. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-04645-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-04645-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04644-0

  • Online ISBN: 978-3-319-04645-7

  • eBook Packages: Computer ScienceComputer Science (R0)