Page 341 - Integrated Wireless Propagation Models

I n - B u i l d i n g ( P i c o c e l l ) P r e d i c t i o n M o d e l s 319

5.3.5.2 An lnterfloor Case
A general path-loss formula for the interfloor case is

L fl = L'.1+ L".1+ L (d) (5.3.2.2.2.12)
mter oar 1- 1- J 11
Equation (5.3.2.2.2.12) is described in Sec. 5.3.2.2.2.

5.3.5.3 lnterbuilding Case
In the interbuilding case, we are using our modified formula Eq. (5.3.4.3.2) induced
from Borjeson and Backer.9
(5.3.4.3.3)

Equation (5.3.4.3.3) has been described in Sec. 5.3.4.3.

5.3.5.4 The External Building Wall Case

.
5.3.5.4. 1 Transmitter Is Outside the Building This case is shown in Fig. 5.3.4.3 1 . The
transmitter is located outside the building. Use the same formulas shown in Eq. (5.3.5.1),
but let L( ) = 0.
B
1
5.3.5.4.2 Receiver Is Outside the Building This case is shown in Fig. 5.2.2.4. . The
receiver is located outside the building. Use the same formulas shown in Eq. (5.3.5.1),
but let L( ) = 0.
D

m
5.4 E p i r ical Path-Loss Models
Path loss is the signal strength attenuated along the radio path when propagating from
the transmitter at the base station to the receiver at the mobile. Three forms of modeling
are used to analyze these losses: the deterministic model (Maxwell's equation), the sta­
tistical model (probability), and the empirical model (measured data). The determinis­
tic model is more accurate in general to find the propagation prediction if the
environment can be precisely described. Besides, this type of model is computational
complexity. The deterministic model uses Maxwell's equations along with reflection
and diffraction laws. The statistical models use probability analysis by finding the
probability density function of the path loss deduced from the historical data. The
results predicted from this model are fairly accurate, and the computation is simple.
The empirical models use empirical equations obtained from the results of several mea­
surement efforts. This model can give accurate results, but the main problem with this
type of model is computational complexity.
Empirical path-loss models are usually used to provide a high-level first-order assess­
ment of the design. Once the design is completed, measurement data can be collected to
fine-tune the design to provide higher accuracy. The Lee in-building model is one such
empirical model. Usually, higher accuracy requires more detailed physical data and algo­
rithms needed. Site-general models (area prediction models in which sites are not specified)
are sometimes too generic to provide an efficient system design for a specific building. On
the other hand, deterministic (physical) models are sometimes too complex to be imple­
mented to take the full advantage of their capabilities. Even with deterministic models,