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Wireless Communications and Mobile Computing
Volume 2017, Article ID 6474768, 7 pages
https://doi.org/10.1155/2017/6474768
Research Article

A Reinforcement Learning Approach to Access Management in Wireless Cellular Networks

1Department of Computer Science, University of Suwon, San 2-2, Wau-ri, Bongdam-eup, Hwaseong, Gyeonggi-do 445-743, Republic of Korea
2Department of Information Technology Engineering, Sookmyung Women’s University, 100 Cheongpa-ro 47-gil, Yongsan-gu, Seoul 04310, Republic of Korea

Correspondence should be addressed to Yujin Lim; rk.ca.gnuymkoos@19nijuy

Received 25 February 2017; Accepted 9 April 2017; Published 14 May 2017

Academic Editor: Syed Hassan Ahmed

Copyright © 2017 Jihun Moon and Yujin Lim. 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. 3rd Generation Partnership Project, “Technical specification group radio access network; study on RAN improvements for machine-type communications,” 3GPP TR 37.868 V11.0.0, 2011. View at Google Scholar
  2. 3rd Generation Partnership Project, “Evolved universal terrestrial radio access (E-UTRA); radio resource control (RRC); protocol specification,” 3GPP TS 36.331 V12.7.0, 2015. View at Google Scholar
  3. M. S. Ali, E. Hossain, and D. I. Kim, “LTE/LTE-A random access for massive machine-type communications in smart cities,” IEEE Communications Magazine, vol. 55, no. 1, pp. 76–83, 2017. View at Publisher · View at Google Scholar
  4. P. Jain, P. Hedman, and H. Zisimopoulos, “Machine type communications in 3GPP systems,” IEEE Communications Magazine, vol. 50, no. 11, pp. 28–35, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. M.-Y. Cheng, G.-Y. Lin, H.-Y. Wei, and A. C.-C. Hsu, “Overload control for machine-type-communications in LTE-advanced system,” IEEE Communications Magazine, vol. 50, no. 6, pp. 38–45, 2012. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Laya, L. Alonso, and J. Alonso-Zarate, “Is the random access channel of LTE and LTE-A suitable for M2M communications? A survey of alternatives,” IEEE Communications Surveys & Tutorials, vol. 16, no. 1, pp. 4–16, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Hasan, E. Hossain, and D. Niyato, “Random access for machine-to-machine communication in LTE-advanced networks: issues and approaches,” IEEE Communications Magazine, vol. 51, no. 6, pp. 86–93, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. Intel Corporation, “Further performance evaluation of EAB information update mechanisms,” 3GPP R2-120270, RANWG2 Meeting #77, 2012. View at Google Scholar
  9. S.-Y. Lien, T.-H. Liau, C.-Y. Kao, and K.-C. Chen, “Cooperative access class barring for machine-to-machine communications,” IEEE Transactions on Wireless Communications, vol. 11, no. 1, pp. 27–32, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. 3rd Generation Partnership Project, “RACH overload solutions,” 3GPP R2-103742, RANWG2 #70bis, 2010. View at Google Scholar
  11. A. Ksentini, Y. Hadjadj-Aoul, and T. Taleb, “Cellular-based machine-to-machine: overload control,” IEEE Network, vol. 26, no. 6, pp. 54–60, 2012. View at Publisher · View at Google Scholar · View at Scopus
  12. J.-P. Cheng, C.-H. Lee, and T.-M. Lin, “Prioritized Random Access with dynamic access barring for RAN overload in 3GPP LTE-A networks,” in Proceedings of the IEEE GLOBECOM Workshops (GC Wkshps '11), pp. 368–372, Houston, Tex, USA, December 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. R. S. Sutton, A. G. Barto, and R. J. Williams, “Reinforcement Learning is Direct Adaptive Optimal Control,” IEEE Control Systems, vol. 12, no. 2, pp. 19–22, 1992. View at Publisher · View at Google Scholar · View at Scopus
  14. A. G. Barto, S. J. Bradtke, and S. P. Singh, “Learning to act using real-time dynamic programming,” Artificial Intelligence, vol. 72, no. 1-2, pp. 81–138, 1995. View at Publisher · View at Google Scholar · View at Scopus
  15. J. Moon and Y. Lim, “Access control of MTC devices using reinforcement learning approach,” in Proceedings of the IEEE International Conference on Information Networking (ICOIN '17), pp. 641–643, 2017.
  16. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, MIT Press, 1998.