Page 227 - Integrated Wireless Propagation Models

M i c r o c e l l P r e d i c t i o n M o d e l s 205

By integrating building, terrain, and attribute data, such as water, the Lee microcell
prediction model can work with these inputs and come up with a much more adaptable
and accurate propagation model.
These data are readily accessible through the Internet. However, to integrate these
data into the model, calculation is not a trivial task.
Cities in different countries most likely will have different building loss curves, as
they are built with different materials. The Lee model also developed an algorithm to
derive the building loss curve Lb. Measurement integration is one of the key features of
the Lee model to ensure the model's accuracy and adaptability. All impacted parame­
ters need to go through the measurement integration process so that data are normal­
ized in each category. Then the model can be applied with the new derived parameters
to secure better accuracy.
Let us give more details on how the model works. The effect of buildings on propa­
gation will be addressed first, followed by an analysis of the effect of terrain on micro­
cell prediction.

4.2.3 The Effect of Buildings on i crocell Prediction
M
A received signal can be in LOS either without any building blockage or with signifi­
1
cant obstruction. These two factors are discussed in more detail in Lee. The flat-earth
assumption is utilized in this section as well.
Let us begin by considering a basic microcell scenario in which there is no building
obstruction and the existing terrain loss occurring on the radio path is L ws·

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4.2. . 1 The Basic LOS Situation
Considering a very basic case of a microcell where there are no buildings obstructing
the LOS and assuming a flat-terrain scenario to start with, the only loss that occurs on
the radio path is L ws· Figure 4.2.3. . 1 provides a map of San Francisco for searching the
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LOS situation.

FIGURE 4.2.3.1.1 San Francisco terr i n .
a