Page 363 - Integrated Wireless Propagation Models

C H A P T E R 6

The Lee Comprehensive

Model I n tegration of

the Three Lee Models

6.1 I n troduction
The fast growth of wireless systems has changed our lifestyles in both our work and
our play. The Lee propagation models have been through generations of revolutions
as well as evolutions. At the very beginning, terrain was the dominant factor, and
then the human-made environment became important. Based on the power of com­
putation and the degree of accuracy and granularity of the input data used in the
propagation models, such as terrain and building maps, three different models were
developed for different environments and focuses.
In the previous chapters, the Lee models have been compared with other popular
models. Based on the predicted accuracy and granularity, there are area-to-area and
point-to-point propagation models. Based on the size of radius of coverage area, we
have pico- (in-building), micro-, and macrocell sites. The propagation model can also be
categorized as theoretical, empirical, or statistical to deterministic site-specific models.
A model is characterized by the input data, the computational power needs, and the
demand of accuracy and speed for solving theories and techniques.
The Lee model has developed based on the theoretical, statistical, and empirical
approaches and validated the Lee macrocell, microcell, and in-building (picocell) predic­
tion models with a large amount of field data, as shown in Chaps. 3 to 5, respectively.
The Lee models have been used by the industry and recognized in academic publica­
tions.]-{, Many continuous integrations and enhancements of the Lee model have been
1
shown?- 5 In this chapter, we present the Lee comprehensive model. It explains how to
integrate the three flavors of Lee models to make a complete system design, from pica­
cell (in-building) to microcell to macrocell. Each cell-specific model can be fine-tuned
with field-measured data. The Lee comprehensive model is used to design a general
large system with all three models used simultaneously in the simulated deployment
environment. The predicted results in this deployment modeling are compared with
other models. Also, the predicted results are compared with newly developed models,

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