KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

Opportunistic Spectrum Access with Dynamic Users: Directional Graphical Game and Stochastic Learning

  • Zhang, Yuli (College of Communication Engineering, PLA University of Science and Technology) ;
  • Xu, Yuhua (College of Communication Engineering, PLA University of Science and Technology) ;
  • Wu, Qihui (College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics)
  • Received : 2017.01.11
  • Accepted : 2017.07.07
  • Published : 2017.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

Keywords

References

  1. Y. Xu, A. Alagan and Q. Wu et al., "Decision-theoretic distributed channel selection for opportunistic spectrum access: Strategies, challenges and solutions," IEEE Commun. Survey & Tutorials, vol. 15, no. 4, pp. 1689- 1713, 2013. https://doi.org/10.1109/SURV.2013.030713.00189
  2. Q. Zhao and B. M.Sadler, "A survey of dynamic spectrum access," IEEE Signal Process. Magazine, vol. 24. no. 3, pp. 79-89, 2007. https://doi.org/10.1109/MSP.2007.361604
  3. H. Li and Z. Han, "Competitive spectrum access in cognitive radio networks: Graphical game and learning," in Proc. of 2010 IEEE WCNC, pp. 1-6, 2010.
  4. Y. Xu, Q. Wu, L. Shen, et al., "Opportunistic spectrum access with spatial reuse: Graphical game and uncoupled learning solution," IEEE Trans. Wireless Commun., vol.12, no. 10, pp. 4814-4826, 2013. https://doi.org/10.1109/TWC.2013.092013.120862
  5. Y. Xu, J. Wang, Q. Wu, et al,. "Opportunistic spectrum access in unknown dynamic environment: A game-theoretic stochastic learning solution," IEEE Trans. Wireless Commun., vol. 11, no.4, pp.1380-1391, 2012. https://doi.org/10.1109/TWC.2012.020812.110025
  6. M. Azarafrooz and R. Chandramouli, "Distributed learning in secondary spectrum sharing graphical game," in Proc. of 2011 IEEE GLOBECOM, pp. 1-6, 2011.
  7. M. Liu, S. Ahmad, and Y.Wu, "Congestion games with resource reuse and applications in spectrum sharing" GameNets, pp. 171-179, 2009.
  8. Y. Xu, J. Wang, Q. Wu, et al, "Opportunistic spectrum access in cognitive radio networks: Global optimization using local interaction game," IEEE J. Sel. Topics Signal Process., vol. 6, no. 2, pp. 180-194, 2012. https://doi.org/10.1109/JSTSP.2011.2176916
  9. Y. Xu, Q. Wu, J. Wang, et al., "Opportunistic spectrum access using partially overlapping channels: Graphic game and uncoupled learning," IEEE Trans. Commun., vol. 61, no. 9, pp. 3906-3918, 2013. https://doi.org/10.1109/TCOMM.2013.072913.120881
  10. J. Zheng, Y. Cai, Y. Xu, and A. Anpalagan, "Distributed channel selection for interference mitigation in dynamic environment: A game-theoretic stochastic learning solution," IEEE Trans. Vehicular Technology, vol. 63, no. 9, pp. 4757-4762, 2014. https://doi.org/10.1109/TVT.2014.2311496
  11. X. Chen, and J. Huang, "Distributed spectrum access with spatial reuse," IEEE J. Sel. Areas Commun., vol. 31, no. 3, pp. 593-603, 2013. https://doi.org/10.1109/JSAC.2013.130323
  12. IEEE 802.16e-2005 and IEEE Std 802.16-2004/Corl-2005.
  13. R. Jain, D. Chiu, and W. Haws, "A quantitative measure of fairness and discrimination for resource allocation in shared computer system," Technical Report, 1984.
  14. D. Monderer and L. S. Shapley, "Potential games," Game Economic Behacior, vol. 14, pp. 124-143, 1996. https://doi.org/10.1006/game.1996.0044
  15. P. Duarte, Z. Fadlillah, A. Vasilakos and N. Kato, "On the partially overlapped channel assignment on wireless mesh network backone: A game theoretic approach," IEEE J. Sel. Areas Commun., vol. 30, no. 1, pp. 119- 127, 2012. https://doi.org/10.1109/JSAC.2012.120111
  16. J. Marden, G. Arslan and J. Shamma, "Joint strategy fictitious play with inertia for potential games," IEEE Trans. Autom. Control, vol. 54, no. 2, pp. 208-220, 2009. https://doi.org/10.1109/TAC.2008.2010885
  17. Q. Wu, D. Wu, Y. Xu and J. Wang, "Demand-Aware Multichannel Opportunistic Spectrum Access: A Local Interaction Game Approach With Reduced Information Exchange," IEEE Transactions on Vehicular Technology, vol. 64, no. 10, pp. 4899-4904, Oct. 2015. https://doi.org/10.1109/TVT.2014.2369484
  18. L. Xiao, H. Dai and P. Ning, "Jamming-Resistant Collaborative Broadcast Using Uncoordinated Frequency Hopping," IEEE Trans. Information Forensics & Security, vol. 7, no. 1, pp. 297 - 309, Feb. 2012. https://doi.org/10.1109/TIFS.2011.2165948
  19. N. Hasan and et al., "Network Selection and Channel Allocation for Spectrum Sharing in 5G Heterogeneous Networks," IEEE Access, vol. 4, pp. 980-992, March 2016. https://doi.org/10.1109/ACCESS.2016.2533394
  20. Darsena D., Gelli, G. and Verde, F., "An Opportunistic Spectrum Access Scheme for Multicarrier Cognitive Sensor Networks," IEEE Sensors Journal, vol.17, no.8, pp.2596-2606, 2017. https://doi.org/10.1109/JSEN.2017.2674181
  21. Akhtar, F., Rehmani, M.H. and Reisslein, M., "White space: Definitional perspectives and their role in exploiting spectrum opportunities," Telecommunications Policy, vol.40, no.4, pp.319-331, 2016. https://doi.org/10.1016/j.telpol.2016.01.003
  22. Pratibha, P., Li, K.H. and Teh, K.C., "Optimal Spectrum Access and Energy Supply for Cognitive Radio Systems with Opportunistic RF Energy Harvesting," IEEE Transactions on Vehicular Technology, Vol.66, Issue 8, pp.7114-7122, 2017. https://doi.org/10.1109/TVT.2017.2673861
  23. Khan, A.A., Rehmani, M.H. and Reisslein, M., "Cognitive radio for smart grids: Survey of architectures, spectrum sensing mechanisms, and networking protocols," IEEE Communications Surveys & Tutorials, 18(1), pp.860-898, 2016. https://doi.org/10.1109/COMST.2015.2481722
  24. X. Zhang, N. Zhao, F. Richard Yu, Minglu Jin, and Victor C. M. Leung, "Resource Allocation in Topology Management of Asymmetric Interference Networks" IEEE Systems Journal, Issue 99, pp.1-11, 2017.
  25. N. Zhao, X. Zhang, F. Richard Yu, Victor Leung, "To Align or Not to Align: Topology Management in Asymmetric Interference Networks," IEEE Transactions on Vehicular Technology, Vol.66, Issue 8, pp. 7164-7177, 2017. https://doi.org/10.1109/TVT.2017.2650990