Page 145 - Integrated Wireless Propagation Models

M a c r o c e l l P r e d i c t i o n M o d e l s - P a r t 2 : P o i n t - t o - P o i n t M o d e l s 123

In the automorphology model, each attribute is correlated to a path loss slope value.
The slope values specified from different types of land covered and land used are used
in the automorphology model for those grids beyond the 1-mile intercept.
In the optional water enhancement, the slope value assigned to any type of water in
the morphology class is irrelevant. The fact that a bin contains water (or not) is the only
consideration for this option.

3.1.5. 1 Network Engineering Process
There are still some issues with most of the currently used network planning tools. One
of the problems is that no flexible model can handle the different types of morphology
that affect propagation, coverage, interference, handoff, and capacity. The morphology
model needs to be enhanced from many different perspectives. A simple 2D model
comprised of 2D morphology data is not good enough today. The third dimension
(height) is playing a more important role in the planning arena of network engineering.
Trees can make LOS mobile become non-LOS. Tall, dense forest can cause a difference
in decibels up to two digits from the predicted path loss, impacting the accuracy of the
morphology model. Another drawback is that some field data are sensitive to the time
of the year, which has not been integrated with the network engineering process.
This section addresses innovative ways to deal with the impact of morphology on
network engineering. There are many different morphologies, and each has a unique
impact on network engineering and planning. For example, different types of trees will
have different impacts on propagation. Also, they behave differently if they are weather
sensitive. In this section, a 4D (time of the year, and height, width, and length of the
morphology) database associated with algorithms is proposed to deal with the impact
1
on system engineering. 4 The key point of this enhancement is that it includes a means
of gaining feedback and of integrating measured data from the field so that the 4D mor­
phology model can be tuned (full flexibility) to handle different situations better.
The innovations include; first, the fundamental concept of dealing with morphol­
ogy in an integrated network with entire system propagation (the specific path loss
slope from the morphology will be derived and applied to the existing model); second,
the algorithm of deriving these morphology slopes; third, the calculation of shadow
loss; and fourth, the identification and integration of the impact on time variance and
associated engineering algorithm.
The minutes of use of wireless transmission for calculating the prediction model
need to be substantially increased for the enhancement of the morphology. Fortunately,
with today's technology, mobile operators in network engineering can afford the cost of
the minutes of use with more accurate processes and cheaper data available.

3.1.5.2 The Algorithm of Categorizing Different Morphologies
A generic propagation model is comprised of a slope and a 1-mile (or 1-km) intercept as
shown in Fig. 3.1.5.2. . It applies the slope and intercept to each radial in calculating the
1
signal strength along the radial.
The morphology area can be classified into three different categories, such as type
1-water, type 2-foliage, and type 3-tunnel, as shown in Fig. 3.1.5.2.2. The detailed
description of the signal propagation over the water will be shown in Sec. 3.1.6.
Figure 3.1.5.2.2 shows the morphology model that deals with the in-morphology
area proposed by this innovation. It is integrated with the traditional slope and inter­
cept of the model.