Abstract—Underwater wireless communication (UWC) has become a significant technique that is used to investigate the underwater environment. It is also noteworthy that the collected data from underwater has to transmit to inland data fusion centers for further investigation and operating instructions need to transmit from the inland center to underwater autonomous vehicles (UAVs) to operate as per the real-time requirements. Therefore, a hybrid terrestrial and UWC setup is required in most of the underwater military and commercial applications

1. A Hybrid RF/FSO and Underwater VLC
Cooperative Relay Communication System
Mohammad Furqan Ali∗, Tharindu D. Ponnimbaduge Perera∗,Dushantha Nalin K. Jayakody∗† and Sahil Garg∗,
∗School of Computer Science and Robotics, National Research Tomsk Polytechnic University, RUSSIA
†School of Postgraduate Studies, Sri Lanka Technological Campus, SRI LANKA
‡Department, Ecole de Technologie Superieure, Universite du Quebec, Montreal, Canada
Email:[ali89, ponnimbaduage, nalin, stefanpnc]@tpu.ru, morapitiya18@gmail.com, sahil.garg@ieee.org
Abstract—Underwater wireless communication (UWC) has
become a significant technique that is used to investigate the
underwater environment. It is also noteworthy that the collected
data from underwater has to transmit to inland data fusion
centers for further investigation and operating instructions need
to transmit from the inland center to underwater autonomous
vehicles (UAVs) to operate as per the real-time requirements.
Therefore, a hybrid terrestrial and UWC setup is required in
most of the underwater military and commercial applications.
In this paper, a dual-hop hybrid terrestrial and underwater co-
operative communication system has been investigated. A floating
buoy works as a relay node to assist information transmission
and visible light communication (VLC) is used for UWC. Free-
space optics (FSO) and RF are used as potential candidates for
terrestrial communication link of the proposed system. Numerical
results show that FSO-VLC combination has the superior bit-
error-rate (BER) performance with compare to RF-VLC setup
in higher SNR conditions regardless of the water mediums.
Index Terms—Cooperative communication, Free space optical
communication (FSO), Underwater wireless communication
(UWC), Visible light communication (VLC).
I. INTRODUCTION
Earth is a water planet, occupied more than 70% of its
surface by water and 95% of such water areas are still
unexplored to envisage underwater phenomenal activities. Due
to an evolutionary revolution and growing interest of human
activities in exploring the undersea environment, UWC has
received significant attention from the wireless communication
research community. Various underwater applications have
been introduced in existing open literature such as marine
life, oil and gas rig monitoring systems, water pollution
control systems and early detection warning of earthquakes
and tsunami [1]. Acoustic, optical and radio frequency (RF)
wireless carriers are used as potential candidates for UWC [2].
Optical signaling provides a high bandwidth data rate with low
latency and is particularly appealing for real-time underwater
applications [3]. Visible light as a the most favorable candidate
for the UWC [4]. In addition, visible light communication
(VLC) is relatively cost-effective and easy to deploy in various
underwater applications over a short distance (up to 50 m)
[5]. VLC has been recognized as a promising alternative and
complementary communication technology to data transfer in
various applications. It has gained an attraction as a potential
wireless candidate for signal transmission in underwater en-
vironment. For underwater wireless communication scenario,
It is easy to install in harsh channel conditions and supports
larger bandwidth along with secured communication unlike
RF communication.
Motivated of this paper, and summarizing above mentioned
facts, we are investigating the BER performance comparison
for two different dual-hop hybrid cooperative relay based com-
munication system models in different underwater mediums
along with strong channel conditions. Dual-hop communi-
cation link has been proposed for a fair solution over long
ranges. In both of the system models, the signal broadcasting
from terrestrial base station to underwater based relay through
RF or FSO link whereas the information forwards to the
destination from relay with VLC (common for both system
models) link. Underwater VLC (UVLC) link considered as
under the combined influence of turbulence and pointing error
impairments of water channel. Additionally, VLC technology
does not interfere with RF waves and it is safe to use in various
applications. It has fruitful future prospects, because of popu-
larity of LEDs. Thus, VLC has shown a potential acceptability
for next generation communication systems for revolution in
the communication era. UVLC has been investigated in most
of the recent existing works on UWC systems [6]–[9]. The
authors in [6], have investigated performance analysis of a
vertical underwater VLC link between the two corresponding
points. Moreover, unlike the horizontal underwater VLC links,
the authors have modeled vertical VLC link with varying
turbulence strength based on the depth-dependant temperature
and salinity. The performance analysis of vertical underwater
VLC link considering the strong water turbulence conditions
is investigated in [7]. The authors have used Gamma-Gamma
probability density function to model strong turbulence in
underwater VLC and formulated a closed-form bit error rate
(BER) expression in underwater based destination. The per-
formance of vertical underwater VLC links, which are subject
to both strong turbulence and pointing errors is investigated in
[8]. In [9], the authors have carried out a detailed underwater
VLC channel modeling and characterization study taking into
account the presence of human and man-made objects. It
is shown that even in complete line-of-site (LOS) blockage,
transmission can take place due to scattering without being

2. affected by the increase in path-loss.
Dual-hop communication has been used to improve system
performance for long-range communication links. In order
to operate and control unmanned autonomous underwater
vehicle (UAUV) along with the real-time data transmission
in underwater, a high demand of dual-hop cooperative hybrid
terrestrial and underwater communication system is required
for numerous underwater applications [10]. A dual-hop un-
derwater RF and underwater wireless optical communication
(UWO) system has been investigated in [10] [11]. In [10], the
authors have examined the secrecy performance of a dual-hop
mixed RF/UWO system and formulated the average secrecy
capacity metrics for the fixed-gain relaying scheme. The more
similar work has been carried out and investigated on secrecy
performance and outage probability of a dual-hop mixed
RF-UWO system in [11]. The authors have shown that the
secrecy performance of the system improves significantly by
increasing the parameters of the legitimate link. Recently, an
efficient alternative signal transmission technique, free-space
optical (FSO) communication over lognormal turbulence chan-
nel conditions has been widely advocated in open literature
[12] [13]. Thus, mixed RF/FSO systems have been extensively
investigated in open literature [14]. In most recent work, based
on wireless energy harvested relay underwater cooperative
communication technique investigated in [15]. The authors
in [15], proposed the simultaneous wireless information and
power transmission (SWIPT) technique with the underwater
based relay. In [16], the authors have conducted a performance
analysis of dual-hop mixed RF/FSO system, where both RF
and FSO links are subjected to Nakagami-m and Gamma-
Gamma fading channels, respectively.
However, to the best of our knowledge, there is no per-
formance evaluation has been conducted between RF-VLC
and FSO-VLC dual-hop hybrid terrestrial and underwater
cooperative communication systems in the open literature.
Thus, in this paper, we investigate the performance differences
of RF-VLC and FSO-VLC dual-hop communications systems
by analyzing the BER performance at the underwater AUV
in different water. We model underwater VLC channel sub-
ject to both turbulence and pointing errors. For the system
performance analysis and comparison both of mixed dual-
hop communication, we have used an identical VLC link and
a similar distance between terrestrial base station to floating
buoy (relay node) in both RF-VLC and FSO-VLC cooperative
communication systems.
The remainder of the paper is organized into five sections. In
Section II, we obtain Bit-error-rate (BER) performance from
our simulation results, in RF and FSO links in each system
model proposed by Fig.1. In Section III, BER performance
calculated by implementing of on-off-keying modulation tech-
nique. In Section IV, the simulation results are presented to
identify of system performance of proposed models. Finally,
Section V concludes the paper.
II. SYSTEM MODEL
In this paper, we are considering the two dual-hop hybrid
terrestrial and underwater cooperative communication systems
as shown in Fig.1. The proposed systems are consists of one
inland base station (s), floating buoy as a relay node (r) and
a remotely operated AUV as the destination node (d) located
in underwater. Inland base station transmits information to the
underwater AUV via floating buoy using decode-and-forward
(DF) relay protocol. It is assumed that all three nodes are
equipped with single antenna and work in the half-duplex
mode. Except for the terrestrial communication link, all other
parameters of the systems are identical to each other. System
model-1 (SM1) uses RF in terrestrial communication link
while the other system model-2 (SM2) used FSO link. RF link
in SM1 is experienced Rayleigh fast fading and corresponding
channel coefficient is denoted as hRF . The channel power gain
represents as h2
RF , which follows the exponential distribution.
We use hF SO = hlhpht to denote the channel coefficient
experience in FSO terrestrial link in SM2, where hl denotes
the path loss, hp denotes the pointing errors between the
source (transmitter) and the relay as a signal receiver and
atmospheric turbulence is assigned by the ht. Note that the hl
is deterministic, and ht and hp are random variables follow-
ing Gaussian and Gamma-Gamma probabilistic distributions
respectively [17]. Detailed optical channel model of FSO link
is provided in Section III. An underwater VLC communication
link is common for both systems and the channel coefficient
is explained in detail in subsection D. The additive white
Gaussian noise (AWGN) with zero mean and variance σ2
xy
is used to model noise between communication nodes, where
x, y ∈ {s, r, d}. Similarly, the distance apart communication
nodes are represented as dα
xy, where α annotates the pathloss
exponent.
Fig. 1. A proposed system model of dual-hop hybrid cooperative RFVLC
underwater wireless communication, where source communicates with des-
tination through relay in different communication link along with different
channel conditions

3. A. SM1-Source to Relay (s-r) Communication RF Link
In SM1, the RF link is used for the communication between
the source and the relay node. The received signal at the
floating buoy can be written as,
yRF =
s
Ps
dα
sr
hRF x + nsr, (1)
where Ps is the signal transmission power of the inland base
station, x denotes the BPSK modulated information symbol,
dsr is the distance between the inland base station and floating
buoy and nsr assigns as AWGN noise experience by the RF
link. Thus, signal-to-noise ration (SNR) at the surface buoy
can be expressed as,
γRF =
Psd−α
sr h2
RF
σ2
sr
, (2)
where σ2
sr denoted as the noise variance of the AWGN. The
surface buoy decodes the received information signal and
forward the regenerated information signal to the AUV through
VLC link in the underwater environment.
B. SM2-Source to Relay (s-r) FSO Communication Link
In SM2, the inland base station uses FSO link to send
information to the surface buoy. In FSO communication link,
signal propagation depends on geometrical constraints of the
system, such as electrical to optical conversion efficiency (η1)
and photo-detector responsivity (r1) of photo-diode. Thus, At
the floating buoy, the received signal through FSO link can be
calculated as,
yF SO =
p
Psη1r1hF SOx + nsr, (3)
The SNR of the FSO link at the buoy can be expressed as
γF SO =
Psη1
2
r1
2
h2
F SO
σ2
rs
. (4)
III. OPTICAL CHANNEL MODEL
In FSO signal propagation, the channel is impaired by
channel fading. Thus, FSO channel hF SO is modeled by
pathloss (hl), considering the atmospheric absorption and
scattering cause attenuation, atmospheric turbulence (ht) and
misalignment also known as pointing errors (hp). The normal-
ized channel coefficient of the FSO link can be described as
in [17],
hF SO = hlhpht. (5)
A. Atmospheric Attenuation
Optical signal affected by attenuation is also known as the
extinction coefficient, which includes atmospheric absorption
and scattering. The attenuation coefficient considered as a
fixed factor of which has no randomness exists in its behavior.
The attenuation coefficient depends on the physical constraints
and distribution of scattering signals and the wavelength
utilized [17]. Thus, adhering to Beer-Lambert law, the path
loss of the FSO link can be given as,
hl(λ, L) =
P(λ, L)
P(λ, 0)
= exp{−c1(λ)L}, (6)
where the distance apart inland base station and the buoy is
denoted by L, P(λ, L) is the transmitted signal power for the
given distance L. However, c1(λ) is an extinction coefficient
which is the total sum of optical absorption and scattering by
the atmospheric conditions.
B. Turbulence Channel Fading Model
In existing works of literature has many statistical channel
models for weak turbulence intensity fluctuation probability
density function (PDF) are experimentally modeled as the log-
normal distribution [18]. In recent work with related FSO com-
munication, a Gamma-Gamma probability distribution was
used to model atmospheric turbulence related channel fading.
According to [17], the PDF of atmospheric turbulence ht is
given as,
fht(ht) = 2
(αβ)
(α+β)
2
Γ(α)Γ(β)
(ht)
(α+β)
2 −1
Kα−β(2
p
αβht), (7)
where the term K(α−β)(·) is defined as the modified Bessel
function of the second kind, α and β are defined as the large
scale variance and small scale variance, respectively [17].
C. Pointing Error
The pointing error is an another parameter of fading in
line of sight (LOS) optical communications. In the LOS,
FSO communication, pointing accuracy is a crucial factor in
determining system performance and reliability. The pointing
error may occur due to the flexible pace of the transmitter and
receiver or due to wind loads, thermal expansions, etc. The
pointing error fading coefficient can be written as [17],
hp = Aoexp
−
2a2
w2
zeq
, (8)
where a denotes the random radial displacement at the signal
receiver and A0 is the fraction of the collected power at the
displacement randomness of a = 0. The displacement of
randomness (a) depends on the horizontal and vertical move-
ments of signal receiver and wzeq represents the equivalent
beamwidth.
D. Relay Buoy to AUV VLC Link
Buoy to AUV communication link is modeled using vertical
VLC, where relay buoy forwards the information received
from the inland base station to the AUV. It is also noteworthy
that the VLC link is common in both SM1 and SM2. The
buoy is assumed to be placed at a fixed location on the sea
surface with a laser diode (LD) directing vertically towards
the stationary AUV. Thus, the received signal at the AUV can
be expressed as,
yV LC =
p
Prη2r2hV LCx̄ + nrd, (9)

4. where Pr the relay buoy’s transmission signal power, η2 is
electrical to optical conversion efficiency at the receiver and
r2 is the photo-detector responsivity. The random attenuation
propagation channel in VLC link is modeled by considering
three factors, i.e., path loss (h0
l) , atmospheric turbulence (h0
t)
and pointing errors (h0
p) [8]. Thus, underwater VLC channel
can be expressed as,
hV LC = (h0
l)(h0
t)(h0
p). (10)
E. VLC Underwater Attenuation Model
The path loss in the VLC link depends on the attenuation
coefficient c(λ). The attenuation coefficient is the sum of total
absorption a(λ) and scattering b(λ) of photons in underwater
environment. Thus, the underwater attenuation coefficient can
be expressed as in [19],
c(λ) = a(λ) + b(λ), (11)
The typical values of a(λ) and b(λ) in different types of water
medium are given in Table I. Thus, by considering (11), the
pathloss of the underwater VLC link can be expressed as [20],
h0
l = e−c(λ)dt
, (12)
where dt is the vertical LOS distance between relay buoy and
the underwater based AUV.
Description of water for
UWC
a(λ) b(λ) c(λ)
Pure sea water 0.053 0.003 0.056
Clear Ocean water 0.069 0.08 0.15
Coastal Ocean water 0.088 0.216 0.305
Turbid Harbor water 0.295 1.875 2.17
TABLE I
THE VALUES OF ABSORPTION, SCATTERING AND ATTENUATION
COEFFICIENTS IN DIFFERENT WATER MEDIUMS [21]
F. Underwater VLC Turbulence Channel Model
We consider the turbulence model proposed in [6]. In this
turbulence model, the authors have modeled the VLC under-
water vertical channel into successive k number of layers and
the fading coefficient associated with each distinct layers. The
fading coefficient is modeled as independent but not identically
distributed Gamma-Gamma random variables. Thus, Gamma-
Gamma pdf for the kth
layer can be given as [8],
fhtk
(h0
tk
) = 2
(αkβk)
(αk+βk)
2
Γ(αk)Γ(βk)
(h0
tk
)
(αk+βk)
2 −1
Kαk−βk
(2
p
αkβkhtk
),
(13)
where Γ(·) is the Gamma function and K(αk−βk)(·) defined
as the modified Bessel function of the second kind. The
consideration of kth
layers in the underwater environment for
scattering process, the large scale cells and small scale cells
are defined by αk and βk respectively, which can be written
as, respectively
αk =



exp




0.49σ2
h0
tk
1 + 1.11σ
12
5
h0
tk
7
6



 − 1




−1
, (14)
βk =



exp




0.51σ2
h0
tk
1 + 0.69σ
12
5
h0
tk
5
6



 − 1




−1
. (15)
where σ2
h0
tk
represent the scintillation index for plane wave
model known as Rytov variance [7].
G. Pointing Error In Underwater VLC Link
Pointing error is also one another source of fading in un-
derwater VLC link. Pointing error occurs due to misalignment
phenomena and tilting position of buoy’s transmitter and/or
AUV’s receiver due to ocean waves and currents. Thus, the
pointing error can be represented as [8],
h0
p = Aoexp
−
2R2
w0
zeq
2
, (16)
where Ao denoted as the fraction of the collected power at
the value of R = 0 and w0
zeq is the equivalent beam width of
underwater VLC link. The beam-width of the VLC link can
be written as w0
zeq = 2σsζ, where ζ is the ratio between of
equivalent beam radius which is the pointing error displace-
ment standard deviation denoted by the σs. The random radial
displacement R at the AUV’s receiver end, calculated by R
=
q
R2
x + R2
y. The displacement along horizontal and vertical
axes is defined by the fraction R2
x and R2
y respectively.
IV. BER PERFORMANCE AT THE DESTINATION
The proposed both of the system models, an underwater
VLC link is in common and consider as vertical link. The sig-
nal transmits to an underwater based AUV through transmis-
sion relay over the different channel conditions. Analytically,
in RF-VLC mixed communication link the average SNR at the
destination can be calculated as [10] [22],
γRF −V LC =
γRF γV LC
γV LC + 1
, (17)
For the FSO-VLC mixed communication the average SNR can
be calculated as
γF SO−V LC =
γF SOγV LC
γV LC + 1
, (18)
where γRF −V LC and γF SO−V LC the average SNR at the
underwater based destination, respectively. Based on (17) and
(18), a single-carrier system with simple modulation technique
as on-off keying (OOK) can be used [6]. The BER for OOK
over real AWGN channel mentioned in [23]. Based on (17), the
BER performance at the destination in SM1 can be calculated
as,
BERd =
Q
r
γRF −V LC
2
, (19)

5. -5 0 5 10 15 20 25
SNR, dB
10
-4
10
-3
10
-2
10
-1
10
0
Bit
Error
Rate
FSO Link
RF Link
Fig. 2. Comparison of BER performance at relay enabled RF and FSO link
Similarly, Based on (18), the BER performance at the desti-
nation in SM2 can be calculated as,
BER0
d =
Q
r
γF SO−V LC
2
. (20)
V. NUMERICAL RESULTS
In this section, we present the simulation results to inves-
tigate the BER performance of SM1 and SM2 at the AUV.
We considered the targeting destination located vertically in
underwater environment with respect to buoy. Unless other-
wise status, we use receiver aperture diameter of Dr = 15cm,
full width transmitter beam divergence angle θ = 6◦
, distance
between inland base station and buoy dsr = 200m and vertical
depth AUV from sea surface dt = 40m. The attenuation
coefficient value of 0.43 for clear air used in FSO link [24].
The corresponding values of pointing error parameters depend
on the fraction of the collected power Ao and equivalent
beam width ζ mentioned in [8]. In Fig.2, we present the
BER performance comparison between terrestrial RF and
FSO communication links at the buoy in both of proposed
system models. As we can clearly see from the Fig.2, FSO
link shows superior BER performance in higher transmitting
SNR conditions, while RF shows superior performance in
lower SNR conditions. However, in transmit SNR 17dB, both
the FSO and RF link show the similar BER performance.
Although, the achievable rate (AR) is out of scope of this
work, the comparison shows the superior BER performance
of the dual-hop hybrid underwater wireless communication.
In Fig.3, we compare the BER performance of SM1 and
SM2 at the AUV in different seawater types, i.e., pure, clear
and coastal water. It can clearly see from the Fig.3 that SM1
(RF-VLC) combination shows better BER performance com-
pare to SM2 (FSO-VLC) in lower SNR conditions regardless
-5 0 5 10 15 20 25
SNR, dB
10
-4
10
-3
10
-2
10
-1
10
0
Bit
Error
Rate
(SM1) RF/VLC in Pure Sea Water
(SM1) RF/VLC in Clear Sea Water
(SM1) RF/VLC in Coastal Sea Water
(SM2) FSO/VLC in Pure Sea Water
(SM2) FSO/VLC in Clear Sea Water
(SM2) FSO/VLC in Coastal Sea Water
Fig. 3. BER performance comparison of RF/VLC and FSO/VLC cooperative
communication in different water mediums
of the water type. However, SM2 (FSO-VLC) shows superior
BER performance in higher SNR, in all mentioned seawater
types. The best BER performance achieved in Fig.3 owns by
the SM2 (FSO-VLC) in pure, clear and coastal seawater. In
addition, Fig.3 proves the results obtained in Fig.2 showing
the similar pattern in BER performance.
In Fig.4, we present FSO and VLC pointing error effect
on the BER performance at the AUV in SM2 (FSO-VLC).
We assumed that both FSO and VLC link experience a
similar pointing error in this simulation. We use different
displacement standard deviation values as presented in Fig.4
to model pointing error. Corresponding pointing error values
are illustrated in the legends of the Fig.4. It can clearly
observed from Fig.4 that the effect on BER performance when
σs = 0.1 is negligible. However, as expected the effect on BER
performance is increased with the increase in displacement
standard deviation. It is also can be seen from the Fig.4 that the
BER performance curve’s slope is relatively has a low value
in higher σs conditions as compare to the lower σs values.
VI. CONCLUSION
In this paper, we investigate the BER performance of hybrid
terrestrial and underwater cooperative communication under
two different setups, where one setup consists of RF terrestrial
link and VLC underwater link while the other use FSO for the
terrestrial link. The floating buoy has been used as a relay to
assist information transmission between an inland base station
and underwater based AUV. Then we have compared the BER
performance at the relay buoy and the AUV to identify the
performance difference between the proposed two cooperative
system set-ups. Simulation results have shown that the FSO-
VLC combination has the superior BER performance in higher
transmitted SNR condition compare to RF-VLC cooperative

6. -5 0 5 10 15 20 25
SNR, dB
10
-4
10
-3
10
-2
10
-1
10
0
Bit
Error
Rate
Fig. 4. FSO and VLC Pointing error effect on BER performance at the AUV
in SM2(FSO/VLC).
setup. In addition, pointing error effect on BER performance
of the FSO-VLC setup also investigated.
VII. ACKNOWLEDGEMENT
This work was funded, in part, by the Scheme for Promotion
of Academic and Research Collaboration (SPARC), Ministry
of Human Resource Development, India under the No. P145,
in part, by the Russian Federation State Project Science, Grant
No. 8.13264.2018/8.9 and by the framework of Competitive-
ness Enhancement Program of the National Research Tomsk
Polytechnic University, in part, by the Academy of Finland
Grant No. 325692 and, in part, by the international cooperation
project of Sri Lanka Technological Campus, Sri Lanka and
Tomsk Polytechnic University, No. RRSG/19/5008 and COST
IRACON grant No. CA15104.
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