Page 358 - Integrated Wireless Propagation Models

336 C h a p t e r F i v e

Comparing the predicted results with the measured data, the deviation between the
two at any measured spot is plotted. From all the deviation values, a map of deviations
is formed. By applying a linear regression, we can find the best-fit slope of each element
to replace the existing one in the formulas. Through this procedure of fine-tuning the
model, we do not worry about the specific details of the floor or building. The Lee
model deals with single-floor, interfloor, single-building, interbuilding, and intersites.
The model, integrated with measured data, provides better accuracy and efficiency. It is
simple and cost effective to use. The general formula of the Lee in-building model is
discussed in Sec. 5.3.5.
Chapter 6 will describe how to integrate the three models of the Lee model-macro-,
micro-, and picocell-into one Lee integrated model by combining and transiting the
different individual models in different areas. The Lee model tries to find a balance
among many different parameters, including accuracy, run time, data granularity, com­
plexity, scalability, and a means of fine-tuning the model. The most common practice is
measurement integration.
As demands increase for more integration and more accuracy, propagation­
predicted models are needed to provide ubiquitous coverage, throughput, and capacity.
The Lee models have evolved and developed to meet the demands on capabilities as
well as accuracy, speed, required data input, and flexibilities. The Lee model started
from a theoretical and statistically based model, then the measured data are integrated
in the model to further improve the accuracy of the model. In addition, different cell
size models need different input parameters to improve the accuracy of the models.
In the macrocell model, we need terrain and clutter data; in the microcell model, we
need building, terrain, and attribute data; and in the Picocell model, we need to have
wall, building material, window, and room dividers. Also in the next chapter, we will
discuss some relatively new activities in the propagation prediction field with new and
old technologies. The chapter also provides a more detailed and insightful view of the
Lee comprehensive models.

References
1. Lee, W. C. Y. Wireless and Cellular T e lecommunications. 3rd ed. New York: McGraw­
Hill, 2005: 389-391, 639-640, 655-656, 674-677.
2. Dobkin, D. "Indoor Propagation Issues for Wireless LANs." RF Design Magazine
(September 2002): 40-46.
3. Lee, D. J. Y., and Lee, W. C. Y. "Propagation Prediction in and through Buildings."
IEEE Transactions on V e hicular T e chnology 49 (2000): 1529-33.
4. Honcharonko, W., Bertoni, H. L., Dialing, 1., Qian, J., and Yee, H. D. "Mechanisms
Governing UHF Propagation on Sinfle Floor in Mordern Office Buildings." IEEE
Transactions on Vehicular T e chnology (May 1992): 77-82.
5. Rappaport, T. S. "Indoor Radio Communication for Factories of the Future.' IEEE
Communications Magazine (May 1989): 15-24.
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6. Molkdar, J. D. "Review on Radio Propagation into and within Buildings " IEE
Proceedings-H (February 1991): 61-73.
7. Lafortune, J. F., and Lecours, M. "Measurement and Modeling of Propagation Losses
in a Building at 900 MHz." IEEE T r ansactions on Vehicular T e chnology 39 (1990): 101-8.
8. Devasirvatham, D. M. J., Banerjee, C., Krain, M., and Rappaport, D. "Multi-Frequency
Radiowave Propagation Measurements in the Portable Radio Environment." in
Proceedings of the IEEE ICC '90, April 1990, 1334-40.