Most radio propagation models are derived using a combination of analytical and empirical methods.

The empirical approach is based on fitting curves or analytical expressions that recreate a set of measured data.

This has the advantage of implicitly taking into account all propagation factors, both known and unknown, through actual field measurements.

However, the validity of an empirical model at transmission frequencies or environments other than those used to derive the model can only be established by additional measured data in the new environment at the required transmission frequency.

Over time, some classical propagation models have emerged, which are now used to predict large-scale coverage for mobile communication systems design.

By using path loss models to estimate the received signal level as a function of distance, it becomes possible to predict the SNR for a mobile communication system.

Using noise analysis techniques , the noise floor can be determined. For example, the two-ray model is used to estimate capacity in a spread spectrum cellular system, before such systems were deployed.