Context-Aware Channel Sounder for AI-Assisted Radio-Frequency Channel Modeling

We describe a context-aware channel sounder that consists of three separate systems: a radio-frequency system to extract multipaths scattered from the surrounding environment in the 3D geometrical domain, a Lidar system to generate a point cloud of the environment in the same domain as the multipaths - providing a geometrical means to associate the multipaths to the environment scatterers - and a camera system to identify and classify the scatterers. With the assistance of artificial intelligence (AI), the data acquired by the three systems can be automatically reduced into a scatter-specific channel model. Two such applications are presented.