Identification of Interacting Objects and Evaluation of Interaction Loss from Wideband Double-Directional Channel Measurement Data by Using Point Cloud Data

This paper proposes an approach to identify interacting objects (IOs) and determine their interaction losses (ILs) using point cloud data from wide-band double-directional channel sounding data. The scattering points (SPs) were identified using the maximum likelihood-based approach applied to the high-resolution path parameters estimated from the channel sounding data, and then IOs were identified via visual inspection of SPs within a 3D point cloud. The proposed approach utilizes all path parameters to calculate the approximate likelihood function for all candidate SPs to determine the SP, regardless of the propagation mechanism. The proposed technique was demonstrated at a suburban residential site with a frequency of 11 GHz. The results show that IOs that are not usually considered in the ray-tracing simulation were identified.