A010210109

IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE)
e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 2 Ver. I (Mar – Apr. 2015), PP 01-09
www.iosrjournals.org
DOI: 10.9790/1676-10210109 www.iosrjournals.org 1 | Page
Characteristics of Optical Channel for Underwater Optical
Wireless Communication System
Mazin Ali A. Ali
The University of Mustansiriyah / College of Science / Physics Department
Abstract: To understand an underwater optical communication, it is necessary to describe the optical path
of the light underwater and the refractive index of water. In the present work the receiver signal power
underwater has been calculated using free space optical wireless communication formula. This procedure
has been used to calculate the link margin, data rate as a function of the distance link. Types of water have
been taken in the consideration. Our results show that the signal to noise ratio most parameter in
communication systems in the distance link, particularly for the refractive index n ≤ 1.4. The data rate,
signal to noise ratio decreases as the refractive index of water and distance link increases.
Keywords: Refractive index of water, optical path, underwater communication, data rate, signal to noise
ratio.
I. Introduction
Wireless optical communications underwater is enjoying a renewed interest from researchers due
to the wide advances in laser sources and receivers, digital communications, and signal processing.
Underwater free space optics (uFSO) fulfills several niche applications for wireless communications in
ocean waters. While RF communications have become ubiquitous in our everyday lives above water, the RF
portion of the electromagnetic spectrum exhibits high attenuation in seawater. Acoustics on the other hand
have long enjoyed success for detection and communication underwater, given their ability to propagate
long distances underwater (>km). However, for high speed data transfer (>Mbps), acoustics are at a
disadvantage, as it is well known that acoustic energy exhibits increasing attenuation with increasing
frequency. Supported by enormous growth in the telecommunications industry over the past few decades,
optical techniques are garnering serious consideration for underwater communications due to higher data
rates they may provide. Additionally, as we will learn, the blue/green portion of the visible spectrum
exhibits minimal absorption in seawater. Still, scattering of light by organic and inorganic particulates in
ocean water can cause significant spatial and temporal dispersion, which may have a measurable impact on
link range and available bandwidth [1, 2]. The attenuation of light by water is caused by two independent
mechanisms, scattering and absorption, which affect the amplitude, phase and arrival angle of the light
beam. Scattering is a random process that changes the directions of individual photons without altering their
properties, while absorption is a thermodynamically irreversible process that transforms the energy of
photon into thermal energy. This is the major absorption mechanism in the sea and varies considerably with
wavelength [3].
II. Underwater Optical Wireless Communication Channel
Light pulses propagating in aquatic medium suffer from attenuation and broadening in the spatial,
spatial, angular, temporal, and polarization domains. The attenuation and broadening are wavelength
dependent and result from absorption and multi scattering of light by water molecules and by marine
hydrosols (mineral and organic matter) [4]. The extinction coefficient c(λ) of the aquatic medium is
governed by the absorption and scattering coefficients α(λ) and β(λ), respectively, and we have[5]
)()()(  c (1)
The scattering due to pure seawater is somewhat limited in magnitude. Fig. 1 shows that the scatter
is limited in nature for wavelengths above 400nm, and is much smaller than the absorption coefficient for
the same wavelengths [6]

Characteristics of Optical Channel for Underwater Optical Wireless Communication System
Fig. 1 Scattering coefficient compared to absorption coefficient of pure seawater vs. wavelength
2.1 Absorption Model
The spectral absorption coefficient, α(λ), which is the change in the beam of light due to the
absorption by the medium (or things in the medium) per meter of path length [7]. The total absorption is a
linear combination of the absorption properties of pure seawater, chlorophyll absorption as a function of
wavelength and concentration, and the two components colored dissolved organic materials (CDOM). The
splitting of the yellow substance into two components allows the model to be universal for all biologically
stable waters and it will permit models in the future to include the effects of fluorescence in a more
consistent manner. The absorption coefficient α (λ) is given by:
)()()()()(  hfclw  (2)
Where αw (λ) is the absorption coefficient of water as a function of wavelength (m-1
), αcl (λ) is the
absorption chlorophyll acid coefficient as a function of wavelength, αf (λ) is the fulvic acid absorption
coefficient and αh (λ) is the humic acid absorption coefficient both as a function of wavelength. The
absorption coefficient for water types, αw (λ), was interpolated from data from [8] with respect to water
concentration of
0
cw = 1 mg/m3, and water concentrations 0 ≤ wc ≤ 15 mg/m3
. It then became:
0
0
)(
0
)(
wa
cw
cw
ww








  (3)
For pure sea water  0405.0*
0
)(
0
 ww , for clean ocean  114.0*
0
)(
0
 ww for coastal
ocean  179.0*
0
)(
0
 ww for turbid harbor  266.0*
0
)(
0
 ww . As well as the absorption
coefficient for chlorophyll, αcl (λ), was interpolated from data from [9, 10] with respect to a chlorophyll
concentration in
0
cC = 1 mg/m3
and chlorophyll concentrations 0 ≤ Cc ≤ 12 mg/m3
. It then became:
0602.0
0
)(
0
)(









cC
cC
ccl  (4)
For ,0602.0)(
0
 c next, the absorption coefficient of the yellow substance which is broken into two
separate components: humic, αh (λ), and fulvic, αf (λ) acid.
)exp()(
0
)(  hkhChh  (5a)
)exp()(
0
)(  fkfCff  (5b)

Where kh=0.01105/nm,
0
h =18.828 m2
/mg is the specific absorption coefficient of humic acid, the first
component of CDOM and kf= 0.0189/nm,
0
f = 35.959 m2
/mg is the specific absorption coefficient of
fulvic acid, the second component of CDOM. Also, Ch and Cf are the concentration of humic acids and
fulvic acids in mg/m3, respectively and can be [9]:

















0
12327.0exp74098.1
cC
cC
cCfC (6a)

















0
12343.0exp19334.0
cC
cC
cChC (6b)
2.2. Scattering Model
This phenomenon is called the spectral beam scattering coefficient, β(λ), which describes the loss
of flux due to the redirection of photons by means of total scattering. The total scattering is a linear
combination of the scattering coefficient of water, βw(λ), scattering from small particles, )(
0
s as a
function of wavelength and concentration, and scattering from large particle, )(
0
l as a function of
wavelength and concentration, is given by [9]:
l
Cls
Csw ).(
0
).(
0
)()(   (7)
The equation for βw(λ) is derived by interpolating the data published by[9] to get:
1
,
322.4
4.0
005826.0)(

 





mw

 (8)
The spectral dependencies for scattering coefficients of small and large particulate matter are given by:
gms /
2
,
7.1
4.0
151302.1)(
0








 (9a)
gml /
2
,
3.0
4.0
3411.0)(
0








 (9b)
Where Cs and Cl are the total concentration of small and large particles in g/m3, respectively given by:
3
/,11631.0exp.01739.0 mg
lC
cC
cCsC
















 (10a)
3
/,03092.0exp.76284.0 mg
lC
cC
cClC
















 (10b)
III. Communication Link Model
There are different parameters important of communications systems such as: the received signal
power, link margin, and data rate. In addition, we performed a signal to noise ratio calculation.
3.1 Receiver Signal Power
We shall consider the situation of optical propagation between points underwater. Consider a laser
transmitting a total power PT at the wavelength 532nm. The signal power received at the communications
detector can be expressed as [11]
rectrans
L
Ldiv
D
transPrecP 


10/.
10.
22
2

 (11)

Where D is the receiver diameter, θ is the divergence angle, γ is the underwater attenuation factor (dB/m),
τT, τR are the transmitter and receiver optical efficiency respectively. The optical path d of a ray of light in
any medium is given [12]
Lnd . (12a)
Where d is the optical path, n is the refractive index of water, and L represents the geometrical optical
distance. So that, eq. (11) can be written as
rectrans
n
d
n
d
div
D
transPrecP 


















.10
.
10.
2
2
2
(12b)
3.2 Link Margin
Another important parameter in the optical communications link analysis is "Link Margin", which
is the ratio of available received power to the receiver power required to achieve a specified BER at a given
data rate. Note that the "required" power at the receiver PREQ (watts) to achieve a given data rate, R
(bits/sec), we can define the link margin LM as [12]:
rectrans
L
LDRhcbNTPLM 


10/
10]
)22
/(
2
[*]/([

 (13)
Where R is a data rate, h is a plank constant and c is the light velocity.
3.3 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 [13]
bNpEL
D
L
rectransTP
R
22
)2/(
210/.
10...




 (14)
Where Ep=hc/λ, is the photon energy at wavelength λ and Nb is the receiver sensitivity (photon/bits) or
(dBm)
3.4 Signal to Noise Ratio (SNR)
The electrical power of the received optical signal is proportional to the mean squared avalanche
photodiode APD current, which can be written as [14]
2
)0(
2
MrecPRAPDi  (15)
and
ch
q
R

0 (16)
where R0 denotes the primary sensitivity of the APD, Prec is the received power, M is the APD gain, η is the
quantum efficiency, q is the electron charge, h is Planck’s constant, c is the speed of light. The noise
contributions
(i.e., the mean-square values of the APD current) are shot noise:
B
x
MrecPRqnoisesig
2
)0(2
2 
 (17)
Surface leakage current noise:
BLqIsurface 2
2
 (18)
multiplied dark current noise:
B
x
MDIqmdark
2
)(2
2
,

 (19)

And Johnson noise:
eqR
TFBkT
johnson
42
 (20)
where ID is the bulk dark current, IL is the surface leakage current, )10()(  x
x
MMF is the excess
noise factor, k is the Boltzmann constant, B is the equivalent noise bandwidth, Req is the equivalent circuit
resistance, FT is the noise figure of the electric circuit, and T is the system temperature. The SNR for the
optical communication system is thus given by
eqRTFBkTBLIqB
x
MDIrecPRq
MrecPR
APDSNR
/42
2
)0(2
2
)0(



 (21)
IV. Simulation results
Simulation by Matlab carried out to show the effect of refractive index of water in underwater
optical wireless communication system (UOWCS). The performance of (UOWC) system can be evaluated
by the receiver signal power, link margin, data rate and signal to noise ratio. We have investigated the high
quality and the best performance of underwater optical wireless communication link systems for different
types of water. The investigating based on the modeling equations analysis and the assumed set of the
operating parameters are shown in Table 1.
Table 1. Proposed operating parameters for underwater optical communications link
Parameters Values
Transmitter optical power 50mw
Transmitter divergence angle 1.5mrad
Transmitter efficiency 0.5
Receiver efficiency 0.5
Optical path 0 ≤ d (m) ≤ 100
Receiver diameter 1cm
Receiver sensitivity -20dBm
Chlorophyll
concentration cc and
water concentration wc
Pure sea water Cc=0.03mg/m3
,
wc=0.035 mg/m3
Clean ocean water Cc=0.4mg/m3
,
wc=0.55 mg/m3
Coastal ocean water Cc=3mg/m3
, wc=4
mg/m3
Turbid harbor water Cc=12mg/m3
,
wc=15 mg/m3
Bulk dark current, ID 0.05 nA
The APD gain 100
The excess noise factor, x 0.5
Electrical band, B 25MHz
Surface leakage current, IL 0.001A
System temperature, T 290K
Noise figure, FT 3dB
Equivalent resistance, Req 50kΩ
So the receiver signal power (dBm) due to the refractive index of water types can be evaluated.
The receiver signal power is achieved in pure sea water, clean ocean water, coastal ocean water and turbid
harbor for wavelength (532) nm at optical path underwater reach to100 m as shown in Fig. 2. The pure and
clean water has very close behavior and it's different about the ocean and turbid. When the refractive index
of water is increasing the receiver signal power decreases, on the other hand, when the refractive index of
water decreasing the received signal power can be reached to long distances.

Fig. 2 Receiver signal power (dBm) as a function of distance link (m)
The link margin for receiver sensitivity-20dBm is achieved for data rate 0.1 Gb/s operating under typical
water conditions for optical path about100 m as shown in Fig. 3. The link margin for water can be reached
to long distance when the refractive index of water decreases, also the pure and clean water have the same
behavior.
The data rate 0.1Gb/s is achieved for refractive index and total attenuation underwater. The data rate of 0.1
Gb/s is obtained at 532 nm for the optical path underwater reaches to100 as shown in Fig. 4. The data rate
0.1 Gb/s can be achieved easily for the other types of waters (pure sea, clean ocean, coastal ocean). Also
note that when the refractive index of water decreasing the data rate can be sent to long distances

Fig. 3 link margin (dB) as a function of distance link (m)
The signal to noise ratio (S/N) is achieved depends on an avalanche photodiode receiver power as
shown in fig. (5); the signal to noise ratio increases with decreasing of refractive index of water for different
water types under study. It is achieved that pure sea, clean ocean water has close values and the same
behavior, as well as the first two types has a higher signal to noise ratio compared to other water types under
the same operating conditions. As well as the signal to noise ratio (S/N) decreasing with increasing distance
link.
Fig. 4 data rate (bits/s) as a function of distance link (m)

Fig. 5- signal to noise ratio (dB) as a function of distance link (m)
V. Conclusion
An underwater wireless optical communications system studying based on free space optical
wireless communications link and by employing the refractive index of water. We are studying the effects
of total attenuation and refractive index on underwater optical communication links. The present work
focuses on the optical path of the light underwater and calculates some parameters such as: the received
signal power, link margin, data rate and signal to noise ratio. The study was carried to the wavelengths 532
nm for four water types pure, clean, coastal and turbid harbor water. It is theoretically found that the
increases the refractive index of water the received signal power, link margin, and data rate is decreasing
under the same conditions. As well as the signal to noise ratio SNR increases with decreasing the refractive
index of water and the optical link. Therefore, it is concluded that the pure and clean water has presented the
highest received signal power, link margin, data rate and signal to noise ratio compared to other water types
under the same operating conditions.
References
[1]. Arnon, S, Barry, J. R., Karagiannidis, G. K., Schober, R., Uysal, M., (2012), Advanced Optical Wireless Communication
Systems', Cambridge University Press.
[2]. Pocela, J., Aguayo, M. C. Otero, P., (2012). Wireless Underwater Communications, Wireless Personal Communications,
64(3), 547-560; Doi: 10. 1007/s11277-012-0600-z.
[3]. Woodward, B., Sari, H., (2008), Underwater Speech Communications with a Modulated Laser, Applied Physics, B. 91,
[4]. Arnon,S., (2010), Underwater Optical Wireless Communication Network, Optical Engineering, vol. 49(1).
[5]. Kedar, D., Arnon, S., (2009), Subsea ultraviolet solar-blind broadband free-space optics communication, Optical Engineering,
vol. 48(4).
[6]. Bouchet, O., (2006), Free-Space Optics: Propagation and Communication, London; Newport Beach, CA.
[7]. Lermusiaux, P. F. J., Chiu, C. S., Gawarkiewicz, G. G., Abbot, P., Robinson, A. R., Miller, R. N., Haley, P. J., Leslie, W. G.,
Majumdar, S. J., Pang, A., Lekien, F., (2006), Quantifying Uncertainties in Ocean Predictions in Oceanography, special issue
on Advances in Computational Oceanography, Paluszkiewicz T., Harper S., Eds., 19(1)1, pp. 92-105.
[8]. Rashed, A. N. Z., Sharshar, H. A., (2011), Performance Evaluation of Short Range Underwater Optical Wireless
Communications for Different Ocean Water Types, , Wireless Personal Communications, , 73(1), pp. 693-708; Doi:
10.1007/s11277-013-1037-8.

[9]. Lermusiaux., P.F.J., (2007), Adaptive Modeling, Adaptive Data Assimilation and Adaptive Sampling, in Physica D, special
issue on Mathematical Issues and Challenges in Data Assimilation for Geophysical Systems: Interdisciplinary Perspectives,
Jones C.K.R.T.,K. Ide K., Eds., 23(3), pp. 172-196.
[10]. F. M. Davidson, F. M., Bucaille, S., Gilbreath., G. C., et al., (2004), Measurements of Intensity Scintillations and Probability
Density Functions of Retroreflected Broadband 980-nm Laser Light in Atmospheric Turbulence, Optical Engineering, 43( 2),
pp. 639-645.
[11]. K. S. Shaik., K.S., (1988), Atmospheric Propagation Effects Relevant to Optical Communication, TDA Progress Report, pp:
180-188.
[12]. Jenkins, F. A., White,H. E., (2001), Fundamentals of Optics, McGraw-Hill Higher Education, 4th
edition.
[13]. Majumdar, A. K., (2005), Free-Space Laser Communication Performance in the Atmospheric Channel, Journal of Optical and
Fiber Communications Reports, 2(4), pp: 345-396.
[14]. Keiser, G., (2000), Optical Fiber Communications, McGraw-Hill Higher Education, 3rd
edition.

A010210109

More Related Content

What's hot

Viewers also liked

Similar to A010210109

More from IOSR Journals

Recently uploaded

A010210109