DOI QR코드

DOI QR Code

다중경로 통신 시스템에서 톰슨 샘플링을 이용한 경로 선택 기법

Thompson sampling based path selection algorithm in multipath communication system

  • Chung, Byung Chang (Department of Information and Communication Engineering, Gyeongsang National University)
  • 투고 : 2021.10.07
  • 심사 : 2021.11.17
  • 발행 : 2021.12.31

초록

In this paper, we propose a multiplay Thompson sampling algorithm in multipath communication system. Multipath communication system has advantages on communication capacity, robustness, survivability, and so on. It is important to select appropriate network path according to the status of individual path. However, it is hard to obtain the information of path quality simultaneously. To solve this issue, we propose Thompson sampling which is popular in machine learning area. We find some issues when the algorithm is applied directly in the proposal system and suggested some modifications. Through simulation, we verified the proposed algorithm can utilize the entire network paths. In summary, our proposed algorithm can be applied as a path allocation in multipath-based communications system.

키워드

참고문헌

  1. M. Ali, S. Qaisar, M. Naeem, W. Ejaz, and N. Kvedaraite, "LTE-U WiFi HetNets: Enabling Spectrum Sharing for 5G/Beyond 5G Systems," IEEE Internet of Things Magazine, vol. 3, no. 4, pp. 60-65, Dec. 2020. https://doi.org/10.1109/IOTM.0001.2000024
  2. Y. Xing, J. Han, K. Xue, J. Liu, M. Pan, and P. Hong, "MPTCP Meets Big Data: Customizing Transmission Strategy for Various Data Flows," IEEE Network, vol. 34, no. 4, pp. 35-41, Jul./Aug. 2020. https://doi.org/10.1109/mnet.011.1900438
  3. B. C. Chung and H. Park, "Path selection algorithm for multi-path system based on deep Q learning," Journal of the Korea Institute of Information and Communication Engineering, vol. 25, no. 1, pp. 50-55, Jan. 2021. https://doi.org/10.6109/JKIICE.2021.25.1.50
  4. M. S. Kim, J. Y. Lee, and B. C. Kim, "Design of MPTCP congestion control based on BW measurement for wireless networks," Journal of the Korea Institute of Information and Communication Engineering, vol. 21, no. 6, pp. 1127-1136, Jun. 2017. https://doi.org/10.6109/JKIICE.2017.21.6.1127
  5. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction, Cambridge, MA: The MIT Press, Mar. 1998.
  6. O. Chapelle and L. Li, "An empirical evaluation of Thompson sampling," in. Proc. of Advances in Neural Information Processing Systems, pp. 2249-2257, 2011.
  7. J. Komiyama, J. Honda, and H. Nakagawa, "Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays," in. Proc. of the 32nd International Conference on Machine Learning, pp. 1152-1161, 2015.