Model Calibration Introduction

A brief primer on RF planning may better frame a discussion on model calibration, or what many engineers refer to as “model tuning”. Propagation models are used by engineers within RF planning tools such as Forsk’s Atoll, Aircom’s Asset and Mentum’s Planet. These software applications – and there are numerous others -- include an underlying GIS system for mapping, a prediction engine to generate the RF simulation and various other components.

Each planning tool supports a range of RF models, that can be either empirical (i.e., based on observed measurements), deterministic (i.e., the model behaves in a certain way when it encounters specific obstacles and environmental change) or a blending of the two.

Regardless of the type of model used, no RF prediction model will be accurate without calibrating it against observed and measured values such as carrier wave (CW) data accumulated through drive tests. This is the focus of the model calibration exercise. To be effective, RF planning tools or “simulation tools” need geodata that precisely replicates the terrain and clutter being considered as well as calibrated or “tuned” models that benefit from accurate measurement data. These models will help deliver a network plan, or contribute to optimization exercises in a simulation that will translate into the real world once implemented.