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Pre-reservation based spectrum allocation for cognitive radio network

Author

Listed:
  • Tuğrul Çavdar

    (Karadeniz Technical University)

  • Zhaleh Sadreddini

    (Karadeniz Technical University)

  • Erkan Güler

    (Giresun University)

Abstract

Studies on the current usage of the radio spectrum by several agencies have already revealed that a large fraction of the radio spectrum is inadequately utilized. This basic finding has led to numerous research initiatives. Cognitive radio technology is one of the key candidate technologies to solve the problems of spectrum scarcity and low spectrum utilization. However, random behavior of the primary user (PU) appears to be an enormous challenge. In this paper, a Pre-reservation based spectrum allocation method for cognitive radio network is proposed to apply a PU behavior aware joint spectrum band (SB) selection and allocation scheme. In the first step, the SB is observed in terms of PU usage statistics whereas in the second phase, a network operator (NO) using a spectrum allocation scheme is employed to allocate SBs among secondary users (SUs). We also introduce the concept of reservation and exchange functionality under the priority serving strategy in a time-varying framing process. Simulation results show that the proposed scheme outperforms existing schemes in terms of the spectrum utilization and network revenue. In addition, it helps NO to manage the spectrum on a planned basis with a systematical spectrum reservation management where the NO has the status of time slots. Moreover, SUs have an opportunity to reserve or instantly request a SB that maximizes the SUs satisfaction in terms of quality of experience.

Suggested Citation

  • Tuğrul Çavdar & Zhaleh Sadreddini & Erkan Güler, 2018. "Pre-reservation based spectrum allocation for cognitive radio network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(4), pages 723-743, August.
    • Handle: RePEc:spr:telsys:v:68:y:2018:i:4:d:10.1007_s11235-018-0424-6
    DOI: 10.1007/s11235-018-0424-6
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    References listed on IDEAS

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    1. K. Coussement & D. Van Den Poel, 2006. "Churn Prediction in Subscription Services: an Application of Support Vector Machines While Comparing Two Parameter-Selection Techniques," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/412, Ghent University, Faculty of Economics and Business Administration.
    2. Kouroush Jenab & Sam Khoury & Ahmad R. Sarfaraz, 2012. "Manufacturing Complexity Analysis with Fuzzy AHP," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 3(2), pages 31-46, April.
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    Cited by:

    1. Ghassan Alnwaimi & Hatem Boujemaa, 2019. "Throughput analysis and optimization of cognitive radio networks using incremental relaying," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 71(2), pages 231-247, June.

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