Accelerating Ray Tracing for Urban V2X Environments through a Fusion Algorithm

This paper introduces an innovative fusion algorithm designed to accelerate ray tracing for wireless channel modeling in urban Vehicle-to-Everything (V2X) environments. The proposed method combines particle swarm optimization, the visibility table, and the partitioning algorithm to achieve a balance between accuracy and speed. Prior to simulation, the visibility table is generated to establish the visibility relationship between obstacle lines and surfaces. Subsequently, the partitioning algorithm is adopted to reduce line-surface intersections. During the simulation, the search area is divided based on emission angles, and then low-resolution ray tracing is employed to identify advantageous regions. An iterative search using the particle swarm optimization algorithm is then conducted for each of the identified advantageous regions to determine the optimal path. The simulation results exhibit remarkable consistency with high-resolution ray tracing, providing strong validation for the effectiveness of the proposed method. Moreover, these results affirm that the proposed method effectively improves calculation efficiency while ensuring the accuracy of ray tracing. Consequently, it exhibits promising potential for practical applications in wireless channel modeling for urban V2X environments.