Table of Contents Author Guidelines Submit a Manuscript
Wireless Communications and Mobile Computing
Volume 2017, Article ID 9053862, 10 pages
https://doi.org/10.1155/2017/9053862
Research Article

Nash Equilibrium of an Energy Saving Strategy with Dual Rate Transmission in Wireless Regional Area Network

1College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan 454000, China
2College of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China

Correspondence should be addressed to Zhanqiang Huo; nc.ude.uph@qzh

Received 26 July 2017; Revised 19 October 2017; Accepted 25 October 2017; Published 20 November 2017

Academic Editor: Donatella Darsena

Copyright © 2017 Zhanqiang Huo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. The Climate Group, Smart 2020: Enabling the low carbon economy in the information age [EB/OL], 2008, http://www.theclimategroup.org.
  2. A. Dejonghe, B. Bougard, S. Pollin et al., “Green reconfigurable radio systems,” IEEE Signal Processing Magazine, vol. 24, no. 3, pp. 90–101, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. K. Hyunduk, H. Heonjin, and K. Changjoo, “Performance evaluation of a CR-based WRAN system using spectrum utilization efficiency,” in Proceedings of the 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, China, October 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. C. Stevenson, G. Chouinard, Z. Lei, W. Hu, S. Shellhammer, and W. Caldwell, “IEEE 802.22: the first cognitive radio wireless regional area network standard,” IEEE Communications Magazine, vol. 47, no. 1, pp. 130–138, 2009. View at Publisher · View at Google Scholar
  5. V. Balaji, P. Kabra, P. V. P. K. Saieesh, C. Hota, and G. Raghurama, “Cooperative Spectrum Sensing in Cognitive Radios Using Perceptron Learning for IEEE 802.22 WRAN,” in Proceedings of the 11th International Conference on Communication Networks, ICCN 2015, pp. 14–23, India, August 2015. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Bagwari, J. Kanti, G. S. Tomar, and A. Samarah, “Reliable spectrum sensing scheme based on dual detector with double-threshold for IEEE 802.22 WRAN,” Journal of High Speed Networks, vol. 21, no. 3, pp. 205–220, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. G. P. Joshi, S. Acharya, and S. W. Kim, “Fuzzy-logic-based channel selection in IEEE 802.22 WRAN,” Information Systems, vol. 48, pp. 327–332, 2015. View at Publisher · View at Google Scholar · View at Scopus
  8. J. Premalatha, U. Anitha, V. Manonmani, and P. Ganesan, “Survey on energy saving methods for green communication network,” Indian Journal of Science & Technology, vol. 8, no. 19, pp. 1–5, 2015. View at Publisher · View at Google Scholar · View at Scopus
  9. G. Rizzo, B. Rengarajan, and M. Ajmone Marsan, “The value of BS flexibility for QoS-aware sleep modes in cellular access networks,” in Proceedings of the 2014 IEEE International Conference on Communications Workshops, ICC 2014, pp. 883–888, Australia, June 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. G. Wu, L. Dong, Z. Qin, and Z. Xu, “Dynamic programming-based pico base station sleep mode control in heterogeneous networks,” International Journal of Communication Systems, vol. 30, no. 2, Article ID e2967, 2017. View at Publisher · View at Google Scholar · View at Scopus
  11. B. Lannoo, A. Dixit, S. Lambert, D. Colle, and M. Pickavet, “How sleep modes and traffic demands affect the energy efficiency in optical access networks,” Photonic Network Communications, vol. 30, no. 1, pp. 85–95, 2015. View at Publisher · View at Google Scholar · View at Scopus
  12. F. Wu and Z. Zheng, “Game theory based spectrum dynamic management,” Journal of Computer Research and Development, vol. 53, no. 1, pp. 38–52, 2016, (in Chinese). View at Google Scholar
  13. G. Wang and Z. Zeng, “Price-based spectrum access algorithm in cognitive radio networks,” Journal of Harbin University of Science and Technology, vol. 19, no. 2, pp. 115–119, 2014, (in Chinese). View at Google Scholar
  14. H. Li and Z. Han, “Socially optimal queuing control in cognitive radio networks subject to service interruptions: to queue or not to queue?” IEEE Transactions on Wireless Communications, vol. 10, no. 5, pp. 1656–1666, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. Y. Xie, X. Tan, L. Ma et al., “Spectrum allocation algorithm base on distributed game theory,” Systems Engineering and Electronics, vol. 37, no. 10, pp. 2391–2395, 2015, (in Chinese). View at Google Scholar
  16. N. H. Tran, C. S. Hong, Z. Han, and S. Lee, “Optimal pricing effect on equilibrium behaviors of delay-sensitive users in cognitive radio networks,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 11, pp. 2566–2579, 2013. View at Publisher · View at Google Scholar · View at Scopus
  17. A. S. Alfa, Queueing Theory for Telecommunications, Springer, New York, USA, 2010, 65-78. View at MathSciNet
  18. H. Niki, K. Harada, M. Morimoto, and M. Sakakihara, “The survey of preconditioners used for accelerating the rate of convergence in the Gauss-Seidel method,” Journal of Computational and Applied Mathematics, vol. 164, no. 1, pp. 587–600, 2004. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Kennedy, Encyclopedia of Machine Learning [M], Springer, New York, USA, 2011, 760-766.