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

FIGURE 5.2.8.3.8 Measurement points collection.

The next category is for handling the NLOS situation when the client is inside or
outside the room. This category needs handle two different cases since the behaviors
are different in these two cases. The first case is for those data points that are inside the
room but in the NLOS situation. The second case is for those data points that are outside
the room but in the NLOS situation. Based on the location of the client, the accumulated
thickness of the wall can be extracted. Thus, the path-loss curve against the blockage
thickness can be derived.
In circumstance when the client is in the room, the method of calculating wall thick­
ness needs to be enhanced to consider the distance from the wall. This issue is not
addressed in the Keenan-Motley models, as shown in its formula:
L (dB) = 32.5 + 20 log(F) + 20 log(d) + K · F(k) + P · W(k)
+ D(D - Db) + Flag (in room) (5.2.8.3.5)

where Flag (in room) is the value of the loss, depending on the client is whether inside
or outside the room. The parameters of Eq. (5.2.8.3.5) are shown in Sec. 5.2.8.1.

5.3 Enhanced Lee I n - B u i l d i n g Model
At Republic Polytechnic (RP) in Singapore, measurement data were collected from a
2.4-GHz WLAN-developed system installed in many different floors in two different
wings (towers) that are connected by a corridor. The measured data were collected from
single-floor, interfloor, and interbuilding measurements. This section provides a com­
plete solution for in-building-related propagation by validating the Lee in-building
2
modeP·3• 8 for a single-floor scenario first. Then the performance of the Lee in-building
model for interfloor and interbuilding scenarios are examined. Also, the FDTD modeF9
was used to validate the measured data with the Lee model to provide another refer­
ence point. The results show that the Lee model outperforms the FDTD model in calcu­
lating both speed and accuracy.