Building Optimal Statistical Models with the Parabolic Equation Method

Abstract

In this paper, we present a new application of electromagnetic propagation model- ing methods like Parabolic Equation (PE) algorithms: these tools can be used to obtain optimal statistical propagation models i.e., best-fltted statistical model for a given propagation envi- ronment. Statistical propagation models are widely used because of their convenience to make predictions that are valid for difierent types of propagation environments and operation condi- tions. However their accuracy is often questionable because they are obtained either empirically with a limited amount of experimental data collected in few propagation environments or de- duced using rough and general theory. As a result the model doesn't square satisfactorily with real operation. Our goal is to improve the preceding process by designing a method that would give an optimized statistical model (OSM) for a given environment. The process that leads to the OSM for a particular application involves several steps that are described in detail in the paper. Sample results are also given and comparisons between OSM and standard statistical models are discussed.