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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

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.

Keywords

References

  1. S. H. Sohn, N. Han, G. B. Zheng, and Jae Moung Kim, "Pilot periodicity based OFDM signal detection method for cognitive radio system," IEICE Transactions on Communication, vol. E91-B, no. 5, pp.1644-1647, May, 2008. https://doi.org/10.1093/ietcom/e91-b.5.1644
  2. N. Han, S. H. Sohn, and J. M. Kim, "A blind OFDM detection and identification method based on cyclostationarity for cognitive radio application," IEICE Transactions on Communication, vol. E92-B, no.6, pp.2235-2238, June, 2009. https://doi.org/10.1587/transcom.E92.B.2235
  3. Zeyang Dai, Jian Liu, Chong gang Wang, and Keping Long, "An adaptive cooperation communication strategy for enhanced opportunistic spectrum access in cognitive radios," IEEE Communications Letters, vol. 16, no. 1, pp. 40-43, January, 2012. https://doi.org/10.1109/LCOMM.2011.111011.111418
  4. M. Thoppian, S. Venkatesan, R. Prakash, and R. Chandrasekaran, "MAC-layer scheduling in cognitive radio based multi-hop wireless networks," in Proc. of the 2006 International Symposium on World of Wireless, Mobile and Multimedia Networks, pp. 191-202, June, 2006.
  5. S. Gandham, M. Dawande, and R. Prakash, "Link scheduling in sensor networks: distributed edge coloring revisited," in Proc. of IEEE INFOCOM, 4, pp. 2492-2501, March, 2005.
  6. Wei Wang, Xin Liu, "List-coloring based channel allocation for open-spectrum wireless networks," in Proc. of IEEE 62nd Vehicular Technology Conference, 1, pp.690-694, September 2005.
  7. Haitao Zheng, Chunyi Peng, "Collaboration and fairness in opportunistic spectrum access," in Proc. of IEEE International Conference on Communications, pp.3132-3136, May, 2005.
  8. C. L. Liao, J. Chen, and Y. X. Tang, "Parallel algorithm of spectrum allocation in cognitive radio," Journal of Electronics & Information Technology, vol. 29, no. 7, pp. 1608-1611, July, 2007.
  9. Yutao Liu, Mengxiong Jiang, Xuzhi Tan, and Lu Fan, "Maximal independent set based channel allocation algorithm in cognitive radios," in Proc. of IEEE Youth Conference on Information, Computing and Telecommunication, pp. 78-81, September, 2009.
  10. Beibei Wang, Zhu Ji, K. J. R. Liu, and Clancy, T.C., "Primary-prioritized Markov approach for dynamic spectrum allocation," IEEE Transactions on Wireless Communications, vol. 8, no. 4, pp. 1854-1865, April, 2009. https://doi.org/10.1109/T-WC.2008.080031
  11. V. Asghari, Sonia Aissa, "Adaptive rate and power transmission in spectrum-sharing systems," IEEE Transactions on Wireless Communications, vol. 9, no. 10, pp. 3272-3280, October, 2010. https://doi.org/10.1109/TWC.2010.090210.100291
  12. E. Jung, Xin Liu, "Opportunistic spectrum access in multiple-primary-user environments under the packet collision constraint," IEEE/ACM Transactions on Networking, vol. 19, no. 6, pp. 1-14, April, 2011. https://doi.org/10.1109/TNET.2010.2091968
  13. Chengyu Wu, Chen He, Lingge Jiang, and Yunfei Chen, "A novel spectrum handoff scheme with spectrum admission control in cognitive radio networks," in Proc. of Global Telecommunications Conference (GLOBECOM), pp. 1-5, December, 2011.
  14. Xiukui Li, S. A. Zekavat, "Traffic pattern prediction and performance investigation for cognitive radio systems," in Proc. of Wireless Communications and Networking Conference (WCNC), pp. 894-899, March, 2008.
  15. Sixing Yin, Dawei Chen, Qian Zhang, and ShuFang Li, "Prediction-based throughput optimization for dynamic spectrum access," IEEE Transactions on Vehicular Technology, vol. 60, no. 3, pp. 1284-1289, March, 2011. https://doi.org/10.1109/TVT.2010.2101090
  16. M. Grossglauser, D. N. C. Tse, "Mobility increases the capacity of ad hoc wireless networks," IEEE/ACM Transactions on Networking, vol. 10, no. 4, pp. 477-486, August, 2002. https://doi.org/10.1109/TNET.2002.801403
  17. A. C. Talay, D. T. Altilar, "United Nodes: Cluster-based routing protocol for mobile cognitive radio networks," in Proc. of IET Communications, vol. 5, no. 15, pp. 2097-2105, October, 2011. https://doi.org/10.1049/iet-com.2010.0285
  18. Q. S. Guan, F. R. Yu, S. M. Jiang, and Gang Wei, "Prediction-based topology control and routing in cognitive radio mobile ad hoc networks," IEEE Transactions on Vehicular Technology, vol. 59, no. 9, pp. 4443-4451, November, 2010. https://doi.org/10.1109/TVT.2010.2069105
  19. Hai Jiang, Lifeng Lai, Rongfei Fan, and Poor, H.V., "Optimal selection of channel sensing order in cognitive radio," IEEE Transactions on Wireless Communication, vol. 8, no.1, pp. 297-307, January, 2009. https://doi.org/10.1109/T-WC.2009.071363
  20. Zhiqiang Li, R. R. Yu, and Minyi Huang, "A distributed consensus-based cooperative spectrum sensing in cognitive radios," IEEE Transactions on Vehicular Technology, vol. 59, no. 1, pp. 383-393, January, 2010. https://doi.org/10.1109/TVT.2009.2031181
  21. R. W. Thomas, L. A. Dasilva, and A. B. Mackenzie, "Cognitive networks," in Proc. of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, pp.352-360, November, 2005.
  22. Anthony McGregor, Mark Hall, Perry Lorier, and James Brunskill, "Flow clustering using machine learning techniques," in Proc. of 5th Int. Workshop on Passive and Active Network Measurement, pp.205-214, April, 2004.
  23. C. T. Chou, S. N. Sai, H. Kim, and Shin, K.G., "What and how much to gain by spectrum agility," IEEE Journal on Selected Areas in Communication, vol. 25, no. 3, pp.576-588, April, 2007. https://doi.org/10.1109/JSAC.2007.070408
  24. H. Kim, K. G. Shin, "Efficient discovery of spectrum opportunities with MAC-layer sensing in cognitive radio networks," IEEE Transactions on Mobile Computing, vol. 7, no. 5, pp. 533-545, May, 2008. https://doi.org/10.1109/TMC.2007.70751
  25. Shengming Jiang, Dajiang He, and Jianqiang Rao, "A prediction-based link availability estimation for routing metrics in manets," IEEE/ACM Transactions on Networking, vol. 13, no. 6, pp. 1302-1311, December, 2005. https://doi.org/10.1109/TNET.2005.860094
  26. A. B. Mcdonald, T. F. Znati, "A mobility-based framework for adaptive clustering in wireless ad hoc networks," IEEE Journal on Selected Areas in Communications, vol. 17, no. 8, pp. 1466-1487, August, 1999. https://doi.org/10.1109/49.780353
  27. Chunyi Peng, Haitao Zheng, and B. Y. Zhao, "Utilization and fairness in spectrum assignment for opportunistic spectrum access," in Proc. of IEEE International Conference on Communications (ICC), pp. 3132-3136, May, 2005.
  28. A. A. Tabassam, M. U. Suleman, "Spectrum estimation and spectrum hole opportunities prediction for cognitive radios using higher-order statistics," Wireless Advanced, pp.213-217, June, 2011.
  29. Xiukui Li, Zekavat Reza, and A Seyed, "Cognitive Radio Based Spectrum Sharing: Evaluating Channel Availability via Traffic Pattern Prediction," IEEE Journal of communications and networks, vol. 11, no. 2, pp.104-114, April, 2009. https://doi.org/10.1109/JCN.2009.6391385
  30. Matthias Wellens, Janne Riihijarvi, and Petri Mahonen, "Empirical time and frequency domain models of spectrum use," Physical Communication, vol. 2, no.1 , pp.10-32, March, 2009. https://doi.org/10.1016/j.phycom.2009.03.001

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