Impact of Point Cloud Reconstruction Detail on mmWave Ray-Tracing in Indoor Environments

Ray tracing (RT) is a key tool for establishing accurate mappings between physical environments and propagation channels. However, due to the complexity of indoor scatterers and the difficulty of fully capturing modeling details, there is no unified specification for scenario modeling, leaving the impact of modeling detail on RT simulations unclear. This work proposes an indoor modeling method based on LiDAR point clouds, which achieves automated mesh reconstruction via minimum bounding box estimation and generates scenario models at different levels of detail (LOD). Comparative analysis shows that modeling detail significantly affects multipath components (MPCs) accuracy. A simple-detail model fails to accurately capture MPCs, whereas a medium-detail model exhibits higher simulation accuracy, and the full-detail model achieves the closest agreement with the ground truth model, although further accuracy gains diminish as complexity increases. Furthermore, indoor scatterers detail has a greater influence on RT results than room boundaries. To balance simulation accuracy and computational complexity, indoor scatterers should include at least external contour features, with opening structures preferred. In contrast, RB modeling can be simplified to a medium-detail model with only external contours. The sensitivity of different channel parameters to LOD also depends on the propagation scenario: in LOS scenarios, DS and PL are highly sensitive to LOD, whereas AS is relatively insensitive; in NLOS scenarios, DS and AS are sensitive, while PL sensitivity significantly decreases.