Wideband Impact of Buildings and Trees on Satellite Mobile
Communication Systems
M. S. AL SALAMEH AND M. M. QASAYMEH
Department of Electrical Engineering
Jordan University of Science & Technology
PO Box 3030, Irbid 22110,
JORDAN,
http://www.just.edu.jo
Abstract- A propagation model for lossy building with tree attenuation in urban and residential areas is
developed for satellite mobile communication systems. This model characterizes the signal transmitted from a
medium earth orbit (MEO) satellite when there are buildings and trees in the path of the signal. The analysis is
performed using the uniform theory of diffraction (UTD). The tree attenuation is evaluated through the
modified exponential decay model (MED). The satellite is assumed to be moving along a circular orbit.
The normalized signal level is computed. Such information is useful in developing the mobile system’s
hand-off algorithm. In wide band systems, the delay-spread is dominant because of the inter-symbol
interference. For such case, the coherence bandwidth and impulse response were computed.
Key-Words: Satellite, Propagation, Building, Tree attenuation, Diffraction, MEO.
1. Introduction
Signal propagation in land mobile satellite (LMS)
communication systems has for the last decade become
an essential consideration. Statistical approaches were
used in modeling the signal propagation [1]. The input
data and computational effort are simple, as the model
parameters are fitted to measured data. Due to the lack
of physical background, such models however, only
apply with good results in environments that are very
close to the one they have been inferred from. On the
other hand, deterministic models provide high
accuracy, but they require actual analytical path
profiles and time-consuming computations [2,3]. A
combination of both approaches has been developed
[4].
For the calculation of the ray contributions in
deterministic methods, a combination of geometrical
optics (GO) and uniform geometrical theory of
diffraction (GTD) is applied [5]. Different research
works focused on the effects of building on radio
channel in satellite mobile communications [6-8]. In
[6], the depolarization effect was considered based on
measurements of received signal near the building
transmitted from antenna placed on a stationary
elevated position. Also, wideband effects of building
were studied by including only single diffraction and
single reflection [7]. Finally, a propagation model for
building blockage in low earth orbit (LEO) satellite
mobile communication system was presented [8]. This
model assumes perfectly conducting walls of the
building, and focuses on how to predict the signal level
at the mobile near the building. Effects of trees on
propagation paths were discussed in [9,10].
In this paper, the effect of lossy buildings on the
signal level from MEO satellite system is examined
using high-frequency ray-tracing methods. The analysis
is performed using the uniform theory of diffraction
(UTD). The tree attenuation is evaluated through the
modified exponential decay model (MED) [10]. The
signal level at the mobile antenna vs. satellite elevation
angle is calculated. In wideband systems, the delayspread is dominant because of the inter-symbol
interference. For such case the coherence bandwidth
and impulse response were computed to evaluate the
performance.
2. Building and Ground Interference
The geometry of the propagation model is illustrated in
Fig. 1. A MEO satellite moving in a circular orbit
above the surface of the earth descends behind a row of
buildings and trees of height and width hb, wb, ht, wt,
respectively, with distance xt between them. An omni
directional mobile antenna located at height hm above
the ground is at distance xm away from the building, so
that all the contributions will have the same gain, also
assume hm< ht < hb. The satellite elevation angle  is
measured from the negative x-axis. The satellite
transmission frequency is 2.1 GHz.
Consider uniform plane wave Ui that is incident on an
edge of lossy dielectric material with (, , ). The
diffracted field at the observation point is:
U d ( P)  D s ,h U i (Q)
y
Building
w1
2.3 Diffracted Fields
wb
Tree
Mobile

hb
ht
hm
z
xm
xt
p
(3)
Where Q is the diffraction point, P is the field point, p
is the distance from Q to P, and Ds,h are the soft and
hard diffraction coefficients of lossy dielectric wedge
[11, 12].
Direct ray
w2
e  jk 0 p
x
3. Tree Attenuation
wt
Fig. 1: Model for building losses and tree
attenuation of the signal from MEO satellite.
The building is assumed to be lossy dielectric
represented by its permittivity and conductivity. The
electric size of both building and tree along the z-axis is
assumed large. The incident ray from the satellite might
undergo reflection from building and ground surfaces,
diffraction from building edges, and attenuation by the
tree. These processes are illustrated below.
2.1 Incident Field
For soft (horizontal) polarization, the incident electric
field Uzi= Ezi is in the z direction while for hard
(vertical) polarization, the incident magnetic field Uzi=
Hzi is in the z direction [5], thus the field at a reference
point is:
The shape of the tree is modeled by a triangle with
height ht and base width wt. The distance that the wave
passes through the tree is denoted by dt. The distance dt
will be one of two cases as shown in Fig. 2. Case 1
when the wave passes through the tree without reaching
its base, and Case 2 when the wave enters the tree and
reflects from its base.
2 (ht  h) tan(  ) cos( )
d t ( h,  ) 
; Case 1
tan(  ) cos( )2  sin 2 ( )
(4)
wt
tan( ) tan(  )
d t ( ) 
; Case 2
sin(  ) tan( )  tan(  )
where   tan 1 (2 ht / wt ) , h is the height at which the
ray meets the center line of the tree, and γ is the angle
between the incident ray and the horizontal direction
0<γ<90o.
Case 1
γ
dt
(1)
U zi (reference)  U 0 .e  jk0 p
where Uo is the amplitude of electric or magnetic field
for soft and hard polarizations, respectively, ko is the
propagation constant in free space, and p’ is the
distance of propagation.
\
2.2 Reflected Fields
Consider uniform plane waves that are incident on a
surface with (, , ) at an angle  with the normal of
the surface. The reflected fields for soft and hard
polarizations are given by:
E zr   s ( ) E zi , H zr   h ( ) H zi
(2)
where Γ , Γ are the soft and hard reflection coefficients,
respectively, that may be found in [11, 12]. The
building has conductivity b=7 S/m and relative
permittivity rb=15, whereas the ground has conductivity
g=0.005 S/m and relative permittivity rg=15 [12].
s
h
h
ht
dt
Case 2
γ
β
wt
Fig. 2: Triangular tree model.
The tree attenuation Lt in dB is estimated through
the modified exponential decay (MED) model [10]
(5)
Lt  0.187 f 0.284 d t 0.588, 200  f  95000 MHz
Where dt is in meters. Substituting (4) in (5), Lt will be
one of three cases:
Lt (h,  )

Lt   Lt ( )
 1

Case 1
Case 2
elsewhere
(6)
4. Formulation of Ray Contributions
The ray contributions are: a) Ground reflection then
second order diffractions, b) First and second order
diffractions, c) First and second order diffractions
followed by reflection from the ground, d) Direct wave,
e) Ground reflection, f) Ground reflection then
diffraction from the building, g) Ground reflection then
diffraction from the building then ground reflection, h)
Building reflection then ground reflection, i) Building
reflection, and j) Ground reflection then building
reflection. It is assumed that the mobile will not be
inside the tree. The reference ray is the non-attenuated
direct component Ei(ref). Thus, to obtain normalized
ray contributions we will divide by Ei(ref). Due to
space limitations, only the formula for the first ray with
soft polarization will be given below.
a) Ground reflection then second order diffractions
0<</2
E i (mobile)  {gs ( / 2   ).D s (w1 ).D s ( w2 )
e
 jk0 .( p1 ( hb  hm ).sin   wb (1cos ) xm . cos )
Lt
wb . p1
}
(7)
where  g is the ground reflection coefficient, and
s
 L h,  , xtr  xm  xtM
Lt   t
1, elsewhere
x .( h  hm )
h  hm
h  hb  t b
,   tan 1 ( b
)
xm
xm
h  hm
xtr  xt  wt / 2, xtM  xt . b
hb  ht
p1  (hb  hm ) 2  x m 2
Note that Lt in equation (7) is the ratio corresponding to
the dB value in equation (5).
5. Wideband Channel Parameters
The basic function that characterizes the wideband
channel is the impulse response h(t,) [13,14]:
h(t ,  i )   Eio ( wc )  (t   i ),  i  d i / c
(8)
i
where c is the speed of light, di is the length of path i, τi
is the time delay along path i, c is the carrier angular
frequency, and Eio is the normalized electric field of
path i. Applying (8) to the ray contribution in (7), the
corresponding impulse response will be:
h(t ,  )  gs (
where

2
  ) D s ( w1 ) D s ( w2 )
Lt
wb p1
 (t   ) (9)
  p1  (hb  hm ). sin   wb (1  cos )  xm cos / c
The coherence bandwidth Bc is a statistical
measure of the range of frequencies over which the
channel can be considered flat [15]. In other words,
coherence bandwidth is the range of frequencies over
which two frequency components have a strong
potential for amplitude correlation. If the Bc is defined
as the bandwidth over which the frequency correlation
function is above 0.9, then Bc  1 /(50  rms ) , where
τrms is the RMS delay (or delay spread) [13]. In wide
band systems, the delay-spread is dominant because of
the inter-symbol interference. Thus, a signal with
bandwidth larger than Bc is highly affected by the
channel. In this case, the channel is said to be
frequency selective.
6. Results
It was shown in [16] that for midpath-obstacle, there
will be 6 dB diffraction loss at the incidence shadow
angle (The angle below which, the direct ray from the
satellite will not reach the mobile). This result was used
to check the validity of the computer programs written
to implement the equations presented in this paper. To
further check the validity of the formulation in this
paper, these programs were used to obtain the results
for the LEO satellites [8] where excellent agreement
were observed.
A typical building in residential environment is
chosen to have 14m height and 10 m width. The mobile
was at a location 20m away from the building and the
antenna height was 3m. A typical building in urban
environment is chosen to have 84m height and 20 m
width. The mobile was at a location 12m from the
building. The tree was at a location 25m from the
building, and has 15m height and 1.5 m width. In fact,
extensive computations were performed for different
building heights, mobile locations, and soft and hard
polarizations. Average values of coherence bandwidth
are shown in Table 1. From Table 1, coherence
bandwidth in residential area is more than that in urban
environment, as expected.
Table 1: Average coherence bandwidth Bc in MHz in
the line of sight (LOS) region
Soft
Hard
polarization
polarization
Urban
10.78
11.21
Residential
34.17
46.51
The normalized signal level at the mobile antenna
in residential and urban environments vs. the elevation
angle was computed for soft polarization, Fig. 3 and
Fig. 4. It is seen from these figures that the variation of
the signal level is faster in urban area as compared with
residential area. Moreover, the range of angles over
10
1
Impulse response
Normalized field strength (dB)
which the signal level is significant is larger in
residential area in comparison with urban area.
5
0
-5
-10
-15
-20
0.6
0.4
0.2
-25
-30
0
-35
-40
0
20
40
60
80 100 120 140 160 180
Elevation angle 
Impulse response
0
-5
-10
-15
-20
50
100
Time in ns
150
200
1
10
5
0
Fig. 5: Impulse response at 120o satellite elevation
angle for hard polarization in urban area.
Fig. 3: Normalized signal level in typical residential
area vs. satellite elevation angle for soft polarization.
Normalized field strength (dB)
0.8
0.8
0.6
0.4
0.2
-25
-30
0
-35
-40
0
20
40
60
80 100 120 140 160 180
Elevation angle 
0
50
100
Time in ns
150
Fig. 6: Impulse response at 120o satellite elevation
angle for hard polarization in residential area.
Fig. 4: Normalized signal level in typical urban area vs.
satellite elevation angle for soft polarization.
The impulse responses for residential and urban
environments at 120o satellite elevation angle are
shown in Fig. 5 and Fig. 6. It is observed from these
figures that the number of significant multipath
contributions is larger in the urban case, which implies
higher fading level. Note also that for the dimensions
chosen for this figure, the tree in the residential case
intercepts the direct ray (at the reference 0 ns) while it
does not intercept the direct ray in the urban case. This
explains why the direct component amplitude is less
than unity in the residential case.
7. Conclusion
Mobile communications using MEO satellites were
considered. The received signal at the earth is the
combination of multipath signals. The multipath
phenomenon results from diffractions and reflections
from the buildings and ground in addition to
attenuation of the trees nearby the buildings. The
building and ground materials are assumed lossy which
required the use of special diffraction and reflection
coefficients for lossy structures. The multipath signals
were described by formulas for each contribution.
Computer programs based on these formulas were
written to find the received signal level at the mobile
and to compute other parameters for wideband
channels. Typical building dimensions in both
residential and urban areas were considered.
To show the usefulness of the analysis in this
paper, various results were presented for signal level,
coherence bandwidth, and impulse response.
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