Wireless Channel Prediction in a Modern Office Building
Using an Image-Based Ray Tracing Method
(submitted to Globecom 93)
C. M. Peter Ho and Theodore S. Rappaport
Mobile and Portable Radio Research Group
Bradley Department of Electrical Engineering
Virginia Polytechnic Institute and State University
1 ABSTRACT
In this paper, the methodology of a three dimensional imagebased ray tracing algorithm is presented. Building information
and antenna properties are used to predict wide-band channels in
a modem office building. Compariscns between prediction
results and measurement results are also given in this paper.
2 INTRODUCTION .
In the last few years, many measurements were made to
. characterize indoor wide-band channels [1]-[4]. Based on the
measurement results; we have some rough ideas about the path
loss and rms delay spread values. in different indoor
envirooments. However, more accurate signal prediction
techniques are necessary to provide optimum capacity and
maximum coverage for future indoor wireless communication
systems [5]. Site-specific channel impulse response prediction
methods, which can incorporate geometrical information of the
envirooment, are desired because measurements are usually
costly and time-consuming. Recently, much work in MPRG has
focused on development of site-specific propagation models [6][8]. The use of building data base in prediction of three
dimensional diffraction has been demonstrated by Russell [6]. A
ray tracing algorithm for the microcellular environment has been
proposed and implemented by Schaubach [7]. A "brute force"
ray tracing method is used in [7] to account for all possible
propagation paths. A similar algcrithm is used for in-building
predictions [8]. Path loss prediction errors are shown to be
within 5 dB for most cases. Therefore, site-specific propagation
models show promise for accurate signal prediction.
Besides brute force ray tracing method, an alternative approach
to implement ray tracing is image theocy. Previous waks based
on image theory include references [9]-[12]. However. all these
models ignore antenna polarization. As shown by [3] and [4],
antenna pattern and polarization have significant effects on path
loss and rms delay spread of wireless channels. In [13], antenna
pattern and antenna polarization effects are included in the
prediction. A channel impulse response predictioo model within
an empty box utilizing image theory is proposed and tested in
reference [13]. Nevertheless, none of the above image-based
models are general enough to include building geometry,
This work
wu
sponsored by
Affiliates, and DARPA
Teledyne Inc.,
polarization effects, antenna pattern effects and penetration
losses. A three-dimensional image-based ray tracing algorithm
that can include effects of surroundings walls, obstacles inside
buildings, antenna patterns and antenna polarizations, is
described in this paper. In this model, the magnitude and the
phase of each multipath component are computed. This model
can even include effects of surrounding buildings. Also, the
algorithm is flexible enough to trace multipath components up to
any number of reflections. Preliminary results show that imagebased algorithm is a viable technique for indoor propagation
prediction.
3 IMAGE-BASED RAY TRACING ALGORITHM
An overview of this prediction model is given in Figure 1. FI!St,
the algorithm reads in building geometry from the blueprint. The
user also needs to define various parameters such as antenna
patterns and antenna locaticns. The algorithm is able to peiform
ray tracing up to a level specified by the user. That is, the
program can include all first order, second order and up to the Nil
crder reflectioo paths. Multipath sources are determined by
image theory. For example, a single-hop multipath component as
shown in Figure 2 has an image located at location IM. The
reflection point P can be determined by the intersectioo between
the object and the line fran 1M to the receiver. As shown in
Ftgure 2, incident and reflected electric field can be decomposed
into parallel and perpendicular polarizations. Secood order
reflection paths can be determined by secondary images, which
are created by considering primary images as sources. Similarly,
multiple reflection paths can be determined by creating images
recursively. The methodology for determining multiple
reflection paths is explained in detail in [14]. Since all objects
are finite in extent, intersection tests must be perfoo:ned to check
if physical reflection paths exist or not. For fixed transmitter
locations, same images can be used to determine channel
characteristics at multiple receiver locations.
As shoWn iri. Figure 1, after a propagatioo path is determined.
geometrical information is used to compute the received power
using Ge<metrical Optics (GO) assumption. Transmissioo losses
are then added to each multipath component. The last two blocks
of the algorithm are explained i..D. detail in the next sectioo.
MPRG Jndustrtal
IEEE GLOBECOM '93.
objects data.
transmitter location and antenna
receiver location and antenna
frequency, level ci ray tracing
--------------,
'''
''
'''
'
Geometrical
Analysis
!Detennination of
!Propagation Paths
''
'''
•••••••••••••,
----------- -------------J
r••••••••••
I
I
:I
Compute Received
Power using GO
and Fresnel Formulae
I
I
:I
:
:'
! Computation of Received
!Power and Absolute Tune
!Delay
solution of the problem when the wavelength vanishes <X' the
frequency approaches infinity. High frequency methods can give
reasooable results to most problems that are not solvable by other
methods. Moreover, the surfaces of the objects are assumed to be
smooth. Most walls and partitions in indoor envirmments are
"smooth" at 2.45 GHz. A roughness factor should be included if
the system operates at higher frequency. Moreover, a diffuse
scattering component should be included into analysis if the
swface is "rough." Most obstacles in indoor environments can
be modeled as a dielectric slab with predefined thickness,
boundaries and dielectric constant. In the proposed algorithm, all
objects are assumed to be finite rectangular planes (rectangular
panels). Although walls and other obstacles have finite width,
reflection coefficients are approximated by the Fresnel
coefficients in this paper. To simplify computation, diffraction is
not cmsidered in this paper [12]. In addition, far field conditions
for the antennas are assumed. The received power of eaeh
component can be determined by using the following equation
[14].
e-jfJL
'
----------- --------------!
I
-
FIGURE 1 Image-Based Ray Tracing Algorithm
TX
RX
...................
~<I>R
1
...······
..··
./........./
! . .· ·
This plane needed to be
defined within a certain
range and with a certain
diefectric constant fl.
·~:IMAGE
....
•fN•hR
(1)
r.-rl.i~~+G~~
J
J
2
oo
p • P_jKI2(Gr<JRA.)
R
T'
16~2
(S)
Table l: Symbols in Equations (l) to (3)
Explanations
Symbols
Q
...
Symbols in the above equations are explained in Table 1.
Polarization characteristics at reflecting interfaces are described
by dyadic reflection coefficients.
'f
1.
-
K • "'LFT(Br+r>FR(8R,.R)hr•f1 •f2 •
Fr!FR
Transmitter/Receiver Antenna Pattern
Gr!GR
Antenna Gains
hr I hR
Antenna Polarization Vectors
L
Total Propagation Path Length
p
Phase Constant (=2rr/A.)
r;
Dyadic Reflection Coefficient at the jtb Interface
r~1r.Lj
Fresnel Reflection Coefficients
Prl PR
Transmitted/Received Power
-
llj, hj.
,lj. ,.
.Lj
Defined in FtgtlfC 2
FIGURE 2 A Single-Hop Multi path Component
Transmission Through Obstacles
4 PROPAGATION MODEL
Assumptions
A Geometrical Optics (GO) propagation model is used in the
prediction algorithm. Both phase and polarization are included
in the model. The model can give accurate results if the size of
the obstacle is much larger than a wavelength, and the
observation point is many wavelengths from the scatterer.
Alternatively speaking, the predictioo provides an asymptotic
The propagation path determined from an image only utilizes
parts of the object's data. To include the rest of the objects into
account, intersection tests for the propagation path is required. If
the propagation path for a certain image exists, we can then
determine whether the refiected ray transmits through soxne
obstacles or not. This can be done by checking whether ·each
reflection "sub-path" intersects with any other objects. This part
of the algorithm is similar to the "brute force" ray tracing
program [7]-[8], which needs to check intersection between each
FIGURE 3 Teledyne's 2nd F1oor Office
ray and each object. However, the number of rays needed to
perform intersection test for the algorithm here is far Jess than
that c:i "brute force" ray tracing. Moreover, each path is known
to be a valid propagation path. Each propagation "sub-path" is
given by the following vector equations,
'Pi· ktj+Pi-1 tor
k~IPj-Pi_ 1 1 and l~j~N+l
<4>
(5)
where Pi is the jth reflection point. The received voltage,
including effects of transmissiro losses, is given as follows.
-jf'L
.
V' • TFr<ar+r>FR(aR,+R>hr•r 1 •T1 •T2 •r2 • ••• rN•hR
(6)
Symbol ~ is the dyadic transmission coefficient The exact
order of the dyadic coefficients in equation (6) depends on the
order of transmissions and reflectioos. For example, equation (6)
assumes a propagation path with a reflection first, followed by
two transmissions and a reflection, and so on.
However, it is much simpler to assume the attenuation caused by
each obstacle to be the same. The voltage induced at the receiver
is then given by multiplying equation (3) by a.K, where a is the
attenuation caused by each penetration, and K is the number of
penetrations through obstacles. The implementation of equation
(6) can be done as an extensioo. of the current version of the
program. The fundamental concept and formulation of the
image-based ray tracing method have been presented.
5 PREDICTION INSIDE TELEDYNE'S BUILDING
Comparisons Between Measured and Predicted Radio Channels
Wide-band measurement results in Teledyne's office building at
2.45GHz were presented in [4]. Twenty-five antenna
combinatioos were tested in [4] to study effects of antenna
pattern and antenna polarizatioo. oo. indoor wide-band channels.
All measurements were made in Teledyne's 200 fi<XX" office,
which is a typical open-plam:Jed modem office environment.
Prediction and measurement results in Teledyne's office are
compared in this section.
A hard-copy of the Teledyne blueprint was· availab1e, and each
object in the building was defined manually. Since the office
contains about two hundred to three hundred objects, it is
extremely tedious and time consuming to define all objects
manually. Hence, oo.ly 52 objects, which represent important
characteristics of the environment, are "sampled" and defined in
the objects data file. The defined objects are given in Figuie 3.
Each object is either a 2m high wooden soft partition or a
concrete wall which extends between floor and ceiling.
Furtherm(X'e, it ~ust be stressed that even all the objects in the
blueprint are included in the prediction. there are still many
objects such as furniture that are ignored in the prediction. It is
believed that Figures 3·gives a reasooable approximation to the
geometry of the environment. The origin of the cocxdinate
system is chosen at one corner as shown in FtgUre 3. The
building is 43.3 meter by 82.3 meter and the height of the ceiling
from the floor is 3 meter. For all measurements. the transmitter
was placed at (95. 32.0) meter.
To compare measurement results with prediction results. the
predicted channel impulse response is convolved with a 30ns
pulse to obtain the corresponding predicted power delay profile.
In this paper, only prediction results fc:r copolarized discone
antennas are presented. Comparisoo.s between measurement
results and predicted results are necessary to verify the validity of
any propagation models. In [11] and [13]. image-based -ray
tracing techniques were used to predict channel impulse
responses, but no comparisoos with measured data were given.
Path loss is an impcxtant design parameter. and hence the
accuracy of predicted path loss values is a common measure of
the accuracy of a propagatioo. model. Comparisoo.s between
predicted and measured path loss values were given in [7], [8],
[15]. However, path loss is a necessary but not sufficient
parameter to determine the validity of a propagation model since
the time dispersion information of the channel is ignaed.
Therefore, comparisons between measured and predicted rms
delay spread (a~) values in Teledyne's office are also presented.
Two profiles can have different shapes yet have identical path
loss and rms delay spread values. Qualitative e<mparisons
between shapes of measured and predicted power delay profiles
can give insights to the actual propagation mechanisms. Due to
lack of space, qualitative comparisons are only given at one
locatioo. in this paper.
slightly better quantitative results than tbe predictioo. using
secood order ray tracing. The shapes of the predicted profiles
using second order or third order ray tracing are extremely close.
't
-75.0
-78.5
-82.0
a~
PL
Measured 78na 60ns 77d8
evel•2
43na 40ns 78d8
evel-3
6lna 49ns 77d8 . . - - - - - - - .
l
r.teaaarwd
fobb2
- - - fobb3
-85.5
Some important assumptions and parameters used for prediction
in Teledyne's building are summarized as follows [14].
•Teledyne's second floor office is modelled by the defined objects
as shown in Figure 3.
•Ceiling is modelled as a rough surface and does not contribute
significant signal compments to the receiver [15].
•Transmission loss for each object is assumed to be 2dB for all
incidence angles [16].
•.f=2.45GHz.
•The dielectric constant for each object is arbitrarily chosen to be
real with value of 15.0. For future work, the predictioo. error can
be minimized by optimizing the dielectric constant [17].
Figme 4 shows the measmed power delay profile verstis the
predicted power delay profiles at obstructed location F using copotarized omnidirectional discone antennas at both the
transmitter and the receiver. 1be transmitter and the receiver are
separated 30 meter apart. In the measured profile, multipath
compments with the most energy arrive between absolute time
delay interval of 150ns and 270ns. A similar behavior is found
for the predicted profiles. There are also significant amount of
signal components near 300ns and 375ns. The predicted power
delay profiles successfully capture these two significant late
arriving components. The earty part of the predicted power delay
;;:)files are not as "smooth" ..s that of the measmed power delay
profile. This is because the actual number of arrival components
in time interval 150 to 270ns is really large. Since only 52
objects are used in the model, some arrival components are not
predicted. If more objects are used in the prediction, a
"smoother" major signal component will appear in the predicted
profiles. Since many objects such as furniture cannot be included
in the objects data, prediction results here seem to be fairly
reasonable for such approximate description of the environment.
The measured path loss is 77dB while the predicted path loss
using second order ray tracing is 78dB. The predicted path loss
using third order ray tracing is 1dB smaller than the predictioo.
using second order ray tracing because more arrival components
are included in the third order model. The measmed mean excess
delay (-t), and the predicted mean excess delays using second
order and thkd ocder ray tracing are 78ns, 43ns, and 61ns
respective.ly. The predicted rms delay spreads are within 20ns of
the measured one. At this location, the general shape of the
predicted profiles agree reasonably well with the measmed one.
In this example, the prediction using third ocder ray tracing has
FIGURE 4 Predicted and Measured Profiles at Location F
The rms delay spread, mean excess delay and the wide-band path
loss values for the measured profiles and the predicted profiles
using third ader ray tracing at eleven locatia:J.S are given in Table
2. The path loss error is unbiased, that is, the average path loss
prediction error is almost zero decibels. There are cases of overpredicted and under-predicted path loss values. The standard
deviation of the prediction error is 4.6dB for second order ray
tracing and 4.7dB for third order ray tracing over a 20dB path
loss dynamic range. Worst case path loss error is 9dB. The path
loss prediction erras are close to that of [8]. Moreover, there
does not seem to be much difference between the predicted path
loss values using second order or third order ray tracing. This is
because the probability . of a significant triple or multiple
reflection path is low. In carida environments, radio channels
behave like rectangular waveguides. ·For such cases, high order
reflection paths can contribute significantly towards the received
power because high order reflection components do not
experience any penetration losses in hallway environments.
Assuming the predicted mean excess delay or rms delay spread
should be within a facta of two relative to the measured data for
"good" predictioo, most data points can be classified as good
prediction. However, there are large delay spread predictioo.
errors at couple locations. Since rms delay spread is sensitive to
small changes of power delay profile, it is not necessarily a good
measure of prediction accuracy. Similar prediction problems fa
rms delay spread are also found in [7]. It appears ·that a better
method to quantify time dispersion is required. Qualitative
comparisons of predicted and measured power delay profiles
show that the shapes of the profiles agree reasonably. well at most
locations.
Table 2: Meawred and Third Order Prediction :a-ult.
Predicted M-nd
i
(M)
[Ray
Receiver
Meuured
Locadoa
i (IY) 1'raciDc
(Topocraphy)
Lev.-3]
A (LOS)
B (OBS)
C(LOS)
D (LOS)
E(OBS)
F(OBS)
G (LOS)
H(LOS)
I (OBS)
L(OBS)
M(OBS)
50
62
47
51
59
78
53
50
101
59
65
28
40
78
68
39
61
50
42
42
34
31
a~(.,.)
Predicted
a..(.,.)
[Ray
Meuuncl Preclicted
Path La. Palla La.
(dB)
(dB) [Ray
Tracinc
Tnlcinl
Le..J-3]
34
37
29
36
43
60
48
41
74
38
37
40
29
85
76
20
49
62
57
42
33
29
Lenld]
64.8
64.0
70.1
69.8
73.5
77.1
76.3
69.4
73.1
68.9
73.6
64.7
69.2
61.1
64.3
74.6
76.8
78.7
71.3
82.4
71.0
76.8
If the computation is performed over the entire office area, a map
of channel parameters can be obtained. The predicted path loss
superimposed on top of the blueprint is given in Figure 5. The
path loss map can be very useful for coverage, interference and
capacity analysis.
38
56
measured values at most locations. The shapes of the measured
power delay profiles also agree reasooably well with predicted
power delay profiles. Although comparison statistics are not
large enough to give a broad-based cooclusion on the
effectiveness of the prediction model it appears that the imagebased ray tracing algorithm shows promise for effective and
efficient in-building site-specific propagation predictioo.
7 REFERENCES
[1] Devasirvatham, D. M. I., "A Cornpari8011 ofT!Dle Delay Spread and Signal
Level Measurements within Two Dissimilar Office Buildings," IEEE Transaction
on Anltnna and Propagation, AP-35, No.3, pp. 319-324, 1987.
[2] T. S. Rappaport, "Otaracterizatioo of UHF Multipath Radio Otannels in
Factory Buildings," IEEE Transactions on Anrenna and Propagation, Vol 37,
No.8, Aug. 1989, pp. 1058-1069.
[3] T. S. Rappaport and D. A. Hawbaker, "Wide-Band Microwave Propagation
Parameters Using Circular and Linear Polarized Antennas for Indoor Wireless
Cllannels," IEEE Transactions on Co111111U11ications, Vol. 40, No. 2, Feb. 1992
[4] C. M. P. Ho and T. S. Rappaport. "Efrccta of Antenna Polariza1ion and Beam
Pattern on Multipath Delay Spread at 2.4SGHz in Indoor Obstructed Wtrelcss
Owmels," 1st International Confennce on UniverStJl Personal Communications,
Dallas, Sept. 29-0ct.2.
[5] T. S. Rappaport and L B. Milstein, "Effects of Radio Propagatioo Path Loss
oo DS·CDMA Cellular Frequency Reuse Efficiency for the Reverse Otannel,"
IEEE Transactions on Vehicular Technology, Vol. 41, No. 3, August 1992, pp.
231-242.
[6] T. A. Russell, T. S. Rappaport, and C. W. Bostian, "Use of a Building
Database in Prediction of Three Dimensional Diffraction," 42nd IEEE Vehi~r
Technology Conference, Denver, May 1992, pp. 943-946.
[7] K. R. Schaubach, N. I. Davis IV and T. S. Rappaport, "A Ray Tracing
Technique for Predicting Path Loss and Delay Spread in Microcellular
Environments," 42nd IEEE Vehicular Technology Conference, Denver, May
1992, pp. 932-93
[8] S. Y. Seidel and T. S. Rappaport. ..A Ray Tracing Technique to Predict Path
Loss and Delay Spread Inside Buildings," Globecom 92, Orlando, Dec. 6-9 1992
74
[9] A. Ranade, ..Local Access Radio Interference due to Building Reflections."
IEEE Transactions on Communications, Vol. 37, No. 1, Ian 1989, pp. 70-7.!.
91
l(~Ji:~
(10] A. Rusta.k:o, Jr., N. Amitay, G. I. Owens, and R. S. Roman, "Radio
Propagation at Microwave Frequencies for Line-of-Sight Miaocellular Mobile
and Personal Conummications," IEEE Transactions on Vehicular Technology,
Vol. 40, No. 1, Feb. 1991, pp. 203-210.
(11] I. W. McKown, and R. L Hamilton, ''Ray Tracing as a Design Tool for Radio
Networb," IEEE Network Magazine, Vol. 5, No.6, Nov. 1991, pp. 27-30. ·
Path Loss (dB)
FIGURE 5 Path Loss Map
6 CONCLUSION
In this paper,. the methodology of an image-based prediction
algorithm is described. Comparisons between predicted resUlts
and measured results in Teledyne's office building at 2.45GHz
for copolarized discone antennas are presented. Path loss errors
are shown to be unbiased with a standard deviation of 4.7dB.
Predicted rms delay spread values agree reasonably well with the
[12] M. H. Barton, I. P. McGeehan, A. R. Nix and M. C. Lawton, ..Error Rate
Prediction for High Data Rate Short Range Systems," Virginia Tech's 2nd
Symposium on Wireless Personal Communications, BlacbbiD'g, June 17·19,
1992.
[13] P. F. Driessen, M. Gimersky, and T. Rhodes, ''Ray Model of Indoor
Propagation," Virginia Tech's 2nd Symposium on Wireless Personal
Communications, Blacksburg, I une 17-19, 1992.
[14] C. M. P. Ho, "Propagation Measurements and Predictions· for In-Building
Perscinal Communication Systems," Master's Thesis in Electrical Enginuring,
Virginia Tech, March 1993.
[15] W. Honcharenko, et. al., "Mechanisms Governing UHF Propagation on
Single Aoot!l in Modem Office Buildings," IEEE Transactions on Vehicular
Technology, Vol 40, No.4, Nov 1992, pp. 496-504.
[16] S. Y. Seidel. T. S. Rappaport, "914 MHz Path Loss Prediction
Models for Indoor Wireless Communications in Multifloored
Buildings," IEEE Transactions on Antenna and Propagarion, Vol. 40,
No.2, Feb.1992, pp. 207-217.
[17] S. Y. Seidel, "Site-Specific Propagation Prediction for W1reless In- .
Building Personal Communication System Design," Ph.D Dissertation
in Electrical Engineering, Vlfiinia Tech, Feb. 1993.
-
\).
'
~
~I
Path Loss Map in Teledyne's Office
38
56
74
91
109
Path Loss (dB)
Path Loss Map in Teledyne's Office
March 8, 1993