ZTE Communications ›› 2025, Vol. 23 ›› Issue (2): 31-45.DOI: 10.12142/ZTECOM.202502005

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6G Digital Twin Enabled Channel Modeling for Beijing Central Business District

LU Mengyuan1,2, BAI Lu1,3,4(), HAN Zengrui5, HUANG Ziwei5, LU Shiliang1,2, CHENG Xiang5   

  1. 1.Joint SDU-NTU Centre for Artificial Intelligence Research (C?FAIR), Shandong University, Jinan 250101, China
    2.School of Software, Shandong University, Jinan 250101, China
    3.National Mobile Communications Research Laboratory, Southeast University, Nanjing 214135, China
    4.Shandong Research Institute of Industrial Technology, Jinan 250100, China
    5.School of Electronics, Peking University, Beijing 100871, China
  • Received:2025-01-20 Online:2025-06-25 Published:2025-06-10
  • About author:LU Mengyuan received her BS degree in engineering from the School of Software, Shandong University, China in 2024. She is currently pursuing her master's degree at the same institution. Her research interests focus on AI-based 6G vehicular communications.
    BAI Lu (lubai@sdu.edu.cn) received her PhD degree in information and communication engineering from Shandong University, China in 2019. From 2017 to 2019, she was a visiting PhD student with Heriot-Watt University, UK. From 2019 to 2022, she was a post-doctoral researcher with Beihang University, China. She is currently a professor with Shandong University. Her general research interests are in areas of wireless communications and artificial intelligence, subject on which she has published more than 50 journal and conference papers and 2 books, held 5 patents, and participated in formulating 5 Chinese standards. She has received IEEE VR Best Paper Award, Science and Technology Progress Award of China Transport and Logistics Association, and TaiShan Scholar Award. She was a recipient of the Young Elite Scientist Sponsorship Program by China Association for Science and Technology. She has served as a member of the Technical Program Committee and session chair for several international conferences. She is currently an associate editor of IET Communications and a member of the IEEE P1944 Standard Group.
    HAN Zengrui received his BS degree in information and communication engineering from the School of Information and Communication Engineering, University of Electronic Science and Technology of China in 2024. He is currently pursuing a PhD degree at the School of Electronics, Peking University, China. His current research interest is Al-based channel modeling.
    HUANG Ziwei received his BS degree in communication engineering from Chongqing University, China in 2019 and PhD degree from the School of Electronics, Peking University, China. His current research interests include wireless communication channel measurements and modeling, including vehicular channel measurements and modeling, UAV channel modeling, and AI-based channel modeling. He was a co-recipient of IET Communications Best Paper Award: Premium Award.
    LU Shiliang is pursuing his master's degree at the School of Software, Shandong University, China. His research interest focuses on MIMO channel modeling.
    CHENG Xiang received his joint PhD degree from Heriot-Watt University and The University of Edinburgh, UK in 2009. He is currently a Boya Distinguished Professor with Peking University, China. His research interests include channel modeling, wireless communications, and data analytics, the subjects on which he has published more than 280 journal articles and conference papers, nine books, and held 26 patents. He was a recipient of the IEEE Asia-Pacific Outstanding Young Researcher Award in 2015 and the Xplorer Prize in 2023. He is a subject editor of the IET Communications and an associate editor of the IEEE Transactions on Wireless Communications, IEEE Transactions on Intelligent Transportation Systems, and IEEE Wireless Communications Letter. He has been a highly cited Chinese researcher since 2020. In 2021 and 2023, he was selected into two world scientist lists: the World’s Top 2% Scientists released by Stanford University and the top computer science scientists released by Guide2Research.
  • Supported by:
    the National Natural Science Foundation of China(62371273);the Taishan Scholars Program(tsqn202312307);the Young Elite Scientists Sponsorship Program by CAST(YESS20230372);the Shandong Natural Science Foundation(ZR2023YQ058);the New Cornerstone Science Foundation through the Xplorer Prize;the Xiaomi Young Talents Program;the open research fund of National Mobile Communications Research Laboratory, Southeast University(2025D04);the China National Postdoctoral Program for Innovative Talents(BX20240007);the China Postdoctoral Science Foundation(2024M760111);the Beijing Natural Science Foundation(4254067)

Abstract:

A novel digital twin (DT) enabled channel model for 6G vehicular communications in Beijing Central Business District (Beijing CBD) is proposed, which can support the design of intelligent transportation systems (ITSs). A DT space for Beijing CBD is constructed, and two typical transportation periods, i.e., peak and off-peak hours, are considered to characterize the vehicular communication channel better. Based on the constructed DT space, a DT-enabled vehicular communication dataset is developed, including light detection and ranging (LiDAR) point clouds, RGB images, and channel information. With the assistance of LiDAR point clouds and RGB images, the scatterer parameters, including number, distance, angle, power, and velocity, are analyzed under different transportation periods. The channel non-stationarity and consistency are mimicked in the proposed model. The key channel statistical properties are derived and simulated. Compared to ray-tracing (RT) results, the accuracy of the proposed model is verified.

Key words: DT, channel modeling, 6G vehicular communications, Beijing CBD, DT-enabled vehicular communication dataset