In this paper the combined effect of specific attenuation due to Fog and Snow on FSO and RF links is considered. Optical wave attenuation due to low atmospheric visibility conditions causes a performance degradation of free space optical (FSO) communication systems.

1. 47 ICRTEDC -2014
Vol. 1, Spl. Issue 2 (May, 2014) e-ISSN: 1694-2310 | p-ISSN: 1694-2426
GV/ICRTEDC/12
DATA RATE ANALYSIS AND COMPARING
THE EFFECT OF FOG AND SNOW FOR
FREE SPACE OPTICAL
COMMUNICATION SYSTEM
1
Er. Sagar, 2
Dr. Rajesh Goel
1,2
Department of Electrical & Electronics Engineering, Samalkha Group of Institutions, Samalkha, India
1
sagar.kumar524@gmail.com, 2
director@sgi.ac.in
Abstract— Optical wireless technology or Free Space
Optics (FSO) is much more similar to the fiber optic
communication except the fiber optic in which atmosphere
is used for the data transmission using laser beam from
transmitter to receiver. In this aspect possibility of
different applications, the performance of such links is
extremely dependent on different weather conditions
particularly in presence of fog. Snow also affects the free
space optics. The weather conditions that reduce visibility
affect the FSO performance. In this paper the combined
effect of specific attenuation due to Fog and Snow on FSO
and RF links is considered. Optical wave attenuation due
to low atmospheric visibility conditions causes a
performance degradation of freespace optical (FSO)
communication systems. Both visibility and attenuation
are measured on a long experimental free space optical
link. Meteorological conditions causing particular
attenuation events are identified. Available models of the
relation between atmospheric visibility and optical
attenuation are compared with the measured data. It is
shown that classical models widely used in the FSO
community still underestimate optical attenuation at
medium and low visibility conditions.
Keywords—Free space optics, optical communication,
RF links.
I. INTRODUCTION
Depending on the environment and range over which an
FSO link operates, it is subject to different impairments.
Long-range links use directed laser beams to transmit data,
and can be used for building-to-building, ground-to-
aircraft, or ground-to-satellite communication. Such links
may operate over ranges of several kilometers or longer,
and often their primary impairment is atmospheric
turbulence, which causes phase and intensity fluctuations
in the received signal. Short-range links often use infrared
or visible light emitting diodes (LEDs) and can be used
indoors for data communications or outdoors for vehicular
communication. Such links operate over ranges of meters
to hundreds of meters and hence are not strongly affected
by atmospheric turbulence. Outdoor links may be subject
to impairment by atmospheric effects, such as rain, fog
and haze. There have been several studies on the impact of
these effects on FSO links, but these studies only take
account of the attenuation caused by them. In particular,
these studies do not take account of how rain, fog and haze
may degrade the performance of an imaging receiver. An
imaging receiver employs a lens, telescope or similar
optical system to image a received signal onto an image
sensor, which is subdivided into multiple pixels. Such an
imaging receiver can separate a desired received signal
from undesired ambient light and interfering
transmissions. Atmospheric effects, such as fog, can
degrade the performance of imaging receivers by two
mechanisms. First is attenuation of the signal, caused both
by absorption and by scattering of light out of the field of
view (FOV) of the receiver. The second mechanism is the
blooming of the image spot at the receiver focal plane,
which causes the spot to spread over a larger area, and
thus a larger number of pixels, on the image sensor. When
the signal power is spread over a larger number of pixels,
each contributing noise, the receiver electrical signal-to-
noise ratio (SNR) is reduced.
In this paper, we analyze FSO links with imaging
receivers in the presence of atmospheric effects, such as
fog or haze, and misalignment. The analysis is based on
the radiative transfer equation, and takes into account both
attenuation and image blooming. We quantify the relative
importance of these two phenomena and study the overall
link performance under different weather conditions. To
our knowledge, this is the first work that takes account of
image blooming caused by atmospheric effects.
II. PROPAGATION THROUGH FOG
As light propagates through the atmosphere, it can get
scattered multiple times, which results in a glow around
the light source in the image. Multiple scattering can be
neglected in clear air or light rain, but becomes
particularly important in haze or fog. There are different
approaches for modeling propagation of light with
multiple scattering. One class of methods involves
numerical Monte-Carlo ray-tracing simulation. A
drawback of such methods is their high computational
complexity, which can grow exponentially with the
number of scattering events to which a ray is subjected.
A.Fog Attenuation Model for FSO
The specific attenuation model is given by
( ) = 13( ) −
(550)
−
Here, V(km) stands for visibility, λ in nm stands for
wavelength and λ0 as visibility reference (550 nm).

2. ICRTEDC-2014 48
=
1.6 > 50
1.3 6 < > 50
0.585 /
< 6
The attenuation of 1550 nm is expected to be less than
attenuation of shorter wavelengths. Which is rejected such
wavelength dependent attenuation for low visibility in
dense fog. The q variable in equation is given by
=
⎩
⎪
⎨
⎪
⎧
1.6 > 50
1.3 6 < > 50
0.16 + 0.34 6 < < 1
− 0.5 0.5 < < 1
0 < 0.5
A Telecom model has provided relations to predict fog
attenuation. It characterizes advection and radiation fog
separately. Al Naboulsi provides the advection fog
attenuation coefficients as
=
0.11478 + 3.8367
Radiation fog is related to the ground cooling by radiation.
Al
Naboulsi provides the radiation fog attenuation
coefficients as
=
0.18126 + 0.13709 + 3.7502
The specific attenuation for both types of fog is given by
=
10
ln(10)
( )
The linear wavelength dependence of attenuation in case
of advection fog and quadratic wavelength dependence of
attenuation in case of radiation fog. This model shows
more wavelength dependence of attenuation for radiation
fog case.
Fig1 Specific attenuation for different models for 850nm,950nm and
1550nm Wavelength
The kruse model for specific attenuation is more
prominent. The Kim model is wavelength independent. It
effects for visibility greater than 1km. Al Nabulsi model
has more attenuation effect than kruse and kim. The
Specific attenuation of Fog is also calculated for different
visibility using wavelength as shown in fig. 2.
Fig2 Specific Attenuation for different Fog w.r.t. Wavelength
The Specific attenuation of Fog is also calculated for
different visibility using wavelength. The heavy fog has
more effect than the other. It means that for less visibility
there is greater attenuation.
B.Snow Attenuation for FSO
The FSO attenuation due to snow has been classified into
dry and wet snow attenuations. If S is the snow rate in
mm/hr then specific attenuation in dB/km is given by
asnow=a.Sb dB/km
If λ is the wavelength, a and bare as follows for dry snow
a =5.42*10-5λ+5.4958776
b =1.38
The same parameters for wet snow are given as follows
a =1.023*104λ+3.7855466
b=0.72
The specific attenuation for FSO is wavelength
insensitive. There are very little changes in the attenuation
for different wavelengths. The specific attenuation for dry
and wet snow is also calculated. The dry snow effects at
the low snow rate whereas wet snow effects at high snow
rate as in fig 3.
The specific attenuation is 110 dB/km for dry snow rate 9
mm/h. As there is not much difference between the dry
snow rate for different wavelengths.

3. 49 ICRTEDC -2014
Fig 3 Specific Attenuation of Different FSO Wavelength for Wet Snow
Rateup to 100 mm/hr
III. COMMUNICATION LINK MODAL
We now consider three types of communication links: the
receiver signal power, link margin, and data rate. In
addition, we performed a signal to noise ratio calculation.
A. Receiver Signal Power
We shall consider the situation of optical propagation
between
points underwater. Consider a laser transmitting a total
power
Ptrans at the wavelength. The signal power received at the
communications detector can be expressed as
= . 10 . /
Where D is the receiver diameter, θ is the divergence
angle, γ is the attenuation factor (dB/m), τtrans, τrec are the
transmitter and receiver optical efficiency respectively.
B.Data Rate
Given a laser transmitter power Ptrans, with transmitter
divergence of θ, receiver diameter D, transmit and receive
optical efficiency τtrans, τrec the achievable data rate R can
be obtained from
=
10 . /
(
2
)
Or can be written as
=
4
Where Ep= hc/λ
C.Signal to noise ratio
The SNR for the optical communication system is thus
given by
=
( )
2 ( + ) + 2 + 4
IV. SIMULATION RESULT
Simulation by matlab carried out to show the weather
effect on optical communication System. The performance
of optical communication system can be evaluated by the
receiver signal power, data rate and signal to noise ratio.
We have investigated the high quality and the best
performance of optical communication link systems for
different weather conditions. The investigating based on
the modeling equations analysis and the assumed set of the
operating parameters are shown in Table.
TABLE I
S.No Operating Parameter Value
1 Transmitter Power 50MW
2 Transmitter Divergence
Angle
1 ≤θ(mrad)≤3
3 Transmitter Efficiency 0.9
4 Range 1 ≤ L(m) ≤ 1000
5 Receiver Diameter 1 ≤ D(cm) ≤10
6 Receiver Efficiency 0.9
7 Receiver sensitivity -20Bm
8 Wavelength 650mn
9 Bulk Dark Current 0.05 nA
10 The APD Gain 100
11 The Excess Noise Factor 0.5
12 Electrical Band 25 MHz
13 Surface Leakage Current 0.001A
14 System Temperature 290K
15 Noise Figure 3dB
16 Equivalent Resistance 50k ohm
17 Weather Condition Clear 0.7(dB/Km)
Haze 7.77(dB/Km)
Light Fog 10.5(dB/Km)
Heavy fog 34.96(dB/Km)
So the receiver signal power due to the effect of weather
conditions can be evaluated. The receiver signal power is
achieved for (650) nm under the effect of clear, haze, thin
fig, light fog and heavy fog as shown in fig. (4), has
proved that the receiver signal power increases with
increasing receiver diameter. It is also observed that the
wavelength 650nm has presented high received signal
power for clear sky compared with the other conditions.
The receiver signal power decreases with increasing
transmitter divergence angle and range for the conditions
under study. The receiver signal power curves have very
different behavior with increasing range about (0.3) km

4. ICRTEDC-2014 50
Fig 4. Simulation Results
The data rate 0.1 Gb/s is achieved for different parameters
communication system under different weather conditions.
The data rate of 0.1 Gb/s is obtained for 650 nm. The data
rate decreases with increasing transmitter divergence angle
and the range, While for increases receiver diameter the
data rate is increasing for the conditions under study. It is
also observed that the data rate have very close behavior
curves when the transmitter divergence angle is increasing
and very different behavior curves for increasing range.
To study the signal to noise ratio characteristics under
different weather conditions, we analyzed it based on the
receiver signal power of the AVD. When the receiver
diameter increases the signal to noise ratio is increasing
for the wavelength (650) nm under study. Also can be seen
the signal to noise ratio have very close behavior curves in
small and medium distance but different for high distance.
So, the heavy fog has attenuation effect much greater than
the other weather conditions.
V.CONCLUSION
In this paper, our main focus on the weather effect that the
most important parameter which is affecting the
performance of FSO links. Simulation was carried out for
the receiver signal, data rate and the signal to noise ratio in
the clear, haze and fog conditions. From the simulation
results, we concluded that the data rate decreases with
increasing divergence angle and link distance for the
parameters under study. It is observed that the clear and
haze weather condition have low attenuation as compared
with the fog attenuation.
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5. 51 ICRTEDC -2014
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