Multi-dimensional material-aware geometric wireless channel rendering using machine learning models

Abstract

Certain aspects of the present disclosure provide techniques and apparatus for generating channel estimates in a spatial environment based on learned material properties for objects in the spatial environment. An example method generally includes receiving, from a ray-tracing model, a plurality of multipath components corresponding to a signal transmitted from a transmitter at a first location in a spatial environment to a receiver at a second location in the environment. For each respective multipath component, energy field characteristics of the respective multipath component are estimated, using a machine learning model, based on interactions with one or more objects in the environment, one or more learned parameters of the machine learning model being associated with one or more properties of the objects. A channel estimate is generated based on the estimated characteristics of each multipath component. One or more actions may be taken based on the generated channel estimate.