DOI QR코드

DOI QR Code

Fair Power Control Using Game Theory with Pricing Scheme in Cognitive Radio Networks

  • Xie, Xianzhong (Chongqing Key Lab of Mobile Communications Technology at Chongqing University of Posts and Telecommunications) ;
  • Yang, Helin (Chongqing Key Lab of Mobile Communications Technology at Chongqing University of Posts and Telecommunications) ;
  • Vasilakos, Athanasios V. (Department of Computer and Telecommunications Engineering, University of Western Macedonia) ;
  • He, Lu (Chongqing Key Lab of Mobile Communications Technology at Chongqing University of Posts and Telecommunications)
  • Received : 2013.08.30
  • Published : 2014.04.30

Abstract

This paper proposes a payment-based power control scheme using non-cooperative game with a novel pricing function in cognitive radio networks (CRNs). The proposed algorithm considers the fairness of power control among second users (SUs) where the value of per SU' signal to noise ratio (SINR) or distance between SU and SU station is used as reference for punishment price setting. Due to the effect of uncertainty fading environment, the system is unable to get the link gain coefficient to control SUs' transmission power accurately, so the quality of service (QoS) requirements of SUs may not be guaranteed, and the existence of Nash equilibrium (NE) is not ensured. Therefore, an alternative iterative scheme with sliding model is presented for the non-cooperative power control game algorithm. Simulation results show that the pricing policy using SUs' SINR as price punishment reference can improve total throughput, ensure fairness and reduce total transmission power in CRNs.

Keywords

References

  1. FCC, "Spectrum policy task force report," no. 02-135, Nov. 2002.
  2. Y. C. Liang, K. C. Chen, G. Li, and P. Mahonen, "Cognitive radio networking and communications: An overview," IEEE Trans. Veh. Technol., vol. 60, no. 7, pp. 3386-3407, Sept. 2011. https://doi.org/10.1109/TVT.2011.2158673
  3. M. Maskery, V. Krishnamurthy, and Q. Zhao, "Decentralized dynamic spectrum access for cognitive radios: cooperative design of a noncooperative game," IEEE Trans. Commun., vol. 57, no. 7, pp. 459-469, Feb. 2009. https://doi.org/10.1109/TCOMM.2009.02.070158
  4. B. Wang, Y. Wu, and K. J. R. Liu, "Game theory for cognitive radio networks: An overview," Comput. Netw., vol. 54, no. 14, pp. 2537-2561, Oct. 2010. https://doi.org/10.1016/j.comnet.2010.04.004
  5. D. J. Goodman and N. B. Mandayam, "Power control for wireless data," IEEE Pers. Commun., vol. 7, no. 2, pp. 48-54, Apr. 2000. https://doi.org/10.1109/98.839331
  6. C. U. Saraydar, N. B. Mandayam, and D. Goodman, "Effcient power control via pricing in wireless data networks," IEEE Trans. Commun., vol. 50, no. 2, pp. 291-303, Feb. 2002. https://doi.org/10.1109/26.983324
  7. F. Nan, M. Siun-Chuon, and N. B. Mandayam, "Pricing and power control for joint network-centric and user-centric radio resource management," IEEE Trans. Commun., vol. 52, no. 9, pp. 1547-1557, Sept. 2004. https://doi.org/10.1109/TCOMM.2004.833191
  8. F. Nan, M. Siun-Chuon, and N. B. Mandayam, "Joint network-centric and user-centric radio resource management in a multicell system," IEEE Trans. Commun., vol. 53, no. 7, pp. 1114-1118, July 2005. https://doi.org/10.1109/TCOMM.2005.851629
  9. S. Lasaulce, Y. Hayel, R. E. Azouzi, and M. Debbah, "Introducing hierarchy in energy games," IEEE Trans. Wireless Commun., vol. 8, no. 7, pp. 3833-3843, July 2009. https://doi.org/10.1109/TWC.2009.081443
  10. S. Buzzi and D. Saturnino, "A game-theoretic approach to energy efficient power control and receiver design in cognitive CDMA wireless networks," IEEE J. Sel. Topics Signal Process., vol. 5, no. 1, pp. 137-150, Feb. 2011. https://doi.org/10.1109/JSTSP.2010.2054065
  11. M. L. Treust and S. Lasaulce, "A repeated game formulation of energyefficient decentralized power control," IEEE Trans. Wireless Commun., vol. 9, no. 9, pp. 2860-2869, Sept. 2010. https://doi.org/10.1109/TWC.2010.072610.091472
  12. X. D. Zhang, Y. F. Zhang, Y. H. Shi, L. Zhao, and C. R. Zou, "Power control algorithm in cognitive radio system based on modifed shuffed frog leaping algorithm," Int. J. Electron. Commun., vol. 66, no. 6, pp. 448-454, June 2012. https://doi.org/10.1016/j.aeue.2011.10.004
  13. F. Li, X. Z. Tan, and L. Wang, "A new game algorithm for power control in cognitive radio networks," IEEE Trans. Veh. Technol., vol. 60, no. 9, pp. 4384-4391, Nov. 2011. https://doi.org/10.1109/TVT.2011.2172474
  14. M. Alayesh and N. Ghani, "Game-theoretic approach for primarysecondary user power control under fast at fading channels, " IEEE Commun. Lett., vol. 15, no. 5, pp. 491-493, Nov. 2011. https://doi.org/10.1109/LCOMM.2011.031611.101271
  15. Y. Kuo, J. Yang, and J. Chen, "Efficient swarm intelligent algorithm for power control game in cognitive radio networks," IET Commun., vol. 7, no. 11, pp. 1089-1098, July 2013. https://doi.org/10.1049/iet-com.2012.0780
  16. H. Yu, L. Gao, Z. Li, X. Wang, and E. Hossain, "Pricing for uplink power control in cognitive radio networks," IEEE Trans. Veh. Technol., vol. 59, no. 4, pp. 1769-1778, May 2010. https://doi.org/10.1109/TVT.2010.2040492
  17. L. Duan, J. Huang, and B. Shou, "Investment and pricing with spectrum uncertainty: A cognitive operator's perspective," IEEE Trans. Mobile Comput., vol. 10, no. 11, pp. 1590-1604, Nov. 2011. https://doi.org/10.1109/TMC.2011.78
  18. Y. Wu, T. Zhang, and D. Tsang, "Joint pricing and power allocation for dynamic spectrum access networks with stackelberg game model," IEEE Trans. Wireless Commun., vol. 10, no. 1, pp. 12-19, Jan. 2011. https://doi.org/10.1109/TWC.2010.120310.091430
  19. M. Hajiaghayi, M. Dong, and B. Liang, "Maximizing lifetime in relay cooperation through energy-aware power allocation," IEEE Trans. Signal Process., vol. 58, no. 8, pp. 4354-4366, Aug. 2010. https://doi.org/10.1109/TSP.2010.2049571
  20. Z. Wang, L. G. Jiang, and C. He, "A novel price-based power control algorithm in cognitive radio networks," IEEE Commun. Lett., vol. 17, no. 1, pp. 43-46, Jan. 2013. https://doi.org/10.1109/LCOMM.2012.120612.121587
  21. K. W. Lu, L. J. Zhang, and J. Yang, "An efficient SIR-first adaptive power control method in cognitive radio network," in Proc. IEEE GHTCE, Nov. 2012, pp. 91-94.
  22. Y. X. Zu, Y. F. Liu, S. B. Mao, and Y. Jia, "Power control algorithm based on SNR cost function in cognitive radio system," in Proc. IEEE ICPADS, Dec. 2012, pp. 913-917.
  23. J. Huang, R. A. Berry, and M. L. Honig, "Distributed interference compensation for wireless networks," IEEE J. Sel. Areas Commun., vol. 24, no. 5, pp. 1074-1084, May 2006. https://doi.org/10.1109/JSAC.2006.872889
  24. M. B. Xiao, N. B. Shroff, and E. K. P. Chong, "Utility-based power control in cellular wireless systems," in Proc. INFOCOM, vol. 1, no. 1, Apr. 2001, pp. 412-421.
  25. Z. Han and K. J. R. Liu, "Non-cooperative power-control game and throughput game over wireless networks," IEEE Trans. Commun., vol. 53, no. 10, pp. 1625-1629, Feb. 2005. https://doi.org/10.1109/TCOMM.2005.857136
  26. D. M. Topkis, Supermodularity and Complementarity. Princeton University, 1998.
  27. A. J. Viterbi, CDMA: Principles of Spread Spectrum Communication. MA: Addison-Wesley, 1995.
  28. V. V. Kulkarni, J. Biswas, R. P. Liu, I. B. Collings, and S. K. Jha, "Robust power allocation for MIMO beamforming under time varying channel conditions," in Proc. IEEE VTC, Sept. 2011, pp. 5-8.
  29. V. Utkin, "Variable structure systems with sliding modes," IEEE Trans. Autom. Control, vol. 22, no. 2, pp. 212-222, Sept. 1977. https://doi.org/10.1109/TAC.1977.1101446