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Demand-Aware Opportunistic Spectrum Access: A Game-Theoretic Learning Approach

  • Yuli Zhang
  • Xucheng Zhu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)

Abstract

We study the problem of opportunistic spectrum access with users’ demands in distributed systems. The users’ demands play an important role in estimating the final access results. For example, the same throughput may lead to completely different experience for the users with different demands. To emphasize the influence of the demand, we use the ratio of demand and throughput to consider them together. We focus on the sum ratios of each user to make the resource allocation efficient from the system view. We model the channel selection problem with demand-throughput ratio as a cooperative game, propose an ordered best response algorithm to achieve NE point and prove the existence of NE point. The stochastic learning algorithms has been used in simulations. The results show that the ordered best response algorithm and stochastic learning approach both converged and achieved good performance in fairness and utility which are better than random access situation. what’s more, the ordered best response algorithm has a significant improvement in convergence time.

Keywords

Opportunistic spectrum access Stochastic learning Ordered best response Demand throughput ratio Game theory 

Notes

Acknowledgment

This work was supported in part by the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province under Grant BK20160034, in part by the National Science Foundation of China under Grant 61631020, Grant 61401508, and Grant 61671473, and in part by the Open Research Foundation of Science and Technology on Communication Networks Laboratory.

References

  1. 1.
    Xu, Y., Anpalagan, A., Wu, Q., et al.: Decision-theoretic distributed channel selection for opportunistic spectrum access: strategies, challenges and solutions. IEEE Commun. Surv. Tutorials 15(4), 1689–1713 (2013). Fourth QuarterGoogle Scholar
  2. 2.
    Zhao, Q., Sadler, B.M.: A survey of dynamic spectrum access. IEEE Signal Process. Mag. 24(3), 79–89 (2007)Google Scholar
  3. 3.
    Mitola, J., Maguire, G.Q.: Cognitive radio: making software radios more personal. IEEE Pers. Commun. 6(4), 13–18 (1999)Google Scholar
  4. 4.
    Haykin, S.: Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun. 23(2), 201–220 (2005)Google Scholar
  5. 5.
    Xu, Y., Wang, J., Wu, Q., et al.: Opportunistic spectrum access in unknown dynamic environment: a game-theoretic stichastic learning solution. IEEE Trans. Wireless Commun. 11(4), 1380–1391 (2012)Google Scholar
  6. 6.
    Zhang, Y., Xu, Y., Wu, Q., Anpalagan, A.: Optimal opportunistic spectrum access with unknown and heterogeneous channel dynamics in cognitive radio networks. KSII Trans. Internet Inf. Syst. 8(6), 2675–2690 (2014)Google Scholar
  7. 7.
    Zhang, Y., Zhao, Q.: Distributed channel selection with dynamic users: a game-theoretic learning approach. In: Proceedings WCSP 2015. IEEE, October 2015Google Scholar
  8. 8.
    Xu, Y., Wu, Q., Wang, J., et al.: Opportunistic spectrum access using partially overlapping channels: graphic game and uncoupled learning. IEEE Trans. Commun. 61(9), 3906–3918 (2013)Google Scholar
  9. 9.
    Li, H., Han, Z.: Competitive spectrum access in cognitive radio networks: graphical game and learning. In: Proceedings 2010 IEEE WCNC, pp. 1–6 (2010)Google Scholar
  10. 10.
    Liu, M., Ahmad, S., Wu, Y.: Congestion games with resource reuse and applications in spectrum sharing. In: GameNets, pp. 171–179 (2009)Google Scholar
  11. 11.
    Xu, Y., Wang, J., Wu, Q., et al.: Opportunistic spectrum access in cognitive radio networks: global optimization using local interaction game. IEEE J. Sel. Top. Sign. Process. 6(2), 180–194 (2012)Google Scholar
  12. 12.
    Xie, X., Zhou, T., Dong, X., He, L.: Traffic-demand dynamic spectrum access. In: Proceedings IEEE WiCOM, pp. 1–4 (2008)Google Scholar
  13. 13.
    Chu, T., Phan, H., Zepernick, H.: Dynamic spectrum access for cognitive radio networks with prioritized traffics. IEEE Commun. Lett. 18(7), 1218–1221 (2014)Google Scholar
  14. 14.
    Wu, Q., Wu, D., Xu, Y., Wang, J.: Demand-aware multichannel opportunistic spectrum access: a local interaction game approach with reduced information exchange. IEEE Trans. Veh. Technol. 64(10), 4899–4904 (2015)Google Scholar
  15. 15.
    IEEE 802.16e-2005 and IEEE Std 802.16-2004/Corl-2005. http://www.ieee802.org/16/
  16. 16.
    Jain, R., Chiu, D., Haws, W.: A quantitative measure of fairness and discrimination for resource allocation in shared computer system, Technical report (1984)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.College of Communication EngineeringPLA University of Science and TechnologyNanjingChina
  2. 2.Science and Technology on Communication Networks LaboratoryShijiazhuangChina

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