An Adaptive Shooting and Bouncing Rays Method for Ray-Tracing Channel Modeling Assisted by Environmental Prior Information for 6G

Due to the fact that the scale and construction of 6G communication systems are progressing toward unprecedentedly large and complex, accuracy and robustness of channel modeling method are vital to ensure that communication systems can work efficiently. Ray-Tracing (RT), as a precise deterministic modeling method, can meet most of these requirements. Shooting and Bouncing Rays (SBR) is a forward RT algorithm with high efficiency and wide usage. Traditional SBR utilizes environmental prior information, like distribution of scatters, only in path-finding. Channel parameters like quantity of rays are determined artificially, which affects SBR’s performance especially in 6G systems. In order to enable SBR to conduct 6G modeling stably and efficiently, we propose an advanced SBR algorithm that utilizes environmental prior information globally for both path-finding progress and parameter-determination. Space-division, face-classification are some environmental-information-assisted processes of the proposed algorithm, which help to calculate channel parameters quantitatively. Additionally, our new algorithm accelerates path-finding progress by decreasing unnecessary intersections through space-division. Simulation reveals our new algorithm reduces computational complexity by 34.53% in comparison of traditional SBR. Furthermore, with Image Method (IM) as a standard, new algorithm has smaller Normalized Mean Squared Error (NMSE) of 78.09% less in LOS-path ignoring power-receiving, compared to traditional SBR. Other metrics such as Power-Delay Profile (PDP) are also demonstrated in our work.