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Handbook of Propagation Effects for Vehicular and ... - Courses

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Summary <strong>of</strong> Recommendations 12-21<br />

probability distributions models are the composite <strong>of</strong> Rayleigh, Ricean, <strong>and</strong> lognormal<br />

probability density functions with more or less physical reasoning. Geometrical<br />

analytical models attempt to predict the combined effects <strong>of</strong> scatterers by applying<br />

electromagnetic theory.<br />

12.11.1 Choosing a Model<br />

The choice as to which model is most appropriate depends very much on the intended<br />

application <strong>and</strong> what propagation phenomenon one wants to predict. Of the different<br />

types, empirical models do not provide insight into the physics <strong>of</strong> propagation processes,<br />

but they characterize the sensitivity <strong>of</strong> the results to important parameters. Statistical<br />

models build upon an underst<strong>and</strong>ing <strong>of</strong> the processes that cause signal variations, but<br />

with simplifying assumptions. Analytical models attempt to describe a particular<br />

propagation scenario deterministically, but then have to use statistics to extend the results<br />

to realistic situations.<br />

12.11.1.1 Empirical Regression Models<br />

The EERS model has already been summarized in this chapter under Section 12.3.1. As<br />

it is based on a large amount <strong>of</strong> data, it gives reasonably realistic estimates <strong>of</strong> fading<br />

distributions by roadside trees.<br />

12.11.1.2 Statistical Models<br />

<strong>Propagation</strong> effects on mobile satellite links are caused when transmissions are reflected<br />

diffusely or specularly, when they penetrate through trees or diffract around buildings.<br />

All these different propagation states can be associated with specific statistical<br />

distributions. Models need to allow <strong>for</strong> a number <strong>of</strong> states appropriate to the environment<br />

under consideration. The Loo <strong>and</strong> Lutz models work well in environments with two<br />

states, the three-state model (Chapter 10), however, covers more outdoor scenarios. The<br />

more states are incorporated into a model, the more specific site <strong>and</strong> parameter data are<br />

required.<br />

12.11.1.3 Analytical Models<br />

Analytical models are mainly useful <strong>for</strong> describing canonical propagation phenomena, as<br />

such they can be very useful in studying the effect <strong>of</strong> varying particular parameters, such<br />

as the b<strong>and</strong>width, or antenna pattern.<br />

12.11.2 Suggestions <strong>for</strong> Future Work<br />

A deficiency <strong>of</strong> the models presented in Chapter 11 is that they were derived <strong>for</strong><br />

vehicular mobile applications, whereas today’s emphasis <strong>of</strong> satellite services has shifted<br />

towards h<strong>and</strong>-held personal user terminals. The environment selections have there<strong>for</strong>e<br />

also broadened from highways to essentially anywhere, including but not limited to<br />

outdoors, inside buildings, inside cars, aboard trains <strong>and</strong> airplanes, etc. Although data<br />

characterizing some <strong>of</strong> these scenarios have been presented in earlier chapters, e.g., fade<br />

measurements into buildings, there has been no concurrent systematic model

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