KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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A Novel Prediction-based Spectrum Allocation Mechanism for Mobile Cognitive Radio Networks

  • Wang, Yao (Communication Research Center, Harbin Institute of Technology) ;
  • Zhang, Zhongzhao (Communication Research Center, Harbin Institute of Technology) ;
  • Yu, Qiyue (Communication Research Center, Harbin Institute of Technology) ;
  • Chen, Jiamei (Communication Research Center, Harbin Institute of Technology)
  • Received : 2013.05.27
  • Accepted : 2013.09.08
  • Published : 2013.09.30
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Abstract

The spectrum allocation is an attractive issue for mobile cognitive radio (CR) network. However, the time-varying characteristic of the spectrum allocation is not fully investigated. Thus, this paper originally deduces the probabilities of spectrum availability and interference constrain in theory under the mobile environment. Then, we propose a prediction mechanism of the time-varying available spectrum lists and the dynamic interference topologies. By considering the node mobility and primary users' (PUs') activity, the mechanism is capable of overcoming the static shortcomings of traditional model. Based on the mechanism, two prediction-based spectrum allocation algorithms, prediction greedy algorithm (PGA) and prediction fairness algorithm (PFA), are presented to enhance the spectrum utilization and improve the fairness. Moreover, new utility functions are redefined to measure the effectiveness of different schemes in the mobile CR network. Simulation results show that PGA gets more average effective spectrums than the traditional schemes, when the mean idle time of PUs is high. And PFA could achieve good system fairness performance, especially when the speeds of cognitive nodes are high.

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References

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