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A novel adaptive spectrum reservation strategy in CRNs and its performance optimization

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Abstract

Spectrum reservation strategy is an effective technology for conserving communication resources in Cognitive Radio Networks. In order to better adapt to changes of the system load, we present an adaptive control approach to determine the reservation ratio of the licensed spectrum for secondary users and propose a novel adaptive spectrum reservation strategy. We then establish a three-dimensional discrete time Markov Chain model to capture the stochastic behavior of users. By using a method similar to that of the matrix geometric solution, we obtain the steady-state probability distribution for the system model, and derive the formulas for some required performance measures of two types of users. Numerical experiments and simulation experiments indicate that the system performance is sensitive to system parameters like the adaptive control factor and the admission threshold. Finally, we construct a system cost function to balance different performance measures, and present an intelligent searching algorithm to optimize the system parameters with the global minimum system cost.

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Acknowledgements

This work was supported in part by National Science Foundation (No. F61472342), China and was supported in part by MEXT, Japan.

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Authors and Affiliations

  1. School of Information Science and Engineering, Yanshan University, Qinhuangdao, China

    Jianping Liu & Shunfu Jin

  2. Hebei Normal University of Science and Technology, Qinhuangdao, China

    Jianping Liu

  3. Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao, China

    Shunfu Jin

  4. Department of Intelligence and Informatics, Konan University, Kobe, Japan

    Wuyi Yue

Authors
  1. Jianping Liu
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  2. Shunfu Jin
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  3. Wuyi Yue
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Correspondence to Shunfu Jin.

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Liu, J., Jin, S. & Yue, W. A novel adaptive spectrum reservation strategy in CRNs and its performance optimization. Optim Lett 12, 1215–1235 (2018). https://doi.org/10.1007/s11590-016-1093-6

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  • DOI: https://doi.org/10.1007/s11590-016-1093-6

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