ETRI Journal

  • 제45권5호
  • /
  • Pages.781-794
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  • 2023
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  • 1225-6463(pISSN)
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  • 2233-7326(eISSN)
한국전자통신연구원 (Electronics and Telecommunications Research Institute)
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Implementation of mmWave long-range backhaul for UAV-BS

  • Jangwon Moon (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Junwoo Kim (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Hoon Lee (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Youngjin Moon (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Yongsu Lee (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Youngjo Bang (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Kyungyeol Sohn (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Jungsook Bae (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Kwangseon Kim (Radio Research Division, Electronics and Telecommunications Research Institute) ;
  • Seungjae Bahng (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Heesoo Lee (Mobile Communication Research Division, Electronics and Telecommunications Research Institute)
  • 투고 : 2023.03.23
  • 심사 : 2023.08.09
  • 발행 : 2023.10.20
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초록

Uncrewed aerial vehicles (UAVs) have become a vital element in nonterrestrial networks, especially with respect to 5G communication systems and beyond. The use of UAVs in support of 4G/5G base station (uncrewed aerial vehicle base station [UAV-BS]) has proven to be a practical solution for extending cellular network services to areas where conventional infrastructures are unavailable. In this study, we introduce a UAV-BS system that utilizes a high-capacity wireless backhaul operating in millimeter-wave frequency bands. This system can achieve a maximum throughput of 1.3 Gbps while delivering data at a rate of 300 Mbps, even at distances of 10 km. We also present the details of our testbed implementation alongside the performance results obtained from field tests.

키워드

과제정보

Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea Government (MSIT) (2020-0-00045, Development of Movable High-Capacity Mobile Communication Infrastructure for Telecommunication Disaster and Rescue).

참고문헌

  1. G. Geraci, D. Lopez-Perez, M. Benzaghta, and S. Chatzinotas, Integrating terrestrial and non-terrestrial networks: 3D opportunities and chanllenges, arXiv preprint, 2022. https://doi.org/10.48550/arXiv.2207.10385
  2. X. Lin, S. Rommer, S. Euler, A. Yavuz, and R. Karlsson, 5G from space: an overview of 3GPP non-terrestrial networks, IEEE Commun. Stand. Mag. 5 (2021), no. 4, 147-153. https://doi.org/10.1109/MCOMSTD.011.2100038
  3. 3GPP: Unmmaned aerial system (UAS) support in 3GPP, TS 22.125, 2022.
  4. S. Mohsan, M. Khan, F. Noor, I. Ullah, and M. Alsharif, Towards the unmanned aerial vehicles (UAVs): a comprehensive review, Drones 6 (2022), no. 6, 1-27.
  5. Y. Zeng, R. Zhang, and T. J. Lim, Wireless communications with unmanned aerial vehicles: opportunities and challenges, IEEE Commun. Mag. 54 (2016), no. 5, 36-42.
  6. A. Merwaday, A. Tuncer, A. Kumbhar, and I. Guvenc, Improved throughput coverage in natural disasters: unmanned aerial base stations for public-safety communications, IEEE Veh. Technol. Mag. 11 (2016), no. 4, 53-60.
  7. N. Zhao, W. Lu, M. Sheng, Y. Chen, J. Tang, F. Yu, and K. Wong, UAV-assisted emergency networks in disasters, IEEE Wireless Commun. 26 (2019), 45-51. https://doi.org/10.1109/MWC.2018.1800160
  8. G. Castellanos, M. Deruyck, L. Martens, and W. Joseph, Performance evaluation of direct-link backhaul for UAV-aided emergency networks, Sensors 19 (2019), no. 15, 45-51.
  9. B. Galkin, J. Kibilda, and L. A. DaSilva, Backhaul for low-altitude UAVs in urban environments, (IEEE International Conference on Communications (ICC), Kansas CIty, MO, USA), 2018, pp. 1-6.
  10. 3GPP: NR; integrated access and backhaul (IAB) radio transmission and reception. TS 38.174, 2020.
  11. A. Fouda, A. Ibrahim, I. Guvenc, and M. Ghosh, UAV-based in-band integrated access and backhaul for 5G communications, (IEEE 88th Vehicular Technology conference (VTC-FALL), Chicago, IL, USA), 2018, pp. 1-5.
  12. H. Zhang, Z. Qi, J. Li, A. Aronsson, J. Bosch, and H. Olsson, 5G network on wings: a deep reinforcement learning approach to the UAV-based integrated access and backhaul, arXiv preprint, 2023. https://doi.org/10.48550/arXiv.2202.02006
  13. N. Ansari, D. Wu, and X. Sun, FSO as backhaul and energizer for drone-assisted mobile access networks, ICT Express 6 (2020), 139-144. https://doi.org/10.1016/j.icte.2019.12.002
  14. S. Nath, S. P. Singh, and S. Sengar, Interference and noise analysis for hybrid FSO/RF-based 6G mobile backhaul, ETRI J. 44 (2022), no. 6, 966-976. https://doi.org/10.4218/etrij.2022-0213
  15. 3GPP: Unmanned aerial system (UAS) support in 3GPP, TS 22.125. 3GPP, 2018.
  16. MIST, Evaluation results of communication service coverage and quality, Republic of Korea, 2021.
  17. 3GPP: Base station (BS) radio transmission and reception, TS 38.104, 2018.
  18. 3GPP: Evolved universal terrestrial radio access (E-UTRA); physical channels and modulation, TS 36.211, 2021.
  19. Y. Jeon, H. Park, and E. Choi, Synchronization and cell search procedure in 3GPP 5G NR systems, (21st International Conference on Advanced Communication Technology (ICACT), PyeongChang, Republic of Korea), 2019, pp. 475-478.
  20. T. A. Pham and B. T. Le, A proposed preamble detection algorithm for 5G-PRACH, (International Conference on Advanced Technologies for Communications (ATC), Hanoi, Vietnam), 2019, pp. 210-214.
  21. A. Finnerty and M. Lee, Integrated SD-FEC in Zynq UltraScale + RFSoCs for higher throughput and power efficiency, Xilinx white paper (WP498), 2018.