Page 209 - Integrated Wireless Propagation Models

C H A P T E R 4

Microcell Prediction Models

4.1 I n troduction
The use of microcells to increase the capacity of cellular mobile communication, espe­
cially in dense urban areas, is an attractive tactic. A number of experimental and theo­
retical studies have been undertaken regarding propagation in the urban microcellular
system. However, predicting the local mean of this microcell requires building layout
data in a 2D or 3D format on aerial photographical maps. Usually, the more detailed the
data, the higher the cost and the more accurate it is to form the model. Balancing the
cost and resolution of building layout data with the accuracy of the model is always a
challenging task.
Microcell prediction is a very important tool in RF design in dense urban areas,
especially for both cellular and WLAN applications. Generally, a microcell is defined as
a cell located in dense urban area, providing less than 1 mile or 1 km of coverage (in
radial) on a generally flat terrain with a low transmitted power (less than 1 W ERP) and
embedded within a cluster of buildings.
When the size of the cell is small, less than 1 mile or 1 km, the street orientation and
individual blocks of buildings have significant effects on signal reception. These vary­
ing street orientations and individual blocks of buildings do not make any noticeable
difference in reception when the signal is well attenuated at a distance over 1 mile or
1 km based on the measured data. However, when the cells are small, a signal receiving
multiple reflections from the individual buildings along the path, before arriving at the
mobile unit, is weakened. These buildings directly affect the received mobile signal
strength and are considered part of the path loss. The general path loss prediction is an
average process. Therefore, we do not need high-resolution 2D and 3D building data,
which are expensive and difficult to obtain and to process correctly. Even though
detailed building data are available, the associated parameters might make the imple­
mentation and accuracy of the model more complicated and less efficient.
There are many microcell prediction models for dense urban-area propagation pre­
1
dictions. -9 This chapter starts with the introduction of the Lee microcell model, how it
works, and what are its enhancements. Then other microcell prediction models will be
presented and discussed. The first few sections focus on the Lee microcell propagation
l 10
model. · The Lee model predicts the local mean from the statistical properties of the
average signal strength, or long-term fading, based on physical parameters, such as
antenna height, frequency, and building thickness. The model starts with 2D building
data, and has been verified against many dense urban areas around the world with
good results. It was enhanced first to deal with the terrain effect in dense urban areas,

187