6G Simulator Using Real Environment Model Based on Point Cloud Data

• Published in: 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring) pp. 1 - 5
• Main Authors: Kitao, Koshiro, Suyama, Satoshi, Tomie, Takahiro, Kuno, Nobuaki, Tateishi, Kiichi, Jiang, Huiling
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24.06.2024
• Subjects: 6G mobile communication; Accuracy; Performance evaluation; Point cloud compression; point cloud data; radio propagation; raytrace; Simulation; System performance; throughput evaluation; Vehicular and wireless technologies
• ISSN: 2577-2465
• DOI: 10.1109/VTC2024-Spring62846.2024.10683213

The 6th generation mobile communication system (6G) is expected to realize ultrafast and high-capacity communications with a peak data rate of more than 100 Gbps and to contribute to the advancement of the Cyber-Physical System (CPS). In order to realize 100 Gbps ultrafast communications in 6G, the utilization of sub-terahertz bands up to 300 GHz band, which can utilize a dramatically wider signal bandwidth compared to 5G, is examined. We have developed a 6G simulator to clarify the feasibility of 100 Gbps ultrafast communications by utilizing the sub-terahertz band for the system. Existing 6G simulators can evaluate throughput when using the 100 GHz band in prepared scenarios such as shopping malls and factory, but not in specific real environments. To calculate throughput with high accuracy, it is necessary to estimate propagation characteristics with high accuracy in the real environment, and recently, raytrace simulation using a polygon model of a structure generated from point cloud data acquired in the evaluation environment has attracted attention as a highly accurate estimation method of propagation characteristics. Therefore, in order to evaluate the system performance in the real environment, we developed an advanced 6G simulator that can simulate and visualize the throughput based on the propagation characteristics obtained from raytrace simulation with a real environment model using point cloud data. In this paper, we describe an overview of the functions of this simulator and an example of performance evaluation.