Hybrid statistical and machine learning method and system for radio frequency (rf) spectrum propagation modeling and prediction

Abstract

Aspects of the subject disclosure may include, for example, obtaining data regarding an environment associated with a cell site, identifying one or more coverage pivots from a plurality of coverage locations in the environment, utilizing one or more machine learning (ML) models to determine emission directions for the one or more coverage pivots based at least in part on locations of the one or more coverage pivots and the cell site in the environment, resulting in determined emission directions, and causing ray tracing simulation to be performed using the determined emission directions, wherein the ray tracing simulation enables first signal coverage estimates to be derived for the one or more coverage pivots and used to extrapolate second signal coverage estimates for a remainder of the plurality of coverage locations. Other embodiments are disclosed.