A 3D Geometry-Based Stochastic Model for mmWave Massive MIMO Subway Train Channels in Tunnel Scenarios

With the rapid evolution of wireless communication technology, the demand for reliable communication within subway tunnels continues to grow. Future subway communication systems will necessitate higher data transmission rates, reduced latency, and enhanced reliability. Therefore, this paper presents a three-dimensional (3D) geometry-based stochastic channel model designed for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) channels in tunnel environments. This work aims to address the limitations of previous studies by providing a more accurate and comprehensive model tailored to the unique propagation characteristics of tunnel scenarios. The material property parameters of tunnels in the ray-tracing (RT) model are calibrated using tunnel channel measurement data, thereby ensuring a strong alignment between the simulation results and the measurement outcomes. The calibrated RT model is subsequently utilized to generate extensive channel data, enabling the tracking and clustering of multipath components (MPCs). Cluster parameters are then derived for various cluster types. Finally, the proposed model’s validity is confirmed by comparing its channel characteristics with actual channel measurements in a new scenario. Simulation results show that the proposed model accurately represents the subway train channel characteristics in tunnel scenarios, offering essential theoretical support and experimental data for the design and optimization of subway wireless communication systems.