Selection of physics-specific model for determination of characteristics of radio frequency signal propagation

A system for determining environmental-specific propagation characteristics of a radio frequency (RF) signal, the system comprising:

• a memory storing instructions;
• and
• at least one processor coupled to the memory, the at least one processor configured to access the instructions from the memory to perform operations comprising:
• receiving a plurality of first propagation characteristics of the RF signal;
• determining a feature vector based on the plurality of first propagation characteristics;
• inputting the feature vector to a machine-learning meta-model;
• executing the machine-learning meta-model to select a particular physics-specific model from a plurality of physics-specific models, wherein each of the physics-specific models is for a different RF signal propagation environment;
• inputting the feature vector to the particular physics-specific model;
• and
• executing the particular physics-specific model to output an estimate of one or more second propagation characteristics of the RF signal based on the feature vector.

A non-transitory computer readable medium having stored thereon software instructions that, when executed by a processor, cause the processor to perform operations comprising:

• receiving a plurality of first propagation characteristics of a radio frequency (RF) signal;
• determining a feature vector based on the plurality of first propagation characteristics;
• inputting the feature vector to a machine-learning meta-model;
• executing the machine-learning meta-model to select a particular physics-specific model from a plurality of physics-specific models, wherein each of the physics-specific models is for a different RF signal propagation environment;
• inputting the feature vector to the particular physics-specific model;
• and
• executing the particular physics-specific model to output an estimate of one or more second propagation characteristics of the RF signal based on the feature vector.