Spectrum and energy efficiency of cooperative spectrum prediction in cognitive radio networks
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In this paper, the spectrum and energy efficiency of cooperative spectrum prediction (CSP) in cognitive radio networks are investigated. In addition, the performance of cooperative spectrum prediction is evaluated using a hidden Markov model (HMM) and a multilayer perceptron (MLP) neural network. The cooperation between secondary users in predicting the next channel status employs AND, OR and majority rule fusion schemes. These schemes are compared for HMM and MLP predictors as a function of channel occupancy in term of prediction error, spectrum efficiency and energy efficiency. The impact of busy and idle state prediction errors on the spectrum efficiency is also investigated. Simulation results are presented which show a significant improvement in the spectrum efficiency of the secondary users CSP with the majority rule at the cost of a small degradation in energy efficiency compared to single spectrum prediction and traditional spectrum sensing.
KeywordsCognitive radio Spectrum sensing Single spectrum prediction Cooperative spectrum prediction Energy efficiency Spectrum efficiency
The first author is pleased to acknowledge the financial support from the University of Tripoli, Tripoli, Libya.
- 5.Eltom, H., Kandeepan, S., Liang, Y. C., Moran, B., & Evans, R. J. (2016). HMM based cooperative spectrum occupancy prediction using hard fusion. In IEEE international conference on communications workshops (pp. 669–675).Google Scholar
- 6.Chatziantoniou, E., Allen, B. & Velisavljevic, V. (2013). An HMM-based spectrum occupancy predictor for energy efficient cognitive radio. In IEEE international symposium on personal indoor and mobile radio communications (pp. 601–605).Google Scholar
- 7.Ahmadi, H., Chew, Y. H., Tang, P. K., & Nijsure, Y. A. (2011). Predictive opportunistic spectrum access using learning based hidden Markov models. In IEEE international symposium on personal indoor and mobile radio communications (pp. 401–405).Google Scholar
- 8.Ahmadi, H., Macaluso, I., & DaSilva, L. A. (2013). The effect of the spectrum opportunities diversity on opportunistic access. In IEEE international conference on communications (pp. 2829–2834).Google Scholar
- 11.Yang, J., Zhao, H. S., Chen, X., Xu, J. Y., & Zhang, J. Z. (2014). Energy-efficient design of spectrum prediction in cognitive radio networks: Prediction strategy and communication environment. Prediction strategy and communication environment. In International conference on signal processing (pp. 154–158).Google Scholar