Page 121 - Integrated Wireless Propagation Models

C H A P T E R 3

Macrocell Prediction

Models Part 2:

Point-to-Point Models

3.1 The Lee ModeP-5
The calculation of macrocell coverage is based on signal propagation prediction tech­
niques. The Lee "point-to-point" model predicts each local mean of the received signal
strength at the mobile terminal based on the radio path between the base station and
the mobile but plots all the predicted local means along a mobile path in a mobile cel­
lular environment. The point-to-point model is a cost-saving tool used for planning a
system in a large coverage area. Otherwise, selecting the proper sites of a base station
based on the measured data in a large area is very costly and labor intensive.
The predicted signal strengths also can be calculated on a sector-by-sector basis.
It is used as an area-to-area model or point-to-area model. A recommendation is to use
a sector of 60° or 120°. In each sector, we may predict the local means along every 0.25°
or 0.5° radial increment within a sector and also use a small distance (radial length)
increment along each radial line. The prediction of local means for each sector is stored
in a data file. These files can be used to support most analyses, such as to generate
a neighboring cell list, frequency planning, traffic demand distribution, hardware
dimensioning, and so on.
The Lee model uses a reference frequency of 850 MHz; however, the model has been
validated with the measured data within the frequency range from 150 to 2400 MHz.
Measurements taken from over 500 drive tests conducted in Europe, Asia, and the
United States have been used to test the Lee model's implementation. These data cover
many different cities and many different characteristics of morphologies, such as dense
urban, urban, suburban, and rural.
The Lee model is also integrated with measurement data and can be customized in
any particular area or to support the use of path loss values that are derived from drive
test data as the basis for any analysis supported. This can be handled alone or in con­
junction with predicted data. Empirical data can also be used to "tune" path loss slopes
and intercepts, using a technique known as measurement integration, to improve pre­
diction accuracy for the Lee model.

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