DOI QR코드

DOI QR Code

기계학습기반 초신뢰·저지연 무선통신기술 연구동향

Research Trends of Ultra-reliable and Low-latency Machine Learning-based Wireless Communication Technology

  • 발행 : 2019.06.01

초록

This study emphasizes the importance of the newly added Ultra-Reliable and Low-Latency Communications (URLLC) service as an important evolutionary step for 5G mobile communication, and proposes a remedial application. We analyze the requirements for the application of 5G mobile communication technology in high-precision vertical industries and applications, introduce the 5G URLLC design principles and standards of 3GPP, and summarize the current state of applied artificial intelligence technology in wireless communication. Additionally, we summarize the current state of research on ultra-reliable and low-latency machine learning-based wireless communication technology for application in ultra-high-precision vertical industries and applications. Furthermore, we discuss the technological direction of artificial intelligence technology for URLLC wireless communication.

키워드

HJTOCM_2019_v34n3_93_f0001.png 이미지

그림 1 3GPP NR URLLC 관련 표준화 일정

HJTOCM_2019_v34n3_93_f0002.png 이미지

그림 2 기계학습과 URLLC 간 개념도

참고문헌

  1. 5G America Whitepaper, New Services and Applications with 5G Ultra-Reliable Low Latency Communications , Nov. 2018.
  2. 3GPP TR 38.913, Study on Scenarios and Requirements for Next Generation Access Technologies , 2018.
  3. M. Chen, U. Challita, W. Saad, C. Yin, M. Debbah "Machine Learning for Wireless Networks with ARTIFICIAL Intelligence: A Tutorial on Neural Networks," ArXiv preprint, Oct. 2017, arXiv: 1710.02913.
  4. M. Iwabuchi, A. Benjebbour, Y. Kishiyama, Y. Okumura, "Field Experiments on 5G Ultra-Reliable Low Latency Communication(URLLC)," NTT DoCoMo Technical Journal, vol. 20, no. 1, July 2019, pp. 14-23.
  5. IEEE Standards, "P1918.1 - Tactile Internet: Applications Scenarios, Definitions and Terminology, Architecture, Functions, and Technical Assumptions." https://standards.ieee.org/develop/project/1918.1.html
  6. M. Dohler et al., "Internet of Skills, Where Robotics Meets AI, 5G and the Tactile Internet," in Eur. Conf. UNetw. Commun., Oulu, Finland, June 12-15, 2017, pp. 1-5.
  7. T. HoBler, L. Scheuvens, N. Franchi, M. Simsek, G. P. Fettweis, "Applying Reliability Theory for Future Wireless Communication Networks," in IEEE Annu. Int. Sypm. Personal, Indoor, Mobild Radio Commun., Montreal, Canada, Oct. 8-13, 2017, pp. 1-7.
  8. ITU-T E.800, Definitions of Terms Related to Quality of Service , Sept. 2008.
  9. H.B. McMahan, E. Moore, D. Ramage, S. Hampson, B.A. Arcas, "Communication Efficient LEARNING of Deep Networks from Decentralized Data," in Proc. Int. Artifical Intell. Statistics(AISTATS), Fort Lauderdale, FL, USA, Apr. 2017, pp. 1-10.
  10. J. Konecny, H.B. McMahan, F.X. Yu, P. Richtarik, A.T. Suresh, D. Bacon, "Federated Learning: strategies for improving communication efficiency," in Proc. Neural Inform. Process. Syst., Barcelona, Spain, Dec. 2016.
  11. J. Park, S. Samarakoon, M. Bennis, M. Debbah,"Wireless Network Intelligence at the Edge," ArXiv preprint, Dec. 2018, arXiv: 1812.02858.