Underwater Optical Communications: A Brief Overview and ...

Eng. Sci., 2021, 16, 146–186

146 | Eng. Sci., 2021, 16, 146-186 © Engineered Science Publisher LLC 2021

Engineered Science

DOI: https://dx.doi.org/10.30919/es8d574

Underwater Optical Communications: A Brief Overview and Recent Developments

Saleha Al-Zhrani,1, 2 Nada M. Bedaiwi,1, 3 Intesar F El-Ramley,4 Abeer Z. Barasheed,1 Ali Abduldaiem,1, 5 Yas Al-Hadeethi1, 6,* and

Ahmad Umar7, 8

Abstract

Even though most of the Earth's area is sheltered by the hydrosphere, the underwater world is nonetheless a challenging puzzle that has drawn the attention of scientists and researchers around the globe. Numerous theoretical and experimental research has been conducted to attain a safe and effective means of communication. This is crucial to facilitate the implementation of critical industrial, military and security applications and to guarantee the management of marine resources sustainably. Underwater communication technologies have come a long way as they have been implemented either utilizing wired and wireless techniques, through employing acoustic waves or electromagnetic waves (in the radio-frequency spectrum or the optical spectrum). Even though acoustic communication realizes long communication ranges in Km, its limited data rate, its low speed, and its undesirable impact on the aquatic environment have all led to the realization of electromagnetic waves-based communication. Electromagnetic waves offer a high data rate and high-speed communication. Moreover, underwater radio frequency communications maintain a smooth transition between water and air, and they are unaffected by the turbidity properties of water. However, they come at a huge cost. Intriguingly, wireless communications in the optical spectrum have outperformed all the above techniques. This is owing to its high bandwidth and low cost. For that reason, we focus this review on the different facets of the underwater optical wireless communications (UOWC) field, where we present an overview of the most important communication techniques and highlight their drawbacks and advantages. We also review the most basic physical processes that influence the light propagation and modulation underwater along with the coding techniques. We then discuss the link configurations and the system design, and we provide a summary of the most prominent studies from 1992 to the present.

Keywords: Optical communications; Link configurations; Communication security; Light propagation; Modulation; LED.

Received: 22 August 2021; Accepted: 14 November 2021.

Article type: Review article.

1. Introduction

Even though the ocean covers most of our planet, there is

much about the deep sea that remains a mystery. Through

ocean exploration, we can monitor all important aspects of

underwater components such as seafloor, deep-sea and ocean

oil pipelines, underwater zoological life, surveillance of

unmanned systems and navigation. We can also collect data

and information about climate change.[1] This information

helps us ensure that ocean resources are managed sustainably

and help us plan to prevent potential environmental disasters.

Therefore, achieving an effective underwater communication

method is an urgent need to perform many critical industrial,

military and scientific applications.[2] Ocean exploration

technologies have come a long way. Many communication

technologies have been developed for underwater applications,

such as wired and wireless systems. These systems have been

realized through different approaches: acoustic waves,

electromagnetic waves (either by using radio-frequency waves

or optical waves) or hybrid systems.[3] Underwater acoustic

communication technology is largely mature and achieves

communication over distances in Km, but it suffers from low

speed and low data rate due to the limited bandwidth. It also

negatively affects the water’s environment. In addition, it is

strongly affected by the characteristics of the water channel,

such as the water’s turbidity and salinity, which make its

1 Department of Physics, Faculty of Sciences, King Abdulaziz

University, Jeddah-21589, Kingdom of Saudi Arabia. 2 Physics Department, Umm Al-Qura University, Al-Qunfudhah

University College, Al-Qunfudhah 21912, Kingdom of Saudi Arabia. 3 Department of Physics, University of Tabuk, Duba University

College, Tabuk-71491, Kingdom of Saudi Arabia. 4 INToo Solutions, 202-6940 East Blvd, Vancouver, BC, V6M 3V5.

Engineered Science Review article

performance weak. Radiofrequency communication is

characterized by its high speed compared to sound waves.

Moreover, radiofrequency waves is not affected by the

characteristics of the water channel; however, they are affected

by the electrical conductivity of the water. They are also bulky,

expensive, and achieve very short communication ranges.

Optical wireless communication (OWC) is a transmission

system of data through an optical carrier, that is ultraviolet

(UV), visible, or infrared, in an unguided propagation medium.

The least attenuated region in the visible spectrum is in the

range between 450–550 nm. Underwater Optical Wireless

Communications (UOWC) are characterized by high data rate,

low cost, high speed, and safety. However, UOWC suffers

from challenges related to the water channel and its modelling

method in a way that makes this method mature and which

causes it to achieve channel models suitable for different water

environments. So far, we have not found a model that fully

covers and addresses the challenges of the underwater channel.

However, UOWC outperformed all methods, through the

above-mentioned features. Aside from the traditional optical,

acoustic and electromagnetic systems, magnetic induction (MI)

communication, as a full of promise substitutional, has drawn

considerable awareness newly.[4] This is attributed to its

inherent excellent features in anticipated channel responses,

imperceptible propagation delay, and its competing energy

consumption.[4-6] Accordingly, currently, there is a wide

interest in research on underwater MI communications.

Furthermore, the progression of antenna design from

traditional single-directional to state-of-the-art multi-

directional MI antennas justifies the wide interest in this

currently hot topic of research. There is also much research

interest on the currently available approaches towards

broadening or reutilizing the accessible bands of frequency to

increase the underwater MI channel capacity.[4]

The major goal of this review is to learn about the main

characteristics and current features of UOWC. Therefore, this

paper covers the following aspects:

• An overview of possible UWC techniques as well as

current published literature.

• A summarized explanation of acoustic and

electromagnetic communication approaches is as well

provided to assist readers in better comprehending how UWC

operates.

• The review also discusses other approaches which

increase the efficacy of UWC systems, like hybrid acousto-

optic systems.

• The optical properties of water are presented and the

comparison in the definition of inherent and apparent optical

properties for various water types is discussed too.

• Furthermore, this study focuses on displaying the major

factors that affect the UOWC as well as the different link

configuration and modulation techniques in UOWC systems.

• The system design and channel coding are also reviewed.

• This survey gives a summary of the different UOWC

systems that are present until 2021, including a description of

their system parameters.

• Conclusions, as well as future prospects, were presented.

(Fig. 1) depicts a chart summarizing the key topics discussed

in this paper.

2. Approaches of underwater communication

The main reasons for the difficulty in underwater

communication (UC) are the physical properties of the

medium. Herein, we provide the main approaches of UC.[7]

2.1. Wired communication

The cable connected directly to the device's platform is one of

the methods of communication. The most common type of this

kind of communication system is a remotely operated vehicle

(ROV). Direct control is allowed by supplying the vehicle

with power via cable and giving the operator real-time video

feedback. The user is allowed to control and collect data in

real time due to the direct connection of the cable. One of the

main advantages of utilizing a cable connection system is to

achieve a much larger power budget by at the same time

delivering power via the same cable.[7] There are many

disadvantages to utilizing the cable connection method. For

instance, it is difficult to maintain large lengths of wires.

Their deployment requires a high cost, and the space that can

be accessed is limited as it depends on the length of the

available cable. Also, due to the difficult water environment,

cables may break or become tangled in rough seas.[7]

2.2. Wireless communication

Nowadays, underwater wireless communications (UWCs) are

realized through communication systems based on acoustic

waves, and electromagnetic waves (radiofrequency waves

(RF), and optical waves)[8]

5 Physics Department, Faculty of Science, Zagazig University,

Zagazig, Egypt. 6 Lithography in Devices Fabrication and Development Research

Group, Deanship of Scientific Research, King Abdulaziz University,

Jeddah-21589, Kingdom of Saudi Arabia. 7 Department of Chemistry, Faculty of Science and Arts, Najran

University, Najran-11001, Kingdom of Saudi Arabia, email:

ahmadumar786@gmail.com. 8 Promising Centre for Sensors and Electronic Devices (PCSED),

Najran, University, Najran-11001, Kingdom of Saudi Arabia.

*Email: yalhadeethi@kau.edu.sa (Y. Alhadeethi)

Review article Engineered Science

Fig. 1 A chart summarizing the important topics in UOWC.

2.2.1. Acoustic communications

Underwater acoustic communication, which is considered as

the utmost popular method in underwater wireless

communication, goes back to 1490[9] when Leonardo da Vinci

proposed that with the use of acoustic means; ships, vessels,

and all sorts of boats are detected from a distance. He used a

tube inserted into the water to detect vessels by ear.

Underwater acoustic method applications continued to be used

for a long time until the late 1800s. Attributed to the inevitable

need for communications during both the first world war and

the second world war, the underwater acoustic communication

system achieved the desired feasibility and thus became a

famous technology, as it was applied to almost all aspects of

underwater wireless sensor networks (UWSNs).[10]

The first underwater acoustic link device was created in the

USA utilizing single sideband (SSB) suppressed carrier

amplitude modulation, which has a carrier frequency range

between 8 and 15 kHz, with a basic voice band and pulse

shaping filters.[11] As a result, the received signal was of bad

quality, necessitating the human ear's and brain's ability to

recognize and comprehend warped speech. A significant

enhancement in data rate and the functional range was noticed

with progress in digital data transmission in 1960.[12]

Productivity was enhanced using multi-track compensation

approaches.[13] To provide more effective underwater acoustic

communication, many investigations were conducted and

eventually led to the development of advanced methods for

channel estimation and various algorithmic designs over a

wide period.[14-18] In 1995, an underwater acoustic wireless

communication (UAWC) system was suggested[19] with a data

rate of 40 kbps. An 8 kbps UAWC system was advanced for a

depth of 20 m and a horizontal distance of 13 km in 1996.[20]

Interestingly, a higher-speed UAWC system was suggested in

2005[21] which achieves a data rate of 125 kbps utilizing a 32

quadrature amplitude modulation technique (QAM) with a

symbol error rate of 10-4. Moreover, another UAWC system

that has a data rate of 60 kbps was proved[22] utilizing a 32

QAM, that can support communications at a depth of 100 m

and for 3 km horizontal distance. To attain large data rates

without the need for complicated calculations, many

researchers used orthogonal frequency division multiplexing

(OFDM) widely in underwater acoustic communications.[23-27]

Alongside the research that has been conducted on UAWC

systems in both the experimental and the theoretical directions,

acoustic modems of different designs, that can be used for

underwater applications, have been marketed and have been

commercially available.[1] Despite the amazing technological

progress, underwater acoustic communication has not

achieved effective communication performance due to various

obstacles. The most important obstacles that limit the effective

communication of underwater acoustic communications are

the absence of any similar types of underwater sound channels,

due to the features of the underwater environment where it is

extra vital and challenging. In other words, the system that

works in one place (for example, shallow water) might not

work in another place (such as the deep ocean).[8] Nowadays,

investigations and research on the physical layer of

underwater acoustic communication have arrived at some

degree of maturity. Many sea experiments have proved such

communication across tens of kilometers or even further

away[20] and transmission rates of up to tens of kilobits per

second or even more.[19,21,22,28,29] The latter represents a

significant development in the early stage of the few tens of

bits per second.[30,31]

Acoustic-based video transmission has also been

exhibited.[29] The most significant virtue of underwater

acoustic communication is its vast contact range, which may

reach tens of kilometers, given the enormous ocean width and

the strong attenuation impact of saltwater on other

transmission channels such as the optical wave and the RF

wave.[32] While UAWC systems are capable of delivering

command and control applications because of the long

transmission range they proved, their data rate is inadequate

for multimedia applications underwater.[8] To reduce the time

and frequency dispersion of the underwater acoustic channels,

a new transmission scheme called the time-reversed non-

orthogonal multiple access (TR-NOMA) was used.[33]

Depending on the time difference of arrival (TDOA), a

localization algorithm for underwater acoustic sensor

networks has been proposed.[34] To solve the problems of the

underwater acoustic channel, several modulation schemes

were discussed and proposed. A scheme was proposed[35] to

solve the problem of redundant energy in unique word

orthogonal frequency division multiplexing (UW-OFDM),

and this scheme showed its superiority in terms of bit error rate.

A scheme called X-transform time-domain synchronous index

modulation (IM) OFDM has been proposed.[36] Several

studies[37-41] have suggested different types of spatial

modulation (SM) and shown an improvement in bit error rate.

Also, to improve the bit error rate of the underwater acoustic

channel and increase energy efficiency, different types of

pseudorandom noise training sequence orthogonal frequency

division multiplexing have been proposed.[42,43] The deep

learning coded index modulation-spread spectrum (DL-CIM-

SS) performance has been evaluated, which was proposed,[44]

over simulation and measured underwater acoustic channels.

The simulation results show the ability of the proposed scheme

to increase the underwater acoustic data rate with significant

energy efficiency improvement and low system bit and symbol

error rate.

Whereas the acoustic approach is the most frequent

approach for obtaining UWC, it does have certain intrinsic

technological limitations. Firstly, the acoustic link

transmission data rate is quite low (within Kbps) because

underwater audio wave frequencies range from tens of hertz

to hundreds of kilohertz.[45] Secondly, because of the slow

transmission speed of the acoustic wave in water (for pure

water it is around 1500 m/s at 20 Celsius), the acoustic link

undergoes extreme contact delay (usually in seconds). It

cannot, therefore, support applications that involve an

exchange of large quantities of data in real-time.[46,47] Thirdly,

acoustic transceivers are normally big, expensive with high

consumption of energy. They are costly for large scale

UWSNs applications.[48] This technique can also have an effect

on life in the sea.[49]

2.2.2 Electromagnetic waves

(a) Radio Frequency communications

Due to the long transmission rate of UAWC systems, they are

useful for control and command applications but are not

appropriate for underwater multimedia applications due to

their limited data rate.[1] Electromagnetic waves are a

considerable faster means of communication.[50]

Electromagnetic waves (EM), in the radio frequency (RF)

range, can achieve high data rate transmission in short

distances so it is a good choice for underwater wireless

communications.[51] Waves having a frequency less than 300

GHz are known as radiofrequency waves.[52] Compared to the

speed of sound travel through water, the speed of radio waves

is much faster (about 2 × 105 times) as it travels in water at a

speed of 2.2 5 × 108 ms-1 (assuming water refractive index =

1.3) while radio waves travel in a vacuum at the speed of light

~3× 108 ms-1. Electromagnetic waves are affected by several

factors such as temperature, salinity and depth, and this leads

to severe attenuation of all electromagnetic waves and thus

limits the distance of the signal through water.[50] Due to the

high water electrical conductivity at high frequency, radio

waves propagate in water differently from their propagate in

the air.[52] Due to the high water electrical conductivity at high

frequency, radio waves propagate in water differently from

their propagate in the air 4.3 Siemens/m,[53] which means it is

around 2 to 3 orders of magnitude greater than that of normal

freshwaters.[54] Therefore, due to this high attenuation, most

commercial radio equipment operates in the MHz and GHz

frequencies and therefore does not work in an underwater

environment.[52] For this reason, communication links for

distances – larger than 10 m in the ocean[55] are not easy to

create in both very- and ultra-high frequency ranges (VHF and

UHF, respectively), and even at high frequencies. At lower

frequencies ranges, for example, at extremely and very low-

frequency 2 ranges (ELF and VLF, respectively), the

attenuation of the electromagnetic wave may be regarded as

low enough to grant strong communication over many

kilometers. Regrettably, these frequency ranges between 3 Hz

and 3 kHz, and between 3 kHz and 30 kHz are not broad

enough to require transmissions at high data rates. Regardless

of being utilized in naval[56] and environmental applications,[57]

achieving reliable communication in ELF and VLF frequency

ranges has both operational and financial - challenges, as the

equipment is bulky, costly and has a high consumption of

energy.[55] or this reason, research on the use of low-frequency

RF waves has been carried out in the past, e.g. Moore[58]

suggested a - wireless communication system that is based on

microwaves, over the surface of ocean water. This system is

capable of transmitting data over tens of kilometers. An

underwater - wireless communication system based on

microwaves was used,[59] this system can communicate over a

horizontal distance of 85 m via employing large transmission

powers around 100 W. Nevertheless, it necessitates the use of

advanced antennas and considerable transmission power.[51]

A similar method was obeyed,[60] with a data rate of 500 kbps

over a horizontal distance of 90 m. Uribe and Grote[61] with a

data rate of 500 kbps over a horizontal distance of 90 m. Uribe

and Grote 61 achieved a data rate of 10 Mbps at a distance of

100 m by improving the capacity of underwater wireless

communication systems based on microwaves. Nevertheless,

RF and microwaves undergo severe attenuation in the water,

for example, in the ocean the attenuation is approximately 169

dB/m for the 2.4 GHz band, whereas in freshwater, it is even

higher, i.e., 189 dB/m.[51] For instance, 2.4 GHz radio waves

have an attenuation of about 1,685 dB/m in seawater which

has a conductivity of 4 S/m.[62]

The scientist Lloret used Binary Phase Shift Keying

(BPSK) and Quadrature Phase Shift Keying (QPSK)

modulations in conducting many experiments in the fields of

industry, science, and medicine (ISM)using 2.4 GHz, as he

was able to cover a range of 16-17 cm underwater at a

frequency of 2.4 GHz.[63] The best range of frequencies is (3-

100 MHz) for the incident beam at a depth of fewer than 5 m

from the air into the sea was established.[60] As a result, it's only

good for very short-range applications like control, telemetry,

the gas and oil industries, and marine exploration. More details

about RF communication underwater can be obtained and

found.[32] Extremely low frequency (ELF) electromagnetic

waves, i.e. 30-300 Hz, are widely implemented in military

utilization or the creation of communication lines between

terrestrial and underwater bodies.[64] They are utilized for the

propagation of long-range and they are deployed effectively

for communication with naval submarines. The ELF system

was launched in 1968 to allow deep-sea submarines to

communicate. An alerting mechanism was employed in this

project to summon the submarine to the surface for high-

bandwidth communication through terrestrial radio

networks.[65] In,[59] it was reported that by using dipole

radiation with high transmission powers, about 100 W, RF

frequencies in the MHz range can propagate in seawater up to

the range of 100 meters. Nevertheless, it needs advanced

antennas design and high transmission power.

By comparing the underwater RF communication with the

acoustic wave and optical wave, the method of radio waves

shows two important advantages. The first aspect is the

relatively smooth transmission with an air/water interface,

which permits cross-boundary communication by combining

the terrestrial and underwater radio frequency communication

systems. The second attribute is its excellent resistance to

water turbulence and turbidity.[32] Despite these advantages,

many restrictions limit the development of underwater RF

communication, most notably. First, short link range due to too

much salt in the water that is considered conductive

transmission medium and thus limits the propagation of the

RF waves that propagate a few meters at extremely low

frequencies (30-300 Hz).[45] Secondly, complex design

requirements for very large antennas, depending on their

location above or underwater. Thirdly, the speeds are still very

slow.[50]

(b) Optical communications

Because of the limitations facing the above two wireless

methods, another method was sought to restrict these

limitations. Huge antennas with high transmitter power in

fresh water and significant attenuation in seawater are the most

apparent flaws that limit the usage of RF transmissions. Also,

underwater acoustic wireless communications (UAWC) suffer

from low bandwidth and low data rate limitations.[51] All these

restrictions of acoustic and radio communications prompted

researchers to consider the option of optical wireless

particularly the visible light,[66] to support a high data rate for

a limited communication range.[8] UOWC is able to achieve

Gbps at a distance of several hundred meters because of the

high frequency of optical carrier.[51] Underwater optical

wireless communication (UOWC) is a fairly new field that

over the past decade has gained significant interest. A

significant reason behind this increased interest is the

availability of off-the-shelf commercial electronics (COTS)

components which reduce device complexity, cost, and power

consumption.[7] Optical wireless communication (OWC) is the

transmission of data through an optical carrier, that is

ultraviolet (UV), visible, or infrared, in an unguided

propagation medium. In OWC, the broadly unrestricted

spectrum (100–780 nm, or ~30 PHz) facilitates wireless data

transmission at tremendously high data rates, that could reach

gigabits per second (Gbit/s). Underwater visible light has the

distinct benefit of passing through the water with somewhat

lower attenuation than the remaining electromagnetic

spectrum. Optical waves propagation underwater often shows

distinct features in various wavelengths 1, as presented (Fig.

2). Duntley[67] determined the fewer attenuation wavelengths

are within the range of 450–550 nm wavelengths (blue and

green lights) as compared to the other wavelength range in In

1963. This is due to the photosynthesis process of algae

especially in the coastal water during the warm seasons.

Therefore, underwater optical communications and coastal

applications sensor systems are designed to work within the

green spectral range. This behaviour of optical waves was

experimentally assured by Gilbert et al.[68] in 1966, which

presented the basis for UOWC systems.

OWC's growth has continued since the initial years of

human civilization. Signaling using ship flags, smoke, beacon

fires, and semaphore telegraph can be regarded as historical

modes of OWC.[70] The world's first wireless telephone system

allowed to transmit speech was created in the year 1800 by

Alexander Graham Bell and Charles Sumner Tainter, who was

his assistant. This invention was called the photophone, and it

was implemented according to the modified sunbeam.[71] The

latest evolution of high-speed power-efficient optoelectronic

devices has presented the pledge of OWC data rates of up to

100 Gbit/s[72] with transmission links of a few kilometers.[73]

These devices involve light-emitting diodes (LEDs),[74] super

luminescent diodes,[75] lasers diodes (LDs),[76]

photodetectors,[77] modulators,[78] and the integration of these

devices.[79] In addition, OWC with dual functionality, like

Light Fidelity (Li-Fi), was suggested for simultaneous lighting

and communication purposes due to the high energy efficiency

of these high-speed optical emitters.[80] However, OWC has

evolved rapidly compared to UOWC and the main reason

behind this delay is the complexity of the aquatic

environments. Various monitor the behaviour of underwater

light, researchers conducted several theoretical and

experimental studies.[81-83] All these litterateurs supply proof of

high-capacity underwater wireless optical communication

across medium distances.

Snow et al.(1992) implemented the first experimental work

utilizing an amplitude-modulated (i.e., pulsed) green laser

beam detected by a remote optical receiver, where an argon-

ion laser diode, emitting at 514–532 nm, was used to send a

50 Mbps signal across a 9 m link length.[84] Bales et al. (1995),

LED-based theoretical analysis of UOWC was performed

where laser diode with transmission power 30 mW in

Clearwater (75% transmission) for 10 Mbps at a range of 20m

and 1 Mbps at a range of 30 m.[85] This study was later

expanded in 2005, in which the theoretical analysis of different

data rates in a variety of aquatic environments proposed that

the operational range differs from less than 10 m to more than

25 m.[86] Chancey et al. (2005) used FM modulation to develop

a short-range UOWC link with a range of up to 5 m and 10

Mbps data rate.[87] J. A. Simpson et al. have looked at basic

topics including modulation schemes, error correction, high-

speed communication lines, and so on, for UOWC.[88,89]

Hanson and Radic (2008),[90] the data rate reached as a high-

speed transceiver increased by 1Gbps, although the distance

was limited to a 2 m test tank. A bidirectional communication

link was developed in 2010, utilizing high-power LED arrays

at 470 nm and discrete pulse interval modulation to realize a

50 m communication range with a high data rate,[90] (Table 1)

presents a summary of UOWC till 2021.

UOWC systems have many advantages compared to RF

and acoustic methods, but the achievement of UOWC is still a

task facing many challenges. The three most important

challenges are:

1) Both absorption and scattering cause many undesirable

effects of light propagation. To limit the attenuation effect

caused by photon interactions with water molecules and other

particles in water, the transmitting light wavelength has been

specifically chosen in the blue and green spectrum.[67]

The most important of these effects are intense attenuation

of the transmitted light signal that causes multi-path fading,

Fig. 2 Absorption coefficient of pure seawater for different transmission wavelengths. Reproduced with permission from [69],

Copyright MDPI.

Table 1. Summaries of various UOWC till 2021.

Name, Year Type of

Transmitter Power Modulation

Type of

receiver Distance (m) Data Rate Ref.

Snow, 1992

514 nm LD

argon-ion

150 mW Pseudo random

signal

PMT 9 50 Mbps 84

Bales, 1995 LED 30 mw APD 20 10 Mbps 85

Bales, 1995 LED 30 mW APD 30 1 Mbps 85

Tivey, 2000 LED IrDA Clear

water PIN PD 5 14.4 kbps 91

Schill, 2004 LED IrDA Clear

water PD 1.71 57.6 kbps 62

Chancey, 2005 LED Square wave PD 12 10 Mbps 87

Farr, 2006 LED Square wave PMT 91 5-10 Mbps 92

Cochenour , 2007 LED 3.6 5 Mbps 93

Hanson, 2008 532 nm LD 10 mW Externally

modulated Laser APD 2 1 Gbps 94

Pontbriand, 2008 LD Digitized

waveform unknown 200 5 Mbps 95

Cox, 2008 Laser NRZ Clear

water PMT 3.66 1 Mbps 96

Cochenour, 2008 Laser 3 W Clear

ocean 64 5 Gbps 97

Cochenour, 2008 Laser 3 W Turbid

harbor 8 1 Gbps 97

Jaruwatanadilok,

2008 Laser 1 W 30- 50 1 Gbps 98

Doniec, 2009 LED 5 W Pool 30 1.2 Mbps 98

Doniec, 2009 LED 5 W Ocean 3 0.6 Mbps 99

Doniec, 2010 470 nm LED 10 W DPIM 50 2.28 Mbps 90

Simpson, 2010 LED Square wave Clear

PD 7.7 5 Mbps 88

Brundage, 2010 LED 13 3 Mbps 50

Baiden LED 10 40 Mbps 100

Gabriel, 2012 LED 0.1 W Deep sea 31 1 Gbps 101

Gabriel, 2012 LED 0.1 W Clean

ocean 18 1 Gbps 101

Gabriel, 2012 LED 0.1 W Costal 11 1 Gbps 101

Tian, 2013 Blue LED 500

Mw (avg) 20-30 Kpbs 102

Cossu, 2013 LED APD 2.5 58 Mbps 103

Watson, 2014 LD 100 mW 1.7 2.5 Gbps 104

Oubei, 2015 520 nm Laser 12 mW OOK 7 2.3 Gbps 105

Nakamura, 2015 405 nm LD 45 mW IM/DD-OFDM APD 4.8 1.45 Gbps 106

Oubei, 2015 450 nm LD 15 mW 16-QAM -OFDM 5.4 4.8 Gbps 107

Lin, 2015 Semiconduct

or Laser

Vpp (vol) turbid 0.3 5-20 Mbps 108

Shen, 2016 450 nm LD 51.3 mW NRZ-OOK APD 20 1.5 Gbps 109

Continued

Oubei, 2016 LD 450 nm QAM-OFDM 6.6 3.2 Gbps 110

Baghdady, 2016 LD 445 nm 15 mW QAM-OOK APD 2.96 3 Gbps 111

Lu, 2016 8 9.6 Gbps 112

Xu, 2016 red-light laser

diode. 32-QAM OFDM APD 6 4.883 Gbps 113

Xu, 2016 450 nm LED N/A 16-QAM OFDM 2 161 Mbps 113

Xu, 2017

diode-

pumped

solid-state

(DPSSL)

64- QAM APD 2 108.55

Mbps 114

Kong, 2017 (RGB-

WDM) LD 15/35 mW 32-QAM OFDM 10 9.5 Gbps 115

Li, 2017

488-nm LD <20 mW PAM4 Tap water PD 10 16 Gbps 116

Liu, 2017 520nm LD 19.4 mW NRZ-OOK Tap water APD 34.5 2.7 Gbps 117

Liu, 2017 520 nm LD NRZ-OOK Tap water APD 20.7 3.48 Gbps 117

Chen, 2017 520 nm LD 15 mW 32-QAM OFDM PIN 21 5.5 Gbps 118

Wu, 2017 450 nm LD 26.15 mW 16-QAM OFDM Tap water PIN 1.7 12.4 Gbps 119

Wu, 2017 450 nm LD 26.15 mW 16-QAM OFDM Tap water PIN 3.4 12 Gbps 119

Wu, 2017 5450 nm LD 26.15 mW seawater PIN 6.8 7.2 Gbps 119

Wu, 2017 450 nm LD 26.15 mW seawater PIN 10.2 4 Gbps 119

Tian, 2017 440 nm

micro-LED 1.5 mW NRZ-OOK Tap water

APD 0.6 800 Mbps 120

Tian, 2017 440 nm

micro-LED NRZ-OOK Tap water

APD 5.4 200 Mbps 120

Zhuang, 2017 448 nm LED PAM4 Tap water APD 10 400 Mbps 121

Liu, 2017 470 nm LED 4.8 mW OOK Tap water PMT 10 7.5 Mbps 122

Liu, 2017 470 nm LED 20 mW OOK Tap water PMT 50 500Kbps 122

Hamilton, 2017 11 4 Mbps 123

Sawa, 2017 120 20 Mbps 124

Fei, 2017 450 nm LD 20 mW APD 15 7.3 Gbps 125

Shen, 2018 450 nm LD <1.6 W PPM MPPC 46 2.5 Mbps 126

Cossu, 2018 470 nm LED

array (7)

Manchester-co

Harbor

water APD 7.5 10 Mbps 127

Chi, 2018 457 nm LED <160 mW PAM8, GK-DNN

NEc Tap water PIN PD 1.2 1.5 Gbps 128

Lu, 2018 460 nm LED

array (4×14) OFDM

Shallow

water PMT 10 205 Mbps 129

Kong, 2018 460 nm LED

array PAM4 Tap water MPPC 2

12.288

Mbps 130

Tsai, 2018 ~430 nm

LED <3.2 mW OOK Tap water APD 1 300 Mbps 131

Wang, 2018 448 nm LED OOK Tap water APD 10 25 Mbps 46

Continued

Hu, 2018 532 nm LD 256-PPM & RS,

Jerlov II

water SPD 120

bits/photon

Huang, 2018 450 nm LD 120 mW 16 QAM-OFDM Sea water PIN/APD 1.7 14.8 Gbps 133

Li, 2018 680-nm red-

light VCSEL 3 mW

Injection-locking

Harbor

water PIN 5 25 Gbps 134

Huang, 2018 680 nm red-

light VCSEL <5.76 mW 16 QAM-OFDM Tap water APD 6 10 Gbps 135

Fei , 2018 450 nm LD 20 mW DMT Tap water APD 15 7.33 Gbps 125

Fei , 2018 single 450-

nm LD 120 mW

Bit-power loading

DMT & NEc Tap water PIN 5 16.6 Gbps 136

Fei , 2018 single 450-

Bit-power loading

DMT & NEc PIN 55 6.6 Gbps 136

Wang , 2018 521-nm LED <160 mW 64-QAM-DMT,

MRC Tap water 2 PINs 1.2 2.175 Gbps 137

Wang ,2019 520 nm

LD <15 mW 32 QAM-OFDM Tap water MPPC 21

312.03

Mbps 138

Wang ,2019 450 nm

LD ~10 Mw 16 QAM-OFDM Sea water PIN PD 3 50 Mbps 139

Lu ,2019 450 nm

LD 50.2 mW OOK Tap water APD 60 2.5 Gbps 140

Hong , 2019 450 nm

LD ~111 mW 256QAMDMT Tap water PIN PD 35 12.62 Gbps 141

Tsai, 2019 488 nm

LD <20 mW PAM4 Tap water APD 12.5 30 Gbps 142

Tsai, 2019 488 nm

LD <20 mW PAM4 Harbor APD 2.5 30 Gbps 142

Han, 2019 470 nm LED

array (7) 1.2 W OOK Tap water PMT 8 19 Mbps 143

Tasi , 2019 405 nm LED

array (4×4) <56.7mW QAM-OFDM Tap water APD 1 200 mbps 144

Zhou ,2019 RGBYC LED 64QAM-DMT

bit-loading-DMT Tap water PIN PD 1.2

14.81 Gbps

15.17 Gbps 145

Wang, 2019 Blue LED <120 mW 64QAMDMT Tap water PIN PD 1.2 3.075 Gbps 146

Shen, 2019 Blue LED PPM Tap water MPPC 46 ~MHz 147

Wang, 2019 520 nm LD 7.25 mW NRZ-OOK Tap water APD 100 500 Mbps 148

Li , 2019 458 nm LED 2.8 mW 32QAMDMT Tap water PIN array

(2×2) 1.2 20.09 G 149

Chen , 2020 450 nm LD 22.9 mW NRZ-OOK Tap water SPAD 117 2M bps 150

Chen, 2020 450 nm LD 22.9 mW NRZ-OOK Tap water SPAD 144 500 bps 150

Hu, 2020

LED array

(4×4)

~285.5

PS-bit loading

DMT Tap water PIN PD 1.2 20.09 Gbps 151

Ramavath , 2020

470 nm

N number of

sources

number

of Photo-

Detectors

30 500 Mbps 152

Hema, 2020 1.5 153

Continued

Arvanitakis, 2020

450 nm

Micro-LED

arrays (6)

<20 mW QAM-OFDM Tap water PIN PD 1.5 4.92 Gbps 154

Arvanitakis, 2020

450 nm

Micro-LED

arrays (6)

<20mW QAM-OFDM Tap water PIN PD 3 3.22 Gbps 154

Arvanitakis, 2020

450 nm

Micro-LED

arrays (6)

<20mW QAM-OFDM Tap water PIN PD 4.5 3.4 Gbps 154

Chen, 2020 520 nm LD 32-QAM APD 56 3.31 Gbps 155

Du, 2021 450 nm laser DFT-S DMT Clear

water APD 50 5 Gbps 156

poor bit error rate (BER) performance over a few hundred

meters link distance in the turbid water environment. In

underwater environments, substances like chlorophyll will

absorb the blue and red lights. These and other colored

dissolved organic material (CDOM) will enhance the turbidity

of the water and thus reduce the light propagation distance.

Furthermore, the CDOM concentration would as well change

with the variations in ocean depth, thereby varying the related

light attenuation coefficients.[157]

2) An exact alignment condition is required in order to ensure

that underwater optical links are not temporarily disconnected

due to misalignment between transmitters and receivers.[158] In

many UOWC systems studies, blue/green lasers or LEDs have

been used because they are distinguished with the advantage

of their narrow beam divergence. Link misalignment can

happen frequently because the underwater environment is

turbulent at relatively shallow depths, particularly in surface-

to-bottom UOWC systems based on vertical buoys.[157,81]

Serious connectivity loss problem occurs due to random

movements of the sea surface.[159]

3) Due to the complexity of the aquatic environment, the

implementation of UOWC systems requires reliable

underwater devices. The performance and lifetime of UOWC

devices are significantly affected by a number of natural

phenomena such as flow, temperature pressure and salinity of

seawater.[45] Batteries have a limited amount of energy and are

difficult to recharge (solar energy cannot be used

underwater).[45]

The major disadvantage of optical communication is that

the range is restricted to 1-100 meters.[160] This range is

determined by water and suspended particles in water where

light is attenuated either by water or dispersed by suspended

particles.[161] Another disadvantage is that optical

communication normally requests a direct line of sight from

the transmitter to the receiver. In Table 2, we compare and

contrast the advantages and drawbacks of the three most

prevalent methods for achieving UOWC.

2.3 Hybrid systems

By combining two or more of the aforementioned underwater

communication methods, hybrid systems are established. This

method is often used for ocean mooring with sensors on the

anchoring cable and wireless cellular connection. Although

hybrid systems are useful because they can take advantage of

the strengths of each method, consequently, increase the

reliability of the system,[7] one of the most important

challenges facing hybrid systems is to move from one

communication medium to another adaptively and seamlessly,

which makes the system more complex and more difficult and

requires protocols and algorithms to understand the

environment in the hybrid system.[162] Many undersea vehicles

used hybrid communication systems that included both

acoustic and optical systems.[163,164] By choosing appropriate

communication links in response to variable traffic loads and

weather effects circumstances, article[165] presents a hybrid

optoacoustic underwater wireless communication system that

minimizes network power consumption and allows high-data-

rate underwater applications. When compared to conventional

optoacoustic techniques, the suggested approach saves up to

35 % on power. Depending on the interoperability between

different underwater wireless communication methods, a

hybrid network of these methods has been proposed.[166]

3. Light properties in water

Water molecules and impurities like suspended and dissolved

particles, organic and inorganic elements make up the

undersea environment, so it can be considered as a complex

and dynamic environment.[167] Interactions between these

particles and light take place and are categorized according to

the optical properties of the water, which differ by several

considerations such as location, time of day, organic and

inorganic content, and temporal differences. The water’s

optical properties can be divided into two parts: inherent and

apparent.[168]

Table 2. Comparison of different wireless underwater technologies.

3.1 Inherent optical properties

Inherent optical properties (IOPs) rely exclusively on water

(components and the electromagnetic properties of the water)

and particulate substances that are present in the water

(suspended and dissolved particles). The geometry of the

ambient light field inside the medium does not affect the

optical properties inherent of water, that is, IOP is not affected

by the method of illumination of sample.[169] The primary IOP

are absorption coefficient 𝑎(𝜆) , scattering coefficient b(λ),

volume scattering function (VSF), attenuation coefficient c(λ),

Acoustic RF Optical A

– Long distance communication

– Widely used UWC technology.

– Tolerant to turbidity

– Moderate data rate

– Smooth flow from air/water interface

- Unaffected by turbidity, salinity, and

pressure gradients

- Works in non-line-of-sight.

-Low cost

-High data rate (gigabits per second)

-Immune to latency.

– High latency

– More energy consumption

– Costly

– Dangerous for marine species

– Low data rate

-Strong reflections and attenuation

when transmitting through water/air

boundary

-Poor performance in shallow water

- Affected by temperature, ambient

noise, salinity, water depth, and

pressure gradients.

-High attenuation over short distance

-Costly

-Bulky

-Severe scattering and absorption

-Difficulty to cross air/water interface

-Medium range

Speed (m/s) 1500 ≈ 2.3 ×108 ≈ 2.3 ×108

Frequency band 10-15 kHz 20 – 300 Hz (ELF) 1012 -1015 Hz

Bandwidth

Distance

dependent[19]:

1000 km <1

1-10 km ≈1

<100 m≈

100kHz

≈ MHz

High bandwidths (up to 100 Mb/s) at very

close range

10-150 MHz

Distance More than 100

kms Up to ≈ 10 m ≈≈ 10 − 150 m

Data rate ~ kbps ~ Mbps ~ Gbps

Attenuation 0.1-4 dB/km (3.5- 5 dB/m) 0.39 dB/m (ocean)

11dB/m (turbid)

Latency High Medium Low

Antenna /receiver

size 0.1 m 0.5 m 0.1 m

Multipath High Low Low

Power consumption High Low High for laser

Low for LED

Transmission

power Tens of Watts Few mW to hundreds of Watts Few watts

Efficiency ≈ 100 bits/J ≈ 30,000 bits/J

Performance

Parameter

-Temperature -

salinity

-Pressure

-Frequency,

-Water conductivity: (salinity and

temperature)

-Absorption

-Scattering

-Turbidity (chlorophyll concentration, salt

ions, etc.).

single scattering albedo 𝜔0, and index of refraction.[170]

Assume a water sample of small volume ΔV and thickness

Δd where a collimated beam with radiant power 𝑃𝐼(λ) is

guided onto the water sample. Part of this power of beam is

absorbed 𝑃𝐴 (λ), part is scattered 𝑃𝑆(λ) by an angle Φ, and

the residual power is transported via water 𝑃𝑇(λ). The ratio of

absorbed power to total incident power is denoted as spectral

absorptance 𝐴(𝜆).

𝐴(𝜆) =𝑃 𝐴 (𝜆)

𝑃𝐼(λ) (1)

In the same way, the spectral scatterance, B(𝜆 ) can be

found by, the ratio of scattered power to the incident power.

𝐵(𝜆) =𝑃𝑆(λ)

𝑃𝐼(λ) (2)

The spectral absorption coefficient 𝑎(𝜆) can be found by

taking the limit, when the thickness approaches zero, for the

ratio of the spectral absorption 𝐴(𝜆) to the thickness Δ𝑑, as

follows:

𝑎(𝜆) = limΔ𝑑⟶0

𝐴(𝜆)

Δ𝑑 (𝑚−1) (3)

And the spectral scattering coefficient 𝑏(𝜆) can be found

by taking the limit when the thickness approaches zero for the

ratio of the spectral scattering 𝐵(𝜆) to the thickness Δ𝑑 , as

follows:

𝑏(𝜆) = limΔ𝑑⟶0

𝐵(𝜆)

Δ𝑑 (𝑚−1) (4)

The spectral beam attenuation coefficient c( 𝜆 ) can be

obtained by combining the spectral absorption coefficient and

the spectral scattering coefficient as:

c(𝜆) = a(𝜆)+ b(𝜆) (5)

where a(𝜆) and b(𝜆) are absorption and scattering coefficient,

respectively. Also the units of coefficients c(𝜆), a(𝜆) and b(𝜆)

are measured in 𝑚−1 and 𝜆 is the vacuum wavelength of

light in (nm)3.

The angular scatterance per unit distance and unit solid

angle, β (Φ, λ) is demarcated as:

β (Φ, 𝜆 ) = limΔ𝑑⟶0

limΔΩ⟶0

β (Φ, 𝜆 )

ΔΩΔ𝑑=

limΔ𝑟⟶0

limΔΩ⟶0

𝑃𝑆 (Φ,𝜆 )

𝑃𝐼ΔΩΔ𝑑 (𝑚−1𝑠𝑟−1) (6)

where β (Φ, 𝜆) is the fraction of power that is scattered out of

the beam through an angle Φ into a solid angle ΔΩ centered

on Φ.

𝑃𝑆(λ) is the spectral power scattered into a solid angle is

calculated as:

𝑃𝑆(Φ, λ) = I𝑠 (Φ, 𝜆 )ΔΩ . (7)

The incident irradiance is computed as follows:

E𝑖 = 𝑃𝐼(λ)/ΔA. (8)

Substituting ΔV = ΔdΔA which is the volume of the

water, results in:

β (Φ, 𝜆 ) = limΔV⟶0

I𝑠 (Φ,𝜆 )

E𝑖( 𝜆) ΔV (9)

This equation denoted the volume scattering function (VSF)

and it can be explained as the scattered intensity per unit

incident irradiance per unit volume of water. By integrating β

(Φ, λ) over all directions, the total scattered power per unit

incidence irradiance and unit volume of water can be

calculated, this parameter is known the scattering coefficient.

𝑏( 𝜆) = ∫ β (Φ, 𝜆 )dΩ = 2𝜋 ∫ β (Φ, 𝜆 ) sin Φ𝑑Φ𝜋

0 (10)

The forward (b𝑓) and backward (b𝑏) scattering coefficients

can be calculated via:

𝑏𝑓( 𝜆) = 2𝜋 ∫ β (Φ, 𝜆 ) sin Φ𝑑Φ𝜋/2

0 (11)

𝑏𝑏( 𝜆) = 2𝜋 ∫ β (Φ, 𝜆 ) sin Φ𝑑Φ𝜋

𝜋/2 (12)

By normalizing the VSF with the scattering coefficient, the

scattering phase function 𝛽 ̃ (Φ, 𝜆 ) can be attained:

𝛽 ̃ (Φ, 𝜆 ) = β (Φ,𝜆 )

b( 𝜆 ) (𝑠𝑟−1) (13)

𝛽 ̃(Φ, 𝜆)can be expressed as the probability of the photon

scattering event in the angular direction Φ.

Single scattering albedo 𝜔0 can be determined as the ratio

of the scattering coefficient to the attenuation coefficient,

where the attenuation coefficient is absorption and scattering,

therefore result of the single scattering albedo law gives the

possibility of photon scattered rather than absorbed:

𝜔0= b( 𝜆 )

c ( 𝜆 ) (14)

If the value of the scattering coefficient is greater than

the value of the absorption coefficient, then the value of single

scattering albedo is 1, and if the value of the absorption

coefficient is bigger than the value of the scattering

coefficient, then the value of single scattering albedo is zero.[52]

3.2. Apparent optical properties

The apparent optical properties (AOPs) are based on two main

factors: the medium and the geometric structure of the

illumination, i.e. whether it is a collimated or diffused

beam.[171] The apparent properties have many benefits, most

notably the following. First, the apparent properties determine

the directional property of the optical beam. Second, they are

utilized to assess the amount of ambient light for

communication nearby the water's surface.[172] Third, when it

comes to radiant energy penetration into the depths of the

ocean, AOPs are very important.[52] Radiance, irradiance, and

reflectance are the most common apparent qualities. The

apparent feature can be produced from regular and stable

lighting sources. Thus, the downwelling irradiance from Sun

is not considered as a clear property due to its variation times

of day and weather state.[171] The diffuse attenuation

coefficient is an optical property that is dependent on the light

field geometry.[170] In those instances, either a ratio of

properties, that are equally impacted by the environment, is

taken into account or a normalized derivative, as indicated by

the following equation[171]

𝑘(𝑧, 𝜆) = −1

𝐸(0,𝜆)

𝑑𝐸(𝑧,𝜆)

𝑑𝑧 (15)

where E is defined as the original apparent property like down

welling irradiance from Sun.

More information about AOPs such as their definitions and

measurements are available at.[168,172-174] Each type of optical

properties have features that contribute to the implementation

of UOWC systems where, AOPs are utilized to compute

ambient luminance near the water surface, whereas IOPs are

utilized to determine communication link budgets.[175]

4. Types of water

Both geographically and vertically differences cause the ocean

waters to differ. The geographical variation ranges from the

clarity of the oceans to coastal areas, and the vertical

difference depends on the amount of light received from the

sun in addition to less background radiation.[176] Despite the

many different types of waters, it can be classified into oceanic

and coastal areas depending on the downwelling irradiance of

sunlight.[176] The oceanic group is divided into four main water

types commonly taken into special consideration in the

literature.[94,177]

• pure seawater, the scattering is low thus the beam

propagates in a nearly straight line, but absorption remains

predominant, leading to a signal loss more than scattering in

these regions.

• clear ocean water, scattering is the dominant factor due to

the abundance of concentration of dissolved particles and

consequently, the scattering has a great effect on overall

attenuation.

• coastal ocean water, the absorption owing to

phytoplankton is the major limiting factor and, hence, the ideal

wavelengths lean towards green.

• Turbid Harbor Water: It shows strong absorption in blue

wavelengths due to the availability of both suspended matter

and color dissolved organic matter (CDOM) like fulvic and

humic acids.

Owing to the salinity that affects the clusters and settling

velocity of suspended particulate matter (SPM), oceans and

estuaries have lower average turbidity than fresh water in lakes

and rivers. Salinity affects the cluster of suspended particles

and attaches them, which leads to their stability at the bottom,

and here shows the interconnectedness between salinity, SPM

and water clarity.[178] The value of the attenuation coefficient c

(λ) depends on the type and depth of the water. The following

table (Table 3) shows the scattering, absorption, and extinction

coefficient for various types of waters.[179]

Table 3. Optical properties of ocean water types. Reproduced

with permission from[179]. Copyright International Journal of

Advanced Computer Science and Applications (IJACSA), 2020.

Water Type a (m-1) b (m-1) c (m-1) -10 dB

distance (m)

Fresh Water 0.040 0.02 0.042 53.55

Sea Water 0.114 0.036 0.150 15.25

Coastal Water 0.178 0.220 0.398 5.77

Harbor Water 0.366 1.828 2.194 1.05

5. Important factors that affect the UOWC

5.1 Absorption

Absorption is the process that occurs when photons interact

with water molecules and particles, leading to an inevitable

loss of energy.[52] According to the principle of energy

conservation, the energy of photons that are lost during the

absorption process is transformed into other sorts like heat and

chemical energies.[180] The continuous decrease of the total

propagating power leads to a reduction in the link distance of

the UOWC, and this is considered the most prominent

absorption effects that limit the implementation of the

UOWC.[180] The density and structure of the particles in the

water, greatly influence the absorption process.[52]

To mathematically derive the coefficients of absorption

and scattering, we suppose that a volume of water ΔV with

thickness Δ d is irradiated by a collimated light beam with

wavelength λ. 𝑃𝐼(λ) refers to the power of the incident light.

A fraction of the incident light power 𝑃𝐴(λ) is absorbed by

water, and another fraction of light power 𝑃𝑆(λ) is scattered.

𝑃𝑇(λ) is the remaining light power that will propagate as

anticipated? The water absorbs a portion of the incident light

power 𝑃𝐴 (λ) and scatters the other portion 𝑃𝑆(λ), while the

remaining part will complete its propagation, 𝑃𝑇(λ), without

any suffering. Based on the law of power conservation, we

have[168,181]

𝑃𝐼(λ) = 𝑃𝐴(λ) + 𝑃𝑆(λ) + 𝑃𝑇(λ) (16)

Section 3.1 can be considered for details of conclusion for

the absorption, scattering and attenuation coefficients.

Moreover, in the words of Jerlov, the underwater light

absorption coefficient can also be defined as the sum of four

absorption factors [182]

a (𝜆) = 𝑎𝑤(𝜆) + 𝑎𝐶𝐷𝑂𝑀(𝜆) + 𝑎𝑝ℎ𝑦(𝜆) + 𝑎𝑑𝑒𝑡(𝜆) (17)

where 𝑎𝑤(𝜆) is the absorption due to pure seawater,

𝑎𝐶𝐷𝑂𝑀(𝜆)is the absorption due to CDOM, 𝑎𝑝ℎ𝑦(𝜆) refers to

the absorption due to phytoplankton, and 𝑎𝑑𝑒𝑡(𝜆) is the

absorption due to detritus.The absorption effect of pure

seawater is attributed to two sources:

- water molecules.

- dissolved salt in water such as NaCl, MgCl2, Na2SO4,

and KCl.[183]

Water molecules absorb a lot of red and infrared light (IR),

this absorption is achieved through many processes such as

ionization, electronic excitation, vibrational or rotational

excitation of water molecules.[87] CDOM is made up of

decomposing organic marine materials and is also known as

gelbstoff. It has dimension smaller than 0.2 mm.[184] Its

concentrations in coastal water are fairly high, whereas those

in oceanic water are fairly low.[52] The blue wavelength absorbs

the most in coastal water, and its absorption reduces

exponentially as the wavelength increases,[52] as shown in Fig.

3. A modeling equation is given to explain this phenomenon

for the wavelength range 350 nm < 𝜆 <700 nm.

𝑎𝐶𝐷𝑂𝑀(𝜆) = 𝑎𝐶𝐷𝑂𝑀(𝜆0 )exp [−0.014(𝜆 − 𝜆0 )] (18)

where the value for 𝜆0 is 400 nm in this situation and

𝑎𝐶𝐷𝑂𝑀(𝜆) is the absorption owing to CDOM at reference

wavelength of 440 nm, which is the selected frequently.[168]

Phytoplanktons are minute creatures that live solely in the

photic zone, which is the area of the ocean where sunlight may

propagate into the waters. It has a range of 50 to 200 meters in

clear ocean water, up to 40 meters on continental shelf, and 15

meters in coastal waters.[185] It contains colorful pigments like

chlorophyll, carotenoids, pheophytin, chlorophyllide, and

phaeophorbides, among others, that absorb a substantial

amount of light. Photosynthesis of chlorophyll is primarily

responsible for phytoplankton absorption effects.[186]

Chlorophyllin phytoplankton absorbs plenty of visible light,

particularly the blue and red wavelengths (𝜆 =430 nm and

665 nm) with extremely small absorption in the green,[168] Fig.

3 is shown the absorption coefficient of pure seawater colored

dissolved organic matter (CDOM) and particles.[183,187-190] The

amount of chlorophyll in the water is determined by the

amount of phytoplankton present, which varies depending on

geographic location, water type, and water depth.[52]

Chlorophyll concentrations in the open ocean range from 0.01

to 4.0 mg m-3, whereas near-shore levels are estimated to reach

as high as 60 mg m−3.[175] Moreover, the distribution of

phytoplankton changes with depth undersea, where only 1%

of the sunlight enters.[185] This means that the attenuation

coefficient differs based on depth, geographical location, hour

of day, and weather.[191]

Fig. 3 Absorption coefficient due to pure seawater, CDOM

and particles. Reproduced with permission from [193],

copyright MDPI.

Detritus is a type of organic waste that is generated by dead

plants and animals[52] and comprises living organic particles

like bacteria and zooplankton, detrital organic debris, and

suspended inorganic particles like quartz and clay. Because of

their same absorption behavior, these chemicals have been

classified together.[192] The peak of its absorption is located in

the blue region of the visible part of the electromagnetic

spectrum.[52] Analogous to the absorption by CDOM, detritus

absorption is described using a model:

𝑎𝑑𝑒𝑡(𝜆) = 𝑎𝑑𝑒𝑡(𝜆0 )exp [−0.011(𝜆 − 𝜆0 )] (19)

where 𝑎𝑑𝑒𝑡(𝜆) is the detritus absorption at the reference

wavelength, which in this case is 400 nm.[168]

As a result of the high total absorption coefficient in both,

the blue region of the electromagnetic spectrum, by the

phytoplankton pigments and the red region of the

electromagnetic spectrum by water, the total absorption

coefficient will be significantly high at these two wavelength

regions.

Depending on the different factors affecting absorption in

underwater environments, the optimal transmission

wavelengths for Pure sea / clear ocean is 450- 400 nm (blue-

green) because the concentration of Chlorophyll, Humic and

fulvic are little. In the Costal ocean, the minimum attenuation

window is around 520-570 nm (yellow-green), the

concentration is high, but in Turbid harbor, work on the range

520-570 nm (yellow-green) and it is much higher

concentrations.[12]

5.2 Scattering

Scattering is the process that takes place when the photon’s

path direction changes from the original direction due to their

interaction with the particles in the water.[52] This

aforementioned interaction causes a change in the direction of

propagation, while the energy does not change.[52] In ocean

waters, scattering occurs in both the forward and backward

directions dramatically, but peaks in the forward direction.[52]

Scattering, unlike absorption, is largely wavelength

independent. The density of particulate matter is the most

important element affecting scattering.[180]

Based on the particle radius, scattering can be divided into

three types.[168,194]

• Molecular (Rayleigh) scattering (≪ λ) (wavelength of

the incident light): This kind of scattering is produced by the

nonuniform local concentrations of molecules and particulate

matter. The intensity is directly proportional to the sixth power

of their diameter and inversely proportional to the fourth

power of the wavelength.

• Turbulent scattering (≫ λ): This scattering mechanism

is proportional to the square of the particle diameter[176] and

results from the random variation in the refractive index (n) of

seawater that relies on temperature, salinity, pressure and

wavelength.[195] The light beam might fluctuate both

temporally and spatially due to the changing refractive index,

this phenomenon is referred to as scintillation.[196] The effect

of turbulence on extremely short-range (less than 10 m) links

may be ignored because the refractive index in seawater does

not change considerably in such links.[81] While the effects of

turbulences appear at longer ranges, they cannot be ignored,

as reported in [197,198]. The studies [199-201] have provided

more details about turbulence in the underwater environment.

• Large particles (∼ λ): This process is typically

determined by the scattering induced by organic and inorganic

particles in seawater. The diameter of such particles is usually

ten times larger than the wavelength of the light.[168] The

scattering coefficient for underwater light propagation can

also be given as a result of the sum of various scattering

factors.[202]

b (𝜆) = 𝑏𝑤(𝜆) + 𝑏𝑝ℎ𝑦(𝜆) + 𝑏𝑑𝑒𝑡(𝜆) (20)

where 𝑏𝑤(𝜆) is the scattering attributed to pure seawater;

𝑏𝑝ℎ𝑦(𝜆) denotes the scattering attributed to phytoplankton;

and 𝑏𝑑𝑒𝑡(𝜆) represents the scattering attributed to detritus.

Because the refractive index changes with flow, salinity,

and temperature fluctuations in pure seawater, the scattering

coefficient will change as well.[180] The Rayleigh scattering

model may be utilized to depict the dispersion generated by

pure saltwater since the wavelength of light is quite high

compared to the size of water molecules.

• At constant temperature and pressure, the absorption

coefficient of water is invariant, although it is highly

dependent on, the scattering coefficient caused by Rayleigh

scattering is similarly highly dependent on. When compared

to absorption, the scattering coefficient has low variance with

temperature and pressure.

• The absorption coefficient of the sea salt is negligible and

it increases towards short 𝜆 . Scattering coefficient due to

Rayleigh scattering, and it is no depends on 𝜆.

• Absorption coefficient is variable with the density of

CDOM, Plankton and detritus also increased towards short 𝜆

but scattering coefficient is negligible by CDOM. Scattering

coefficient is variable with the density of plankton and detritus

(Mie scattering), and increase towards short 𝜆.

Three processes may be used to characterize the effects of

scattering on UOWC links: spatial, temporal, and angular

dispersion.[203]

Spatial dispersion is produced by the beam spreading

owing to the multiple scattering mechanisms. The photon

density at the receiver site decreases as a result of this. Photons

arriving at the receiver from a diffuse beam are spatially

scattered due to the initial distribution as well as the

underwater environment.[97,203] As the light beam hits the

receiver at various times, it causes temporal dispersion. As a

result, there would be a path difference and a time delay,

potentially limiting bandwidth.[97,203,204]

Angular dispersion refers to the distribution of photon

reception angles owing to scattering underwater. Scattering

occurs at small forward angles in seawater, as a result, the

angular dispersion is small. Angular dispersion, on the other

hand, can have major effects in turbid water where scattering

dominates[204] VSF is an essential parameter that defines

scattering in seawater, as discussed in section 3.1. VSF has

been measured by several researchers. The next section

defines the VSF computed by Petzold as well as two analytical

formulae for modelling the VSF.[52]

5.2.1. Petzold scattering function

n underwater scattering modelling, the Petzold phase function

is the most widely quoted and utilized. Reference[205] defines it

as a portrayal of normal ocean water. It is based on the results

of investigations of three forms of water taken in the early

1970s: turbid water, coastal water, and clear water.[206] The

turbid water sample was taken in San Diego Harbor, California,

the coastal water sample was taken in San Pedro Channel,

California, and the clear water sample was taken in the Tongue

of the Ocean, Bahamas Islands.

The VSFs for the three types of water, which was used as

a scattering agent in the laboratory experiment.[207] The VSFs

are clearly peaked forward, meaning that the majority of the

light will disperse at small forward angles.[52]

5.2.2. Analytical phase functions

There have been a number of analytical phase functions

suggested, two of which are considered in this paper.

The first one is Henyey-Greenstein (HG) function,[52] it was

first suggested in 1941 for use in astrophysics to describe the

scattering angles induced by interstellar dust clouds.[208] It is

used by several researchers in underwater environments, but

they point out that it is inaccurate at small angles of less than

20o and broad angles of more than 130o.[209,210]

The equation for the HG phase function is:

𝑃𝐻𝐺(𝛷, 𝜆) =1

1−𝑔2

(1+𝑔2−2𝑔𝑐𝑜𝑠 𝛷)3/2 (21)

where Φ is the scattering angle, and g is the HG asymmetry

parameter, which is equal to the average cosine of the

scattering angle over Φ all directions of scattering and is

dependent on the medium's characteristics.[52]

The amounts of light scattered in the forward direction is

represented by the value of g.[211] If g = 0, the scattering is

isotropic, and if g = 1, the scattering is very forward.[212] More

details about the influence of various g values can be obtained

and found.[213]

The second analytical phase functions are Two-Term

Henyey-Greenstein (TTHG). Haltrin changed the original HG

function to create this phase function.[214] It is more explicit

than the original HG model, but not as accurate as Petzold's[52]

phase function, which is calculated by experiment.

The TTHG function is given by:

𝑃𝑇𝐻𝐺(𝛷, 𝜆, 𝑔 𝐹𝑊𝐷, 𝑔𝐵𝐾𝑊𝐷) = 𝛼𝑃𝐻𝐺(𝛷, 𝑔𝐹𝑊𝐷) +

(1 − 𝛼)𝑃𝐻𝐺(𝛷, −𝑔𝐵𝐾𝑊𝐷) (22)

where α is the forward-directed HG phase function weight,

and 𝑔 𝐹𝑊𝐷 and 𝑔𝐵𝐾𝑊𝐷 are the asymmetry factors for the

forward and backward-directed HG phase function,

respectively.

Absorption is the key limiting factor in pure seawater, but

the low scattering coefficient prevents the beam from

diverging. Clear ocean waters have a larger concentration of

dissolved particles, which impacts scattering. The primary

source of absorption and scattering are high concentrations of

plankton, detritus, and minerals in coastal ocean water. The

highest concentration of dissolved and in-suspension matter is

found in turbid harbor water, which significantly reduces light

propagation.[215]

5.3. Attenuation

The sum of the attenuation caused by absorption and scattering

defines the total attenuation in the UOWC system. By using

Beer-Lambert's law, the attenuation coefficient called also the

extinction coefficient of the optical signal for a distance z is

determined as shown:

𝐼 = 𝐼0 𝑒−𝑐(𝜆)𝑧 (23)

where 𝐼0 is the power of transmitted light; z signifies the light

transmission distance; I refers to the power of light after

transmitting z distance, and c(λ) indicates the attenuation

coefficient. With various water types and depths, the value of

the attenuation coefficient c(λ) can change. The parameters

that impact the underwater optical wireless communication

transmission system are affected by types of water which

depends on (wavelength, depth, and season). Absorption is

influenced by biological factors such as the concentration of

chlorophyll, fulvic acid and humic acid.[3] Scattering of the

spectra is influenced by biological factors such as large

particles and small particles. The statistical distribution and

scattering strength was used to calculate scattering

coefficients.[3]

Beer's Law has a restricted application because it only

explains the attenuation due to absorption and single events of

scattering.[216] However, several cases of multiple scattering

can occur in nature. It also assumes that the source and

receiver are perfectly aligned with each other, and only in

Line-of-Sight (LOS) contact situations can it be implemented.

Also, Beer's Law avoids temporal dispersion.[22]

The references[53,157,168,217,218] provide more information on

different types of water and differences in attenuation

coefficient with other characteristics like depth, pressure, and

salinity.

5.3.1 Attenuation length

Attenuation length (AL) is the product of attenuation

coefficient c(𝜆) and transmission distance z, and it is a unitless

quantity.[52] AL is the exponential component's argument in the

BL law (𝑐(𝜆)𝑧). The received power would be reduced by a

factor of 1/e, or 63 percent, at 1 AL. To compare the

performance of different systems, particularly at differing

water turbidities and transmission distances, several studies

use attenuation length, (AL=(𝑐(𝜆) ∗ 𝑧).[219]

5.4 Turbulence

Optical turbulence greatly influences optical wireless

communications. It is defined as the random fluctuations of

the refraction index. The underwater nature is very complex

and the transmission of optical beams is also greatly perturbed

by ocean turbulence.[216] Ocean turbulence is the result of many

phenomena, including changes in temperature, differences in

salinity and the formation of air bubbles in seawater.[54]

5.5 Signal noise underwater

There are several noise sources that disturb the system of

optical communication under water. Each noise is addressed

and the expression is given for its variance in.[86,220] In the bit

transmission simulation, the variation of noise converts into

the noise power range that we can use.

The modeled noise consists of (1) background noise, (2)

dark current noise, (3) thermal noise, and (4) shot noise.[98]

5.5.1 Background noise

The background noise comes from the optical environment

and electrical current leakage from photodetector.[51] It consists

of black body radiation and underwater ambient light, the

main source of which is the refracted sunlight from the water's

surface.[98] The background noise power can be written as:

𝑃𝐵𝐺 = 𝑃𝐵𝐺_ 𝑠𝑜𝑙𝑎𝑟 + 𝑃𝐵𝐺 _𝑏𝑙𝑎𝑐𝑘𝑏𝑜𝑑𝑦 (24)

The variance of the background noise is:

𝜎𝐵𝐺2 = 2 𝑞ℜ𝑃𝐵𝐺𝐵 (25)

where ℜ is the responsivity, λ is the wavelength, ℎ =6 .6261 × 10−34 𝐽 ss is the Planck’s constant, the electron

charge 𝑞 = 1 .6 × 10−19 coulombs, η =0 .8 is the quantum

efficiency of the detector, and B is the electronic bandwidth.

Solar background noise: The solar background noise power is:

𝑃𝐵𝐺− 𝑠𝑜𝑙𝑎𝑟 = 𝐴𝑟 × 𝐹𝑜𝑣𝐹𝑎𝑐 × 𝛥𝜆𝑇𝐹 𝐿𝑠𝑜𝑙 (26)

where 𝐴𝑟 = πD2

4 , D is the diameter of the aperture, FOV is

field of view of the system in radians, 𝐹𝑜𝑣𝐹𝑎𝑐 = 𝜋(𝐹𝑂𝑉)2, Δλ is the optical filter bandwidth, and 𝑇𝐹 is the optical filter

transmissivity. The solar radiance 𝐿𝑠𝑜𝑙 (watts/𝑚2) is given by 86:

𝐿𝑠𝑜𝑙 = 𝐸𝑅𝐿 𝑓𝑎𝑐𝑒𝑥𝑝(−𝐾𝐷𝜔)

𝜋 (27)

where E is downwelling irradiance (𝑤𝑎𝑡𝑡𝑠/𝑚2), R is

underwater reflectance of the downwelling irradiance, 𝐿 𝑓𝑎𝑐

is the factor describing the directional dependence of the

underwater radiance, K is the diffuse attenuation coefficient,

and 𝐷 is depth. For a wavelength of 532 nm, E = 1440

watts/ 𝑚2 , R =1 .25%, and 𝐿 𝑓𝑎𝑐 = 2.9 in the horizontal

direction.[86]

2) Blackbody radiation background noise: The noise

power from blackbody radiation is:

𝑃𝐵𝐺−𝑏𝑙𝑎𝑐𝑘𝑏𝑜𝑑𝑦 =2ℎ𝑐2𝛼×𝐹𝑜𝑣𝐹𝑎𝑐×𝐴𝑟𝑇𝐴𝑇𝐹𝛥𝜆

𝜆5[𝑒𝑥𝑝(ℎ𝑐/𝜆𝑘𝑇)−1] (28)

where 𝑐 = 2 .25257 × 108 𝑚 𝑠⁄ is the speed of light in the

water, 𝑇𝐴 = exp( −τo) is the transmission in water, 𝑘 =1 .381 × 10−23 𝐽. 𝐾−1 is the Boltzmann’s constant, and α

=0 .5 is the radiant absorption factor.

In reference,[221] a photon tracing algorithm is used to

develop a unified model for underwater channel

characterization and system performance analysis in the

presence of solar noises, particularly for a shallow

environment. By considering a tight (FOV), the delay spread

and ambient noise impact may be reduced, and the system can

also achieve accuracy when combined with a wide aperture.

5.5.2 Dark current noise

Dark current noise is the noise present in the detector in the

absence of light, when there is no optical power incident on

the photodetector. It also refers to the minimum light intensity

that the (photodiode) can detect and leads to photocurrent

generated by background radiation.[222]

The variance of the dark current noise is:

𝜎𝐷𝐶 2 = 2𝑞𝐼𝐷𝑐𝐵 (29)

where 𝐼𝐷𝑐 = 1 .226 × 10−9 Ampere.

5.5.3 Thermal noise (Johnson noise)

This noise is due to the resistive elements in the pre-amplifiers

used in receivers.

The variance of the thermal noise is

𝜎𝑇𝐻2 =

4𝑘𝑇𝑒𝐹𝐵

𝑅𝐿 (30)

where we suppose that the equivalent temperature 𝑇𝑒 is 290K,

F = 4 is the noise figure of the system, and 𝑅𝐿 = 100 Ω is the

load resistance.

5.5.4 Current shot noise

Shot noise exists when the received signal is present. It

referred also to the quantum noise. It occurs due to random

variance of received photons on the receiver side.[51] It is

related to the statistical fluctuation in both the photocurrent

and the dark current. These fluctuations are due to the

randomness of electrons. In other words, these electrons are

produced in different time and in different areas of photodiode,

so the current which is produced by these electrons has

fluctuations.

The variance of current shot noise is:

𝜎𝑠𝑠 2 = 2 𝑞ℜ𝑃𝑠𝐵 (31)

where 𝑃𝑠 is the signal power. The total noise variance

represents the sum of all noise sources. \Therefore, in the

detector, the variance in current noise without any optical

signal is defined as:

𝜎0 2 = 𝜎𝑇𝐻

2 + 𝜎𝐷𝐶 2 + 𝜎𝐵𝐺

2 (32)

Due to the presence of shot noise, the current noise variance

in the detector for receiving an optical signal is defined as:

𝜎 1 2 = 𝜎𝑇𝐻

2 + 𝜎𝐷𝐶 2 + 𝜎𝐵𝐺

2+ 𝜎𝑠𝑠 2 (33)

5.6 Multipath interference and dispersion

The multipath effect, which occurs in almost all technologies

for land-based and underwater communication, is a significant

factor that causes signals to fade quickly. Since the signals

from different paths arrive at different times at the receiving

unit, the superimposition of the signal results in deformation

or extreme fading of the received signal in the event of a phase

error, eventually leading to bit errors. As in acoustic

communication, it is generated in the optical underwater

channel, when an optical signal reaches the detector after

hitting several scattering objects or several reflections from

other underwater bodies. This eventually leads to the

dispersion of waveform time (time spreading) and reduces the

data rate due to inter-symbol interference (ISI).

The amount of multipath interference depends upon

system specifications and the propagation environment.

Owing to the very high speed of light, the impact of multipath

interference in UOWC is not as evident as it is in acoustic

communication.

Optical waves are reflected from the top to down of a

shallow water region and produce several signals at the

detector. The surface and bottom reflections can be overlooked

in deep oceans. Interference is suppressed using advanced

signal processing methods including channel equalization and

adaptive optics at the receiver.

Even though channel equalization for rapidly fluctuating

underwater channels looks to be a major problem, detailed

characterization of the underwater optical channel will aid in

the selection of appropriate characteristics of device

fabrication for robust and high-quality optical

communications. The authors' work in Refs [94] and [98]

focuses on the channel time dispersion that leads to ISI.

Polarized light is used to examine the influence of

transmission distance on time dispersion,[98] ISI is essential for

long-range transmission (50 m) at high data rates, according

to the findings (1 Gbps). In order to quantify channel time

dispersion in UOWC, the impact of device design features

such as transmitter beam divergence and receiver aperture size

is discussed.[94] The authors,[209] used the Monte Carlo

simulation method to assess UOWC and found that when

working over moderate distances, the channel time dispersion

can be ignored except for the highly turbid environment. As a

result, at distances that are mild, UOWC is capable of handling

high data rates. The performance of ISI on 25 m coastal water

at two different data rates ( 0.5 Gbps and 50 Gbps ) with spatial

diversity is investigated.[223]

Spatial diversity is shown to help reduce the impact of

multipath interference by partially compensating for ISI

degradation, especially at low data rates. Its efficiency,

however, deteriorates, particularly at high data rates.

6. Link configuration of UOWC

UOWC can be classified into four categories based on

connection configurations between nodes in UWSNs, see Fig.

4 below:

6.1. Point-to-point line-of-sight (LOS) configuration

The point-to-point LOS configuration is the most common at

UOWC. This approach necessitates careful alignment of the

transmitter and receiver.[16] In Fig. 4(a), as well as the use of a

coherent light source with a low divergence angle, such as a

laser. In pure water with little absorption and scattering, the

LOS approach works well for long-distance transmission.[224]

However, in the real underwater environment, where perfect

alignment is difficult, especially when the transmitter and

receiver are not fixed nodes, such as underwater autonomous

vehicles (AUVs) and remotely operated vehicles (ROVs), this

is a major problem.[175] Also, the presence of various

impediments, such as phytoplankton, rocks, as well as

turbidity and water turbulence increase the difficulty.[225,226]

The configuration of the LOS UOWC link is similar to that of

Fig. 4 Four link configurations of UOWC.

the Free Space Optical (FSO) communication system.[227]

Across a vertical distance of 200 meters’ maximum and a

horizontal radius of up to 40 meters, this device can attain a

data rate of up to 10 Mbps.[95]

6.2. Diffused LOS configuration

Diffused LOS utilizes diffused light sources with a large

divergence angle, such as high-power light emitting diodes

(LEDs). Fig. 4(b) shows how to broadcast UOWC from one

node to many nodes. This approach will reduce perfect

alignment requirements, where the transmitter and receiver are

not exactly oriented in the same line. Instead, molecular

scattering will reroute the transmitted radiation one or many

times before it reaches the detector. As a result, diffuse-LOS

communications relaxes position, acquisition, and tracking

constraints (PAT).[228] Nevertheless, the two primary

disadvantages of this configuration are the relatively limited

communication distances and reduced data rates. Furthermore,

due to the large interaction area with water, the diffused-light

based link struggles from aquatic attenuation as compared to

the point-to-point LOS arrangement.[180] The 532 nm laser and

a diffuser were used by Cochenour and Mullen[97] to produce

diffused light. A distributed UOWC link with a data rate of up

to 1 Gbps was built in a 7.72 m long water tank.

6.3. Retroreflector-based LOS configuration

The special implementation of the point-to-point LOS

configuration is the retroreflector-based LOS configuration, a

modulated retro-reflector that reflects the light that is

transmitted as shown in Fig.4 (c).[229] The information will be

encoded on the reflected light during this process. Since the

retroreflector end has no laser or other light sources (it has a

mirror), it is suitable for duplex UOWC systems and its

consumption power, volume, and weight will all be decreased

significantly. The disadvantage of this arrangement is that the

transmitted optical signal's backscatter can interfere with the

reflected signal, decreasing the system's signal-to-noise ratio

(SNR) and increasing the bit-error-rate (BER). Additionally,

the received signal would be reduced even more when the

optical signals travel through the underwater channel twice.[230-

6.4. Non-line-of-sight (NLOS) configuration

The NLOS configuration can be constructed either via light

reflection from the sea surface, or light scattering from tiny

particles in the water (e.g. plankton, particulates, dissolved

organic matters, inorganics),[233] see Fig. 4 (d). After lighting

the air-sea surface, the optical beam emitted by the source is

reflected then detected by the receiver.[234] It is transmitted to

the sea surface at an angle of incidence larger than the critical

angle by the transmitter, resulting in total internal reflection of

the light beam.[235] Before being detected by the receiver, the

photons generated by the transmitter will be redirected many

times by minute particles in the water.[224] That leads to the

NLOS link overcoming the strict pointing, acquisition, and

tracking (PAT) requirements of LOS UOWC.[234] To ensure

proper signal reception, the receiver should continue to face

the sea surface in an orientation that is nearly parallel to the

reflected light. The irregular sea surface slopes caused by wind

or other sources of turbulence are the main challenge of NLOS

links.[234] Meanwhile, the light is also absorbed and scattered

as it travels through the propagation medium. Light back to

the transmitter will also display these undesirable phenomena

and cause significant signal scattering.

The experimental NLOS UOWC links are focused on

underwater ranging and imaging applications. Alley et al.[236]

suggested employing a 488 nm blue laser as the illuminator in

an NLOS imaging system. Experimental findings show that

this NLOS configuration greatly increases the imaging SNR

compared to the traditional LOS imaging system. A related

experimental approach was proposed,[237] for underwater

detection, ranging, imaging and communication using

modulated pulse laser in NLOS arrangements.

Arnon et al.[235] suggested utilizing a reflected beam from

the sea surface to transmit data in the (NLOS) system.

Submarine networks may be configured using this NLOS

geometry. However, in this study, authors adopted an ideal

assumption of a stable sea surface and minimal scattering,

which may differ from practical systems. NLOS link based on

UV- laser has been utilized in emulated highly turbid harbor

water.[224] This configuration achieves a data rate of 85 Mb/s at

a transmission distance of 30 cm using on-off keying (OOK).

7. Modulation techniques

A procedure of combining a low signal with a high signal to

create a new one is known as modulation. It involves changing

a periodic waveform's parameter in order to use the signal to

send a message.

The modulation is called an analog modulation scheme if

the variation in the carrier parameter is continuous. If the

variation is discrete, then it called digital modulation

scheme,[238] (Figs. 5 and 6) shows these two types of

modulation.

Fig. 5 Types of analog modulation.

Fig. 6 Main types of digital modulation.

The common modulation formats for digital signaling are

shown in Fig. 7 below.

The selection of a particular transmitted symbol set or

modulation scheme is dependent on exhaustive knowledge

and in-depth understanding of the application system,[179] the

type of laser utilized, the system's target cost, the type of

channel present, and the system's goals.

On-off-keying (OOK), Binary PPM, 4-ary PPM, and

Manchester coded OOK are usually related with direct

detection systems, whereas the formats FSK., PSK, and ASK

are usually associated with coherent detection systems.[239]

UOWC channel modulation techniques have got a lot of

interest due to its potential to significantly affect the

performance of the system.[111] In UOWC, modulation is

categorized into two parts.[240]

1-Intensity modulation (IM)

2- Coherent modulation

7.1. Intensity modulation (IM)

(IM) depending on the presence or absence of a signal, there

Fig. 7 Types of modulation formats for digital signaling.

is no information about the phase. The modulation technique

used is determined by the kind of application and the intricacy

of the design.[47] Different modulation schemes may be

changed by optimizing the pulse rate, pulse width, and

frequency. The most common IM scheme in FSO

communication systems is on-off keying (OOK) which is a

binary level modulation.[241] The OOK is also possible to

implement in UOWC systems. Another common modulation

technique used in UOWC systems is the pulse position

modulation (PPM) scheme. If a direct detection receiver

detects the intensity-modulated signal, then the method is

considered to be intensity-modulated/direct detection (IM/DD)

or (non-coherent detection). Since IM/DD systems are cheaper

and less complex, they are commonly used in UOWC

systems.[47]

For both IM techniques (OOK) or (PPM), a lot of studies

are being conducted on it such as.[242,243] During (OOK)

transmission, an optical pulse that occupies part or entire bit

duration denotes a single data bit '1'. The absence of an optical

pulse, on the other hand, represents a single "0" data bit.

There are two pulse formats in OOK modulation scheme:

1- Return-to-zero (RZ) format: A pulse with a duration that

only occupies a part of the bit duration is described as "1".

2- Non-return-to-zero (NRZ) format: A pulse occupies the full

bit duration.

It has been shown that the RZ-OOK achieves greater

energy efficiency than the NRZ-OOK, but at less channel

bandwidth.[111]

The transmitted OOK signal suffers from different channel

fading because of the intense absorption and the OOK was

shown experimentally[105] using the modulated laser at 520 nm

over 7 m distance, to achieve 2.3 Gbps high-speed UOWC

system. for UOWC, various intensity modulation techniques

are investigated.[244] To test UOWC's feasibility, a low-cost

laser transmitter with OOK modulation schemes working at

(405 and 635 nm) was designed. The blue laser (405nm) has a

greater propagation distance and a higher data rate (reaching 1

Mbps) than the red laser (635), according to Ref.[96], which

was obtained using a PMT receiver. The PPM is a good option

for long-distance communication system,[245] and it is much

more energy efficient, also it does not need a dynamic

thresholding compared with OOK modulation, but it has lower

bandwidth usage rate and more complex transceivers. Many

variants of the PPM frameworks are used to increase the

wireless communication system's bandwidth efficiency, in Fig.

8.[246,247,248] It also explores the influence of the concentration

of chlorophyll and the distance of propagation. An updated

version of PPM with better bandwidth usage is

demonstrated.[249] The author implemented the single-chip

device PPM modulation to increase the synchronized and

encoding performance of the light beam in an underwater

climate.[250]

To increase higher bandwidth performance, more

complicated PPMs such as 8-PPM or 16-PPM can be used. An

updated PPM scheme was suggested by Sui et al.[126] for

UOWC. The same power efficiency and anti-noise output as

Fig. 8 Various frameworks of pulse position modulation (PPM).

the traditional PPM can be preserved by this updated PPM. It

has also enhanced the system's bandwidth utilization rate.

PPM was also used in many experimental UOWC

implementations in addition to theoretical studies. You will

find similar studies.[251,241] The dimensions of dissolved

particles in water, as well as turbidity, have a significant

impact on it. Also, multipath propagation leads to ISI due to

the reflection of the optical signal and restricts the bandwidth

of channel.[248] The performance of OOK modulation to reduce

the impact of underwater turbulence using MIMO in UOWC

is described.[223]

Coherent detection is the other method of detecting the

modulated optical signal. The local oscillator is used to

convert the optical carrier down to the baseband (homodyne

detection) or intermediate frequency (heterodyne detection).

This signal is then demodulated by the demodulation process

to the baseband. The signal level rises much above the noise

level of the electrical circuit due to the powerful local

oscillator field, which improves the system's sensitivity. In the

UOWC system, coherent systems are rarely employed because

of their complexity, consumption, and high cost, these reasons

making it an unacceptable choice for underwater

communication.[252]

7.2 Coherent modulation

Coherent modulations transmit information regarding the

amplitude, polarization or phase of optical carriers, as opposed

to direct IM systems. The optical carrier will combine with the

optical signals received on the receiver side and Implement

demodulation. The example of coherent modulation are

frequency-shift keying (FSK), Phase shift keying (PSK), and

differential phase-shift keying (DPSK). When IM (OOK /

PPM) is compared to coherent modulations, coherent

modulations provide improved receiver sensitivity, system

spectrum efficiency, and background noise rejection, but at the

cost of more implementation complexity and higher costs.[227]

A comparison was presented[253] between several schemes. It

shows the OOK modulation system is simple and economical,

but its BER performance was 10−2 for SNR = 25 dB, which

is very low. For evaluating the BER performance of these four

modulation techniques, a 470 nm blue laser at 2.59 mw output

power was used. It has been demonstrated that the (PPM) is

better for low power underwater applications, while PSK

offers good performances in terms of bandwidth, error

performance but with poor power efficiency.

(BPSK, QPSK, 8-Phase Shift Keying (8-PSK), 16-

Quadrature Amplitude Modulation (16-QAM), and 32-

Quadrature Amplitude Modulation (32-QAM)) are applied[93]

for turbid water conditions, providing data rates of up to 5

Mbps. It was able to submit 106 symbols per second and, in

a 3.6 m water tank. The initial speed was increased from 1

Mbps using BPSK to 5 Mbps using 32-QAM. A decision

feedback equalizer (DFE) is added to the phase shift silence

keying (PSSK)[254] and phase shift-PPM (PSPPM)[255] for low

power consumption in underwater sensor networks.

Subcarrier intensity modulation (SIM) is another type of

coherent modulation technique utilized in UOWC that has a

high spectrum efficiency but a low average power

efficiency.[47,256] An experimental UOWC system was

proved[103] that utilized SIM, the BER was shown to have been

lowered from 10-3 to 10-9.

Modulation can be performed directly or with the help of

an external modulator. Direct modulation is the easiest way to

actualize where the current driving the source of light is

directly modulated. Although direct modulation of lasers

through a pump source is straightforward, it restricts the data

rate and link range in the UOWC system by chirping.[257] The

non-linearities lead to relaxation oscillations in the case of

Solid-state lasers, avoiding the direct modulation of the

laser.[12] Experimentally, a high data rate underwater channel

up to 2.3 Gbps over 7 m using a directly modulated 520 nm

laser diode.[105]

External modulation is the process of a laser light

generating constant power passing via an external modulator

(a voltage-driven system). It's used to get modulated optical

power from the external modulator's output. These schemes

have the ability to use the source's full power. However, the

modulation range is limited by external modulators and

requires a relatively high drive current.[12] An externally

modulated laser with a wavelength of 532 nm is employed[94]

to achieve an optical underwater link of 1 Gbps. The

performance comparison of some various modulation

techniques is given in Table 4.

8. System design

The UOWC system generally consists of three fundamental

components, the transmitter unit, the water channel and the

receiver module. Fig. 9 shows the basic block diagram of

UOWC system. The optical signal is modulated by a

modulator in the transmitter part (Tx). The light source can be

a laser or LED. The modulated light beam includes the

required information, as well as projection optics (lens) and

beam guiding if necessary. The transmitted light beam enters

the sea through the platform window. The signal is distorted in

the water channel due to several factors, such as optical

turbulence (air bubbles, salinity gradient and temperature

gradient), dispersion, absorption and background noise. The

beam enters the window of the receiver after it has been

attenuated 86. A photodetector (PD) in the receiver side,

collects the transmitted optical beam by the receiver lens and

convert it to an electrical signal. The electrical signal is passed

through a signal processing unit and a demodulator 239.

Since the photodiode can only translate light intensity

variations into current changes. The next stage includes

cascading a trans-impedance amplifier to convert current to

voltage 239. In order to reduce the thermal and ambient noise

levels, the converted voltage signals will then pass through a

low pass filter 227. Finally, a PC or BER tester can collect and

analyze the recovered original data to evaluate some

significant performance parameters, such as BER 258.

8.1 Transmitter

A transmitter commonly used in UOWC, either laser diodes

(LDs) or light-emitting diodes (LEDs) sources 52, 97, 251,

259, 260. Depending on the need and taking into consideration

that underwater systems are limited in terms of power and

bulk, the choice of LED or laser in the blue-green region of

the spectrum can differ. In general, blue-green LEDs are

preferred for the buoy system working in shallow water. Laser-

based systems are suitable for systems operating in deep, clear

ocean water. In the blue-green region, laser or LED output

power varies from 10 mW to 10 W. When it comes to choosing

a source for the UOWC, both LEDs and lasers have

advantages and weaknesses 261. Lasers have fast switching

times and high optical power, but LEDs are inexpensive,

Table 4. UOWC modulation schemes. Reproduced with permission from Ref [179], Copyright International Journal of Advanced

Computer Science and Applications (IJACSA)).

Modulation Scheme Limitation Benefit

OOK Low energy efficient Low cost, Simple

SIM Complicated devices, Average power

efficiency Low cost, Increase system capacity

QAM High cost, Complex implementation Good response to noise, High spectral efficiency

PPM Complex transceiver, Low bandwidth High power efficiency

PoISK Low data rate, Short distance range High tolerance to turbulence

PSK High cost, Complex implementation High receiver sensitivity

DPM Complicated demodulation devices,

Error spread in demodulation High bandwidth efficiency

Fig. 9 Generic communication system block diagram.

simple, more reliable and less temperature-dependent 261. As

compared to lasers, the LED-based device is less vulnerable to

underwater effects due to its wide viewing angles. The

performance of the LED-based system is evaluated using

geometric effects such as beam divergence, receiver FOV, and

dynamic range. In the UOWC system, the implementation of

LED is cheaper and simpler; however, due to incoherent

optical beam and light spread in all directions, the relation

range is very limited. The communication range can be

expanded either by utilizing a powerful ability LED (working

in Watts) or by transforming the coverage in all directions into

one direction system using optical focusing or by applying

LEDs array 12.[262] A quasi-omnidirectional UOWC system is

realized by using a prismatic array with three high-power blue

LED modules to produce optical signals in different

directions.[263] Without using any digital signal processing

algorithms, data throughput of 22 Mbps may be reached across

a 10-m underwater channel. Furthermore, for 10-m, 30-m,

and 40-m underwater channels, the maximum net data rates

achievable using MRC and frequency domain equalization

(FDE) algorithms are 69.65 Mbps, 39.8 Mbps, and 29.85

Mbps, respectively.

Lasers are employed to meet the requirements for deep

subsurface communication because they have long ranges,

high power, high efficiency, high data rates and low latencies

12. First-ever connection using lasers involving planes and

submarines is detailed.[264]

The high-quality output of the coherent laser beam is

quickly degraded by turbulence and underwater scattering.

The laser-based UOWC system may reach a link distance of

100 m in clear water and 30 to 50 m in turbid water.[265]

LD offers a higher intensity of output power, improved

collimation characteristics, spectral narrowing range, and

switching speeds that are substantially faster compared to

LED. However, this comes at the cost of a greater price, a

shorter lifespan, and temperature sensitivity.[266] Therefore,

LDs are more suited for implementation in high-speed UOWC

applications that have strict alignment requirements. Optical

diffusers are implemented in many LD-based UOWC

applications to minimize system pointing requirements.[94,267,268]

In comparison between (Diffused LD and LD without

diffusers) based UOWC systems, diffused LD- will benefit

from both high speed and relatively low direction

requirements.[269] LEDs, on the other hand, can be employed in

a variety of diffused UOWC applications that need short-range,

low-speed transmission due to their lower output power

intensity, greater divergence angles, and lower bandwidths. A

design and tradeoff for a directional and omnidirectional

UOWC link using LD and arrayed LEDs are provided.[93]

Furthermore, lasers can support high data rates because of

their wide bandwidth (>1 GHz), as opposed to LEDs, which

have a bandwidth of less than 200 MHz. The laser-LED

difference is displayed in Table 5.

8.2 Receiver

The light detection system or a receiver is one of the main

components of UOWC. The design of a receiver to operate in

the ocean environment is dissimilar to the design of an

ordinary communication receiver. In optical receivers, there

are four types of photodetectors can be used as shown in Fig.

10. The most functional OWC systems use PIN photodiode or

avalanche photodiode (APD) as receiver.[242]

Some specific requirements have to be met by the UOWC

receiver system to address the effects of noise and attenuation.

The receiver's most significant parameters are large FOV, high

gain, fast response time, low cost, small size, high reliability

and high sensitivity and responsivity at the operating

wavelength, and high SNR.[242]

The Photomultipliers (PMT), semiconductor photo-

sensors, and biologically based quantum photo-sensors are the

most popular photo-sensors in the blue-green region,[12] see Fig.

Table 5. Laser and LED characteristics in UOWC.

Parameter Laser diode (LD) Light emitted diode (LED)

Operating wavelength 450-570 nm (blue-green) region 450-570 nm (blue-green) region

Modulation bandwidth Up to GHz (higher) Up to MHz (lower)

Output Power intensity

(received optical power) Higher power Low power = 1W (unless arrayed)

Divergence of beams Narrow spread ( large divergence)

Cost expensive Low cost

Speed Higher speed Lower speed

Range Long range Short range

lifetime Medium Long

Temperature Dependency Highly dependent on temperature Less dependence

Fig. 10 Main Types of Photodetectors.

When choosing a photodetector, there are some

considerations to take. Photomultipliers are high sensitivity

and speed. Although phototransistors and photoresistors

function well as light-activated switches, they are too slow for

communications.

Fast response PIN photodiodes have a fast response time,

cheap cost, unity gain, and strong ambient light tolerance, but

APD has a broad internal gain and excellent quantum

efficiency (70 - 90%).[239] The most significant difference

between these two devices is the noise performance. Thermal

noise is the most common type of noise in PIN photodiodes,

whereas the output for APDs is most common restricted by

shot noise.[227] As APD can provide high current gain, it can be

carried out at the cost of more complex auxiliary circuits in

longer UOWC links (ten meters).[270,271] APD is potentially

faster and has an internal gain greater than PIN, but requires

high bias voltage, complicated control circuits and ambient

noise sensitivity.[12] In addition, the quantum efficiency of

APD depends on the material thickness, e.g. in the 400-500

nm range, silicon has very low sensitivity. For this reason, the

PIN photodiode seems to be a more promising technology at

shorter wavelengths than APD for the UOWC system.[12]

Fig. 11 Types of Photo-Sensors in the blue-green region.

APD was used as a receiver to demonstrate a 1 Gbps data

rate over a 2 m propagation path using a 532 nm laser at 7 W.[94]

Using PIN and APD receivers, three different models for long,

short and hybrid propagation ranges were explored.[99] It has

also been applied in many UOWC experiments in addition to

PIN diodes and APDs.[272,62,260,273-276]

Photomultiplier tubes (PMT) is a type of vacuum tube that

is very sensitive to light, greater optical gain, lower noise

levels, high-frequency response, and a wide storage area

compared to photodiodes, but it suffers from high supplies of

voltage (on the order of 100 volts) and high unit costs.[277]

However, because of the large scale, increased power

consumption, and fragility, PMTs are a poor UOWC option.[278]

PMT is used to create a laboratory setup communication

link for 500 kbps in return-to-zero format and 1Mbps in the

non-return-to-zero form at a distance of 3.66 m along with a

variable gain amplifier on the receiver.[96] The omnidirectional

transmission and receiving of the PMT optical signal in

conjunction with the hemispherical diffuse for the 100 m

range.[279]

Biologically, photosynthetic life underwater is exploited

by spiral quantum photo-sensors.[50,55] The faint Sunlight and

lighting from other hydrothermal vents can be absorbed and

processed by biological life underwater. Their biological

organism captures solar radiation and uses quantum coherence

to move the energy to the reaction center where the

photosynthesis biochemical reaction starts.[12] Much research

is underway to invent quantum devices that are biologically

inspired and function effectively in the underwater

environment.[280-283] The comparison between Semiconductor

photo-sensors, PMT, and Biologically-inspired quantum

photo-sensors are presented in Table 6.

In a recent study,[284] the single photon avalanche diode

(SPAD) was utilized as the receiver in a long-range (UOWC)

system. It's a photodetector like (APD) but it can detect fewer

photons (reach to single photon) with a higher temporal

resolution, this mode of operating is called Geiger’s

mode.[140,285] The authors suggested a technique to obtain the

time slot synchronization clock (TSSC) from the received

discrete photon-counting pulses and to recover the data to

minimize the number of photons needed to receive 1 bit data.

Using 256-PPM, a favorable performance was obtained which

is of 0.875 photons/bit with a symbol error rate (SER) of 1.8

× 10-3.

Table 6. Comparison for various types of photo-sensor.

Semiconductor photo-sensors PMT

Biologically inspired

quantum photo-sensors PIN APD

fast response

Low cost

Unity gain and

good tolerance

to ambiance

High current gain is

achievable, Longer UOWC

links (tens of meters) can be

constructed, albeit at the cost

of more complicated auxiliary

circuits.[180]

Internal gain is significant,

and quantum efficiency is

high.[12]

The quantum efficiency of

APD depends upon the

thickness of the material.

PMT benefits from higher sensitivity,

higher optical gain and lower noise

levels.[180]

Take advantage of

photosynthetic life

underwater.[12]

Highly efficient candidates for

The dominant

noise is thermal

noise[227]

The performance is mainly

limited by shot noise.[227]

Faster than PIN and has a

greater internal gain, but

requires a larger bias voltage,

sophisticated control circuitry,

and is more susceptible to

ambient noise.[12]

PMT is oversensitive to shocks and

vibration. Overexposure to light has the

potential to damage it.

PMTs are also significantly more expensive

than photodiodes.[180]

High voltage sources (on the order of

hundreds of volts) and a high unit cost are

disadvantages.[180]

They are a poor candidate for UOWC due to

their large size, higher power consumption,

and fragility.

8.3 The underwater wireless optical channel

In optical wireless communications, water is the channel of

communication through which the optical beam is propagated,

and thus the passing optical beam is affected by the properties

of water (inherent and apparent). In order to know the behavior

of optical beam propagation underwater and the challenges it

faces, the channel must be accurately modelled. Several

previous studies dealt with the classification of current

channel models based on the inherent optical properties and

their representation by Beer-Lambert law or by using the

volume scattering function or by using the radiative transfer

equation (RTE) and solving it in an approximate analytical or

numerical (the most famous of which is the Monte Carlo

simulation) method.[286-288] In a recent study by us, the channel

models were classified based on the type of effect that was

taken into account when proposing the models and it includes

the effects of absorption and scattering or turbulence, or all of

them together.

As a result, the optical power received is decreased, which

in turn reduces the communication system's signal-to-noise

ratio (SNR).[228] The channel impulse response is one of the

most important characteristics for determining the channel's

performance, and it has been examined by numerous

researchers to define UOWC links.[52]

9. Channel coding of UOWC

Channel coding (also known as error control coding) is used

in communication systems to detect and correct symbols that

have been received incorrectly. When digital data are

transmitted across a noisy channel, there is always a

probability that the received data contain errors.[289] Forward

error correction (FEC), which is one of the most commonly

used error control systems, is a data transmission process that

adds extra information to the original messages that can then

be used to detect and correct errors without the need for

retransmissions.[290] Both at the transmitter and the receiver,

channel coding is carried out. Channel coding is referred to as

an encoder on the transmission side, where extra bits (parity

bits) are added to the raw data before modulation. Channel

coding is known as the decoder on the receiving side.[291] FEC

channel coding schemes such as Turbo, low density parity

search (LDPC), Reed Solomon (RS), convolutional, and

others are used in UOWC systems to reduce the impacts of

underwater attenuation.[292]

9.1 Principles OF Forward Error Correction (FEC)

Forward error correction coding is a process of the addition of

error correction codes to the original data and it is capable of

enhancing the power efficiency of a communication system.[290]

Wireless channels suffer from noise, interference and fading

during transmission, which causes errors, so the transmitter

adds extra information to solve this before the data is sent

(adding extra bits to the information data at the transmitter).

The important feature of the FEC is that there will be no

retransmission of data.[293] FEC may be a faster and more

suitable option when propagation delay is a factor. The

addition of check bits, on the other hand, would usually

increase the transmission bandwidth or message delay (or

both).[294]

9.2 FECs and their function

A digital information source sends a message (data word D)

containing k bits of data to an encoder in a forward error-

correction coding (FECC) communication system. The

encoder outputs an n-bit codeword C after adding r bits of

check data. There is some noise and corruption in the

transmission, which causes errors. On the receiving end, a

suitable decoder may be used to recover the original data

sequence,[290] this can be seen in Fig. 12.

Fig. 12 How FEC works.

Fig. 13 Forward error correction coding.

An (n, k) block erasure code transforms k source data into

a group of n coded data, with any k of the n encoded data

allowing the original source data to be reconstructed. The first

k data in each group are usually identical to the original k

source data, while the remaining (n – k) data are identified as

parity data,[295] see Fig. 13.

9.3 Classification of Channel Codes

The channel codes can be classified into different categories

as seen in the Fig. 14.

9.4 Types of FEC

There are several different forward error correcting codes

in the FEC code family that are used in varying situations.

Block codes and convolutional codes are the two major types

of FEC codes,[290] see Fig. 15.

(A) Block Codes

The principle of coding data in blocks dates back to

Shannon’s original 1948 work.[296]

A message block of k knowledge symbols is uniquely

mapped to n coded channel symbols in block coding, resulting

in a code word.[258] Block codes include Reed-Solomon coding,

Golay, BCH, low-density parity-check (LDPC) code, and

Hamming codes.

Fig. 14 various types of channel coding.

Fig. 15 Classification of FEC techniques.

Fig. 16 depicts a block coder with k information digits

going in and n digits coming out after the encoding process. K

message bits and r redundant (parity bits) verification bits

make up the n-bit codeword. According to the number of n

output code bits and k input data bits, codes are designated

with the notation (n, k).[290] The code rate ® is a particularly

important value, which is identified as[258]:

𝑅 = 𝑘

𝑛 (34)

(B) Convolutional Codes

In 1955, Elias suggested convolutional codes, which function

differently than block codes.[297] Convolutional encoders

produce n output bits for every k input bits, but instead of

using blocks, they use a sliding window of data to do so. In

this case, k and n are small integers, and k < n in functional

codes is similar to block codes. The encoded message now

depends on the current input message, which is made up of k

symbols, as well as m previous messages, each of which is

made up of k symbols. The memory order of the code is

represented by this value, m. Redundancy in convolutional

codes is a function of the encoder’s memory order as well as

the number of parity bits in the codes. Another essential

parameter is the code’s restriction length, which is denoted by

K and equals m + 1.[258] Convolutional codes are a form of

error-correcting code that can be continuously encoded and

decoded, making them ideal for real-time applications.[290]

Fig. 16 The block coder’s procedure.

In UOWC, several articles have compared the

performance of various coding schemes. Everett conducted

channels estimating for various seawater conditions using an

experimental UOWC testbed,[258] and he concluded that the

white Gaussian noise channel additive is a good

approximation for the Free Space Optical (FSO)

underwater channel.[180]

9.5 Related works

Many classical block codes have been applied to the UOWC

due to their simplicity and strength. The Reed-Solomon (RS)

FEC (255, 129) code was the first block code used in the

UOWC system.[89] The 405 nm laser diode and RZ OOK

modulation were used in this system to obtain a 500 kbps

UOWC link in a 3.66 m long water tank. The experimental

results indicated that, compared to an uncoded OOK system,

the coded system would decrease the needed power to reach a

BER of 10-4 by roundabout 8dB.

In the upgraded system[88] by the same research group[89]

from North Carolina State University modified their system in

a seven-meter long water tank, a 5-Mbps UOWC link using

the RS code was built. The experimental results show that at

the (255,129) RS and (255,223) RS codes will improve the

SNR of received signals by 6 and 4 dB, respectively and BER

of 10−6. Other UOWC experiment that makes utilization of

(2720, 2550) RS and SIM are discussed.[103] In (2720, 2550)

RS code performed error correction, decreasing the BER from

1.5 ×10-3 to 10-9.

In addition to the RS code, UOWC systems have also

introduced other classical block code and error-detecting code

such as Bose-Chaudhuri-Hocquenghem (BCH) code and

cyclic redundancy control (CRC) code to increase the BER

output in low SNR underwater environments.[180] Wang and

Zheng[298] simulated the anti-noise efficiency of BCH and RS

codes using simple OOK modulation. Numerical results

revealed that the RS code outperformed the BCH code in

terms of error correction but at the cost of a lower transmission

data rate. To maintain the robustness of the UOWC system,

error correction at the packet level instead of using a single

layer of FEC code for byte-level error correction, coding

methods were suggested. A two-layer error correction coding

system was employed in UOWC video transmission system

by Doniec et al.[299,300]

While block codes are easy to enforce, they are not capable

of providing UOWC with optimal performance, especially in

environments with severe interference. More complex and

efficient channel coding schemes are therefore used, such as

low-density parity-check (LDPC) code and Turbo code.[180]

The LDPC code is a highly efficient linear block code. It is

based on sparse parity check matrices and can obtain error

correction efficiency close to the Shannon limit.[227]

In order to create a block code, it includes two or more

convolutional codes and an interleaver that can also attain a

BER near the Shannon limit. While several studies on the

implementation of LDPC and Turbo codes in the FSO

communication system have been suggested, there is indeed a

lack of research on the use of LDPC and Turbo codes

applications in the UOWC.[180]

Everett also showed the achievement of RS, LDPC, and

Turbo codes in UOWC systems both theoretically and

experimentally.[168] A researcher thoroughly discussed the

technique of the RS, LDPC, and Turbo codes and differing

their achievements at UOWC codes in terms of BER, power

quality, and communication distance extension. Paper[168]

offers a comprehensive description of channel coding

methods implementation in UOWC.

Convolution code and Turbo[301] code are used to enhance

the performance of a MIMO-OFDM system.[302] The

performance of (UOWC) device using (OOK) modulation at a

data rate of 500 Mbps across a 30 m link range is

investigated.[152] To reduce the effects of weak oceanic

turbulence and beam attenuation, transmit/receive diversity

schemes such as Multiple-Input Single-Output (MISO),

Single-Input Multiple-Output (SIMO), and Multiple-Input

Multiple-Output (MIMO) techniques with and without RS-

coding were used.[152] The performance of the links is

calculated in the presence of (63, 51) RS-code (MIMO) and

compared to the performance of the uncoded (SISO) system

and when the two competing schemes are used, a decrease in

transmit power is observed to achieve a bit error rate (BER)

of 10-5.[152]

10. Performance evaluation

Here we discuss some key metrics that are commonly used to

assess the performance of the communication system. (BER)

is a powerful metric that provides an end-to-end evaluation of

any communication system. It gives an assessment of the

entire system, the transmitter, the channel, and the receiver

and is defined as the ratio of the error bits to the total number

of bits.

𝐵𝐸𝑅 =𝐸𝑟𝑟𝑜𝑟 𝑏𝑖𝑡𝑠

𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑏𝑖𝑡𝑠 (35)

BER can also be defined in terms of signal to noise ratio or

(Error probability, EP)

𝐸𝑃 =1

2(1 − 𝑒𝑟𝑟𝑜𝑟 𝑓𝑢𝑛𝑐𝑡𝑖𝑜𝑛)√

𝐸𝑏

𝑁0 (36)

where 𝐸𝑏 is the energy of one bit and 𝑁0 is the noise in 1Hz

bandwidth. The ratio 𝐸𝑏

𝑁0⁄ is a representation of the signal

to noise ration.

Transmission Loss: Transmission loss Y of a light signal

per meter underwater is defined as the ratio of the loss due to

water to the transmission distance:

𝑌 =𝐿𝑜𝑠𝑠 𝑑𝑢𝑒 𝑡𝑜 𝑤𝑎𝑡𝑒𝑟

𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 (37)

The total loss and the loss due to water can be obtained by

finding the difference between the input power, that is sent

from the source, and the output power that is received at the

receiver.

𝑃𝑜𝑤𝑒𝑟𝑖𝑛𝑝𝑢𝑡 − 𝑃𝑜𝑤𝑒𝑟𝑜𝑢𝑡𝑝𝑢𝑡 = 𝑇𝑜𝑡𝑎𝑙 𝑙𝑜𝑠𝑠 =

𝐿𝑜𝑠𝑠 𝑑𝑢𝑒 𝑡𝑜 𝑤𝑎𝑡𝑒𝑟 + 𝑜𝑡ℎ𝑒𝑟 𝑙𝑜𝑠𝑠 𝑠𝑜𝑢𝑟𝑐𝑒𝑠 (38)

Transmission quality: The transmission quality contains all

information about the damage that occurred to the signal due

to all sorts of attenuation sources.

Another evaluation parameter is the interplay between the

transmission quality and the BER. Understanding this

relationship between the transmission quality and EBR is

important to characterize the performance of the system and it

can be summarized using the simple diagram Fig. 17 shown

below:

Fig. 17 Transmission quality versus BER.

In region A, the transmission quality is low, here the EBR

value is a good representation of the quality of the transmitted

signal. In region B, when the EBR value increases above a

certain threshold, its value is not a good representation of the

signal quality. In this region, the system is not able to measure

the noise. Hence, in this case, the modulation error ratio

(MER), is used to evaluate the performance. MER is defined

as the log of the ratio of the root mean square power of the

error to root mean square of the reference signal.[224,303-305]

𝑀𝐸𝑅 = 10 𝑙𝑜𝑔𝑅𝑀𝑆 𝐸𝑟𝑟𝑜𝑟

𝑅𝑀𝑆 𝑣𝑒𝑐𝑡𝑜𝑟 (39)

11. Basic characterization parameters of the main parts in

UWOC system

Transmitter unit, as discussed in section 8.1, the transmitter is

composed of an information source, a light source, a

modulator, and a lens. LED and DL are common light sources.

Lasers are generally characterized by evaluating the lasing

spectrum first which contain the fundamental mode

wavelength and the secondary or side wavelength bands. High

resolution laser, interferometer-based wavelength meters are

typically used to measure the laser spectrum. The laser

bandwidth which is, an important parameter of a laser, the

width of the optical spectrum can also be measured using these

interferometric based meters. The optical power current

voltage (LIV) curve is another very crucial parameter to

determine the lasing threshold current, the maximum

operating current, the turn-on voltage, and the maximum

operating voltage. This curve can be measured using a digital

laser controller that could scan the laser current and measure

the corresponding voltage and power. Laser noise is another

characterization parameter, such as the white quantum noise,

that is due to spontaneous emission, and other technical noise

sources such as mechanical vibration noise, temperature

fluctuation noise. The modulator in the transmitter unit is used

to perform intensity or coherent modulation as mentioned in

section 7. The common modulators used for these purposes are

the acousto-optic modulators and electro-optic intensity

modulators.

For the receiver unit, the reader is referred to section 8.2

for a detailed discussion about the various photodetectors and

photomultipliers. The water channel can be characterized by

measuring the particle size distribution, this can be done using

the Zetasizer. This technology uses the dynamic light

scattering (DLS) principle to measure the diameter of the nano

and microparticles. The particle size distribution gives

information about the scattering mechanisms that are expected

to play in the water channel. Mie and Rayleigh scattering have

been discussed in section 5.2. Also, the VSF and attenuation

coefficient are key characterization parameters of the water

channel, we have given a description for them in section

3.1.[224,303-305]

12. Conclusion

Due to the frequent usage of the aquatic environment in many

essential and crucial applications such as underwater

environmental monitoring, marine research, calamities, and

military activities, there is a growing global interest in

exploring the underwater environment. Underwater wireless

communication (UWC) is the transmission of data in the

aquatic environment through a randomly fluctuating

underwater channel, utilizing various technologies such as

acoustic waves, radio frequency (RF), and optical waves,

despite the diverse conditions of the undersea environment.

This paper provides a comprehensive survey of the various

(UWC) approaches, and also other methods for improving

system performance, as well as current relevant research.

UWOC operates and provides the best efficiency within the

blue-green region of the electromagnetic spectrum. UWOC

has a substantially higher transmission bandwidth and hence

provides a much higher data rate than its other counterparts,

which is a key aspect that makes optical communications

superior to other technologies. Different noise sources,

inherent optical characteristics like absorption and scattering,

and apparent optical properties have an impact on the UWOC

system. This study presents the challenges and advantages of

underwater light propagation, modulation scheme, coding

techniques, and the fundamental physical processes that affect

them. The link configurations and system design are

considered in this paper, with a focus on the different types of

linking methods that can be used to provide underwater

communications, and also the benefits and drawbacks of each

system, as well as the conditions in which each type is utilized.

In addition, the major parts and components of the underwater

optical communication system are discussed in detail.

Moreover, this survey provides an overview of several UOWC

systems that will be given until 2021, with a description of

their system parameters.

13. Future directions

As described in the preceding sections, UWOC's academic and

industry research initiatives have already become a reality.

Nevertheless, this field of study is still in its beginning phases

in many areas, and there are still unsolved issues. To gain a

deeper understanding of the underwater environment and

channel characterization, extensive field investigations and the

utilization of testbeds are required. In the following points,

several potential research challenges at UWOC are mentioned.

➢ Link misalignment is an unavoidable occurrence, as

stated in section 6. Although a few research projects, on smart

transceivers for overcoming link misalignment, have been

proposed, extremely intelligent UWOC transceivers are still

needed.

➢ For UWOC transceivers, more research and study of

novel theoretical models (including statistical and numerical)

are necessary to fully understand laser beam propagation over

a randomly varying underwater channel. Also, most

theoretical UWOC research has not effectively addressed the

effects of transceiver noise on UWOC. The noise model of

UWOC transceivers must be investigated and implemented.

➢ With regards to modulation and coding techniques, prior

research has covered several matching schemes and produced

good results, but modifying the modulation and coding

scheme to react to real-time changes in the link remains a

challenge. Adaptive modulation or coding techniques for

UOWC has been investigated by few implementations. As a

result, various transmission schemes for UOWC systems must

be proposed to extend the system's coverage area and improve

its performance. When a mechanism exists to adaptively

switch modulation and coding schemes based on water

turbidity, the system will save a significant amount of energy

that is necessary for decoding complexity, resulting in a longer

cruising period.

➢ There has only been a few research on UWOC networks

thus far. Novel efficient network protocols must be devised

because of the particular characterization of wireless optical

channels in an underwater environment.

Acknowledgment:

This work was supported by the Deanship of Scientific

Research (DSR), King Abdul Aziz University, Jeddah. The

authors, therefore, gratefully acknowledge the DSR technical

support.

Conflict of interest

There are no conflicts to declare.

Supporting information

Not applicable.

References

[1] N. Saeed, A. Celik, T. Y. Al-Naffouri, M.-S. Alouini, Ad Hoc

Netw., 2019, 94, 101935, doi: 2019.101935.

[2] X. Sun, C. H. Kang, M. Kong, O. Alkhazragi, Y. Guo, M.

Ouhssain, Y. Weng, B. H. Jones, T. K. Ng, and B. S. Ooi, J. Light.

Technol., 2020, 38, 421-431, doi: 10.1364/JLT.38.000421.

[3] T. Fatma Abdalkarim, M. Universiti Tun Hussein Onn, E.

Fakulti Kejuruteraan Elektrik dan, Open ocean underwater

wireless optical communication: chlorophyll and depth

dependent variation in attenuation, Universiti Tun Hussein Onn

Malaysia, Batu Pahat (2015).

[4] Y. Li, S. Wang, C. Jin, Y. Zhang, T. Jiang, IEEE Commun. Surv.

Tutor., 2019, 21, 2466-2487, doi:

10.1109/COMST.2019.2897610.

[5] H. Ma, E. Liu, R. Wang, X. Yin, Z. Xu, X. Qu, B. Li, IEEE

Trans. Veh. Technol., 2019, 69, 3449-3453, doi:

10.1109/TVT.2019.2963357.

[6] K. Arunkumar, C. R. Murthy, IEEE Trans. Signal Process.,

2020, 68, 2435-2448, doi: 10.1109/TSP.2020.2983830.

[7] C. P. Gage, Towards a Modular, Low-Power, Low-Cost, and

High-Speed Underwater Optical Wireless Communication

Transmitter, UC San Diego Electronic Theses and Dissertations,

(2019).

[8] M. F. Ali, D. N. K. Jayakody, T. D. P. Perera,K. Srinivasan, A.

Sharma, and I. Krikidis, Underwater communications: Recent

advances, 2019.

[9] R. Urick, Principles of underwater sound: Peninsula. Los

Altos, 1983.

[10] B. Truax, Acoustic communication, Greenwood Publishing

Group, 2001.

[11] A. Quazi, W. Konrad, in IEEE Commun. Mag., 1982, 20, 24-

[12] H. Kaushal, G. Kaddoum, IEEE Access, 2016, 4, 1518-1547,

doi: 10.1109/ACCESS.2016.2552538.

[13] R. E. Williams, H. F. Battestin, J. Acoust. Soc. Am., 1971, 50,

1433-1442, doi: 10.1121/1.1912785

[14] M. Stojanovic, L. Freitag, M. Johnson, paper presented at the

Oceans' 99. MTS/IEEE. Riding the Crest into the 21st Century.

Conference and Exhibition. Conference Proceedings (IEEE Cat.

No. 99CH37008), 1999, doi: 10.1109/OCEANS.1999.805007.

[15] W. Li, J. C. Preisig, IEEE J. Ocean. Eng., 2007, 32, 927-939,

doi: 10.1109/JOE.2007.906409.

[16] M. Stojanovic, paper presented at the 2008 IEEE

International Conference on Acoustics, Speech and Signal

Processing, 2008, doi: 10.1109/ICASSP.2008.4518853.

[17] A. Vlasenko, P. Korn, J. Riehme, U. Naumann, Mon.

Weather Rev., 2014, 142, 2502-2520, doi: 10.1175/MWR-D-13-

00205.1.

[18] Y. R. Zheng, paper presented at the MILCOM 2007-IEEE

Military Communications Conference, 2007, doi:

10.1109/MILCOM.2007.4454811.

[19] M. Stojanovic, IEEE J. Ocean. Eng., 1996, 21, 125-136, doi:

10.1109/48.486787.

[20] A. Zielinski, Y.-H. Yoon, L. Wu, IEEE J. Ocean. Eng., 1995,

20, 293-299, doi: 10.1109/48.468243.

[21] H. Ochi, Y. Watanabe, T. Shimura, JPN J. Appl. Phys., 2005,

44, 4689, doi: 10.1143/jjap.44.4689

[22] H. Song, W. Hodgkiss, J. Acoust. Soc. Am., 2013, 134, 905-

908, doi: 10.1121/1.4812762.

[23] F. Frassati, C. Lafon, P.-A. Laurent, J.-M. Passerieux, paper

presented at the Europe Oceans 2005 Conference, 2005,doi:

10.1109/OCEANSE.2005.1513163.

[24] B. Li, S. Zhou, M. Stojanovic, L. Freitag, P. Willett, IEEE J.

Ocean. Eng., 2008, 33, 198-209, doi: 10.1109/JOE.2008.920471.

[25] B. S. Sharif, J. Neasham, O. R. Hinton, A. E. Adams, IEEE

J. Ocean. Eng., 2000, 25, 52-61, doi: 10.1109/48.820736.

[26] M. Stojanovic, Low complexity OFDM detector for

underwater acoustic channels, IEEE, 2006.

[27] Y. V. Zakharov, V. Kodanev, paper presented at the 2000

IEEE International Conference on Acoustics, Speech, and Signal

Processing. Proceedings (Cat. No. 00CH37100), 2000, doi:

10.1109/ICASSP.2000.861150.

[28] A. Song, M. Stojanovic, M. Chitre, IEEE J. Ocean. Eng.,

2019, 44, 1-6, doi: 10.1109/joe.2018.2883872

[29] C. Pelekanakis, M. Stojanovic, L. Freitag, paper presented at

the Oceans 2003. Celebrating the Past. Teaming Toward the

Future (IEEE Cat. No. 03CH37492), 2003, doi:

10.1109/OCEANS.2003.178494.

[30] A. Goalic, J. Labat, J. Trubuil, S. Saoudi, D. Rioualen, paper

presented at the Proceedings of OCEANS'94, 1994, doi:

10.1109/OCEANS.1994.364247.

[31] J. H. Fischer, K. R. Bennett, S. A. Reible, J. H. Cafarella, I.

Yao, paper presented at the OCEANS 92 Proceedings@

m_Mastering the Oceans Through Technology, 1992 of

Conference, doi: 10.1109/OCEANS.1992.607644.

[32] X. Che, I. Wells, G. Dickers, P. Kear, X. Gong, IEEE

Commun. Mag., 2010, 48, 143-151, doi:

10.1109/MCOM.2010.5673085.

[33] H. Esmaiel, Z. A. H. Qasem, H. Sun, J. Qi, J. Wang,Y. Gu,

IET Comm., 2020, 14, 3394-3403.

[34] S. Li, H. Sun, H. Esmaiel, Sensors, 2020, 20, 4457, doi:

10.3390/s20164457

[35] Z. A. Qasem, J. Wang, X. Kuai, H. Sun, H. Esmaiel, IEEE

Wirel. Commun. Lett., 2021, 10, 1886-1889, doi:

10.1109/LWC.2021.3085020.

[36] Z. A. Qasem, H. A. Leftah, H. Sun, J. Qi, H. Esmaiel, IEEE

Syst. J., 2021,1-12,doi: 10.1109/JSYST.2021.3052470.

[37] Z. A. H. Qasem, H. Esmaiel, H. Sun, J. Qi, J. Wang, Sensors,

2020, 20, 6134, doi: 10.3390/s20216134

[38] N. U. R. Junejo, H. Esmaiel, H. Sun, Z. A. H. Qasem, J.

Wang, Symmetry, 2019, 11, 711, doi: 10.3390/sym11050711.

[39] H. Hussein, H. Esmaiel, D. Jiang, Electron. Lett., 2018, 54,

907-909, doi: 10.1049/el.2018.0948

[40] Z. A. H. Qasem, H. Esmaiel, H. Sun, J. Wang, Y. Miao and

S. Anwar, Sensors, 2019, 19, 1519, doi: 10.3390/s19071519.

[41] H. Esmaiel, Z. A. Qasem, H. Sun, J. Wang, N. U. Rehman

Junejo, Sensors, 2019, 19, 5271, doi: 10.3390/s19235271

[42] H. Esmaiel, D. Jiang, Electron. Lett., 2014, 50, 650-652, doi:

10.1049/el.2014.0466.

[43] H. Esmaiel, D. Jiang, Wirel. Pers. Commun., 2017, 96, 1577–

1593, doi: 10.1007/s11277-017-4257-5.

[44] Z. A. H. Qasem, H. A. Leftah, H. Sun, J. Qi, J. Wang, H.

Esmaiel, Veh. Commun., 2021, 28, 100314, doi:

10.1016/j.vehcom.2020.100314.

[45] D. Pompili, I. F. Akyildiz, IEEE Commun. Mag., 2009, 47,

97-102, doi: 10.1109/MCOM.2009.4752684.

[46] P. Wang, C. Li, Z. Xu, J. Light. Technol., 2018, 36, 2627-

2637, doi: 10.1109/JLT.2018.2819985.

[47] A. S. Hamza, J. S. Deogun, D. R. Alexander, IEEE Commun.

Surv. Tutor., 2018, 21, 1346-1382, doi:

10.1109/COMST.2018.2876805.

[48] J. Partan, J. Kurose, B. N. Levine, SIGMOBILE MC2R,

2007, 11, 23-33, doi: 10.1145/1347364.1347372.

[49] W. W. Au, P. E. Nachtigall, J. L. Pawloski, J. Acoust. Soc.

Am., 1997, 101, 2973-2977, doi: 10.1121/1.419304.

[50] H. Brundage, Designing a wireless underwater optical

communication system, Massachusetts Institute of Technology,

[51] M. F. Ali, D. N. K. Jayakody, Y. A. Chursin, S. Affes, S.

Dmitry, Arch. Comput. Method. Eng., 2020, 27, 1379-1412, doi:

10.1007/s11831-019-09354-8.

[52] F. Jasman, Modelling and Characterisation of Short Range

Underwater Optical Wireless Communication Channels,

University of Warwick, 2016.

[53] J. R. Apel, Principles of ocean physics, Academic Press,

[54] H. M. Oubei, C. Shen, K. H. Park, A. Kammoun, T. K. Ng,

M. S. Alouini, B. S. Ooi, paper presented at the 2017 22nd

Microoptics Conference (MOC), 2017, doi:

10.23919/MOC.2017.8244482.

[55] C. M. Gussen, P. S. R. Diniz, M. L. R. Campos, W. A.

Martins, F. M. Costa, J. N. Gois, J. Commun. Inf. Sys., 2016, 31,

242-255.doi: 10.14209/jcis.2016.22

[56] Y. Chen, W. Y. Pan, H. Y. Peng, H. Q. Zhang, paper presented

at the Proceedings of the 9th International Symposium on

Antennas, Propagation and EM Theory, 2010, doi:

10.1109/ISAPE.2010.5696513.

[57] R. L. Dowden, R. H. Holzworth, Y. C. J. Rodger, J.

Lichtenberger, N. R. Thomson, A. R. Jacobson, E. La, J. B.

Brundell, T. J. Lyons, S.O. Keefe, Z. Kawasaki, C. Price, V.

Prior, P. Ortiga, P J. Weinman, Y. Mikhailov, O. Veliz, X. Qie, G.

Burns, A. Collier, O. P. Junior, R. Diaz, C. Adamo, E. R. Williams,

S. Kumar, G. B. Raga, J. A. Rosado, E. E. A. Vila, M. A. Clilverd,

T. Ulich, P. Gorham, T. J. G. Shanahan, I. T. Osipowicz, G. Cook,

and Y. Zhao, IEEE Antenn. Propag. Mag., 2008, 50, 40-60, doi:

10.1109/MAP.2008.4674710.

[58] R. K. Moore, IEEE Spectrum, 1967, 4, 42-51, doi:

10.1109/MSPEC.1967.5217169.

[59] A. I. Al-Shamma'a, A. Shaw, S. Saman, IEEE T. Antennas

Propag., 2004, 52, 2843-2849, doi: 10.1109/TAP.2004.834449.

[60] A. Shaw, A. Al-Shamma'a, S. Wylie, D. Toal, paper presented

at the 2006 European Microwave Conference, 2006, doi:

10.1109/EUMC.2006.281456.

[61] C. Uribe, W. Grote, paper presented at the 2009 3rd

International Conference on New Technologies, Mobility and

Security, 2009, doi: 10.1109/NTMS.2009.5384789.

[62] F. Schill, U. R. Zimmer, J. Trumpf, paper presented at the

Proceedings of ACRA, 2004, doi: 10.1.1.529.9671.

[63] J. Lloret, S. Sendra, M. Ardid, J. J. Rodrigues, Sensors, 2012,

12, 4237-4264, doi: 10.3390/s120404237

[64] Lake, Clam, Extremely Low Frequency Transmitter Site

Clam Lake, Wisconsin, 2001, Tech. Rep. [Online]. Available:

fs_clam_lake_elf_hires.PDF (fas.org).

[65] C. A. Altgelt, THE WORLD’S LARGEST “RADIO”

STATION,2005, Tech. Rep. [Online]. Available:

https://www.hep.wisc.edu/~prepost/ELF.pdf

[66] Z. Ahmad, Underwater optical wireless sensor network,

University of Warwick, 2013.

[67] S. Q. Duntley, J. Opt. Soc. Am., 1963, 53, 214-233, doi:

10.1364/JOSA.53.000214.

[68] G. Gilbert, T. Stoner, J. Jernigan, paper presented at the

Underwater Photo Optics I, 1966, doi: 10.1117/12.971001.

[69] G. Schirripa Spagnolo, L. Cozzella, F. Leccese, Sensors,

2020, 20, 2261, doi: 10.3390/s20082261

[70] A. A. Huurdeman, The worldwide history of

telecommunications, John Wiley & Sons, 2003.

[71] S. P. Thompson, Nature, 1880, 22, 481-481, doi:

10.1038/022481a0.

[72] S. A. Hamilton, B. S. Robinson, T. E. Murphy, S. J. Savage,

E. P. Ippen, J. Light. Technol., 2002, 20, 2086-2100, doi:

10.1109/jlt.2002.806781

[73] J. Söderberg, Sci. Technol. Human Values, 2011, 36, 423-450,

doi: 10.1177/0162243910368398.

[74] Y. Wang, L. Tao, X. Huang, J. Shi, N. Chi, IEEE Photonics

J, 2015,7, 1-7, doi: 10.1109/JPHOT.2015.2489927.

[75] C. Shen, C. Lee, T. K. Ng, S. Nakamura, J. S. Speck, S. P.

Denbaars, A. Y. Alyamani, M. M. El-Desouki, and B. S. Ooi, Opt.

Express, 2016, 24, 20281-20286, doi: 10.1364/OE.24.020281.

[76] S. Nakamura, S. F. Chichibu, Introduction to nitride

semiconductor blue lasers and light emitting diodes, CRC Press,

[77] K. T. Ho, R. Chen, G. Liu, C. Shen, J. H. Lerma, A. A. Al-

Saggaf, T. K. Ng, M. Alouini, J. H. He, and B. S. Ooi, Opt. express,

2018, 26, 3037-3045, doi: 10.1364/OE.26.003037.

[78] C. Shen, T. K. Ng, J. T. Leonard, A. Pourhashemi, H. M.

Oubei, M. S. Alias, S. Nakamura, S. P. DenBaars, J. S. Speck, A.

Y. Alyamani, M. M. Eldesouki, and B. S. Ooi, ACS Photonics,

2016, 3, 262-268, doi: 10.1021/acsphotonics.5b00599.

[79] C. Shen, C. Lee, E. Stegenburgs, J. H. Lerma, T. K. Ng, S.

Nakamura, S. P. DenBaars, A. Y. Alyamani, M. M. El-Desouki,

and B. S. Ooi, Appl. Phys. Express, 2017, 10, 042201, doi:

10.7567/APEX.10.042201.

[80] D. Tsonev, S. Videv, H. Haas, paper presented at the

Broadband Access Communication Technologies VIII, 2014, doi:

10.1117/12.2044649.

[81] X. Yi, Z. Li, Z. Liu, Appl. Opt., 2015, 54, 1273-1278, doi:

10.1364/AO.54.001273.

[82] B. Tu, L. Liu, Y. Liu, Y. Jin, J. Tang, Appl. Opt., 2013, 52,

3147-3155, doi: 10.1364/AO.52.003147.

[83] F. Lu, S. Lee, J. Mounzer, C. Schurgers, paper presented at

the Proceedings of the Fourth ACM International Workshop on

UnderWater Networks, 2009, doi: 10.1145/1654130.1654141.

[84] J. B. Snow, J. P. Flatley, D. E. Freeman, M. A. Landry, C. E.

Lindstrom, J. R. Longacre, and J. A. Schwartz, paper presented at

the Ocean Optics XI, 1992, doi: 10.1117/12.140670.

[85] J. W. Bales, Proc. of Unmaned Unthethered Submergible

Technology, 1995, 9, 406-415, doi: 10.1364/AO.47.000277.

[86] J. W. Giles, I. N. Bankman, paper presented at the MILCOM

2005-2005 IEEE Military Communications Conference, 2005,

doi: 10.1109/MILCOM.2005.1605919.

[87] M. A. Chancey, Short range underwater optical

communication links, (2005).

[88] J. A. Simpson, C. W. Cox, C. William, R. J. Krier, B.

Cochenour, L. B. Hughes, F. J. Muth, IEEE OCEANS 2010 -

Seattle, WA, USA (2010.09.20-2010.09.23)] 2010, doi:

10.1109/OCEANS.2010.5664429.

[89] W. C. Cox, J. A. Simpson, C. P. Domizioli, J. F. Muth, B. L.

Hughes, paper presented at the OCEANS 2008, 2008, doi:

10.1109/OCEANS.2008.5151992.

[90] M. Doniec, D. Rus, paper presented at the 2010 IEEE

International Conference on Communication Systems, 2010, doi:

10.1109/ICCS.2010.5686513.

[91] M. Tivey, P. Fucile, E. Sichel, Ridge 2000 Events, 2004, 2(1),

27-29, doi: 110802340.

[92] N. Farr, A.D. Chave, L. Freitag, J. Preisig, S.N. White, D.

Yoerger, and F. Sonnichsen, paper presented at the OCEANS

2006, 2006, doi: 10.1109/OCEANS.2006.306806.

[93] B. Cochenour, L. Mullen, A. Laux, paper presented at the

OCEANS 2007, 2007, doi: 10.1109/OCEANS.2007.4449173.

[94] F. Hanson, S. Radic, Appl. Opt., 2008, 47, 277-283, doi:

10.1364/AO.47.000277.

[95] C. Pontbriand, N. Farr, J. Ware, J. Preisig, H. Popenoe, paper

presented at the OCEANS 2008 Conference, 2008, doi:

10.1109/OCEANS.2008.5151977.

[96] W. C. Cox Jr, A 1 Mbps underwater communication system

using a 405 nm laser diode and photomultiplier tube, North

Carolina State University, 2008.

[97] B. Cochenour, L. Mullen, A. Laux, paper presented at the

MILCOM 2008-2008 IEEE Military Communications

Conference, 2008, doi: 10.1109/MILCOM.2008.4753048.

[98] S. Jaruwatanadilok, IEEE J. Sel. Area Commun., 2008, 26,

1620-1627, doi: 10.1109/JSAC.2008.081202.

[99] M. Doniec, C. Detweiler, I. Vasilescu, M. Chitre, M.

Hoffmann-Kuhnt, D. Rus, Mar. Technol. Soc. J., 2010, 44, 55-65,

doi: 10.4031/MTSJ.44.4.6.

[100] G. Baiden, Y. Bissiri, paper presented at the OCEANS'11

MTS/IEEE KONA, 2011, doi:

10.23919/OCEANS.2011.6106950.

[101] C. Gabriel, A. Khalighi, S. Bourennane, P. Léon, V. Rigaud,

EGU General Assembly., 2012, pp. 2685.

[102] B. Tian, F. Zhang, X. Tan, paper presented at the 2013

IEEE/ASME International Conference on Advanced Intelligent

Mechatronics, 2013, doi: 10.1109/AIM.2013.6584317.

[103] G. Cossu, R. Corsini, A. M. Khalid, S. Balestrino, A.

Coppelli, A. Caiti and E. Ciaramella, paper presented at the 2013

2nd International Workshop on Optical Wireless

Communications (IWOW), 2013, doi:

10.1109/IWOW.2013.6777767.

[104] M. A. Watson, P. M. Blancharda, C. Stacea, P. K. Bhogala,

H. J. Whitea, A. E. Kelly, S. Watson, M. Valyrakis, S. P. Najda, L.

Marona, and P. Perlin, paper presented at the

Unmanned/Unattended Sensors and Sensor Networks X, 2014,

doi: 10.1117/12.2073675.

[105] H. M. Oubei, C. Li, K. H. Park, T. K. Ng, M. S. Alouini,

and B. S. Ooi, Opt. Express, 2015, 23, 20743-20748, doi:

10.1364/OE.23.020743.

[106] K. Nakamura, I. Mizukoshi, M. Hanawa, Opt. Express,

2015, 23, 1558-1566, doi: 10.1364/OE.23.001558.

[107] H. M. Oubei, J. R. Duran, B. Janjua, H. Y. Wang, C. T. Tsai,

Y. C. Chi, T. K. Ng, H. C. Kuo, J. H. He, M. S. Alouini, G. R. Lin,

and B. S. Ooi, Opt. Express, 2015, 23, 23302-23309, doi:

10.1364/OE.23.023302.

[108] A. Lin, W. Lu, J. Xu, H. Song, F. Qu, J. Han, X. Gu and J.

Leng, paper presented at the OCEANS 2015-Genova, 2015, doi:

10.1109/OCEANS-Genova.2015.7271456.

[109] C. Shen, Y. Guo, H. M. Oubei, T. K. Ng, G. Liu, K. H. Park,

K.T. Ho, M. S. Alouini, and B. S. Ooi, Opt. Express, 2016, 24,

25502-25509, doi: 10.1364/OE.24.025502.

[110] H. M. Oubei, J. R. Durán, B. Janjua, H. Y. Wang, C. T. Tsai,

Y. C. Chi, T. K. Ng, H. C. Kuo, J. H. He, M. S. Alouini, G. R. Lin,

and B. S. Ooi, paper presented at the Conference on Lasers and

Electro-Optics, San Jose, California, 2016, doi:

10.1364/CLEO_SI.2016.SW1F.1.

[111] J. Baghdady, K. Miller, K. Morgan, M. Byrd, S. Osler, R.

Ragusa, W. Li, B. M. Cochenour, and E. G. Johnson, Opt. Express,

2016, 24, 9794-9805, doi: 10.1364/AO.57.008314.

[112] H. H. Lu, C. Y. Li, H. H. Lin, W. S. Tsai, C. A. Chu, B. R.

Chen, and C. J. Wu, IEEE Photonics J., 2016, 8, 1-7, doi:

10.1109/JPHOT.2016.2601778.

[113] J. Xu, Y. Song, X. Yu, A. Lin, M. Kong, J. Han, and N. Deng,

Opt. Express, 2016, 24, 8097-8109, doi: 10.1364/OE.24.008097.

[114] J. Xu, M. Kong, A. Lin, Y. Song, J. Han, Z. Xu, B. Wu, S.

Gao, and N. Deng, Opt. Lett., 2017, 42, 1664-1667, doi:

10.1364/OL.42.001664.

[115] M. Kong, W. Lv, T. Ali, R. Sarwar, C. Yu, Y. Qiu, F. Qu, Z.

Xu, J. Han, and J. Xu, Opt. Express, 2017, 25, 20829-20834, doi:

10.1364/OE.25.020829.

[116] C. Y. Li, H. H. Lu, W. S. Tsai, M. T. Cheng, C. M. Ho, Y. C.

Wang, Z. Y. Yang, and D. Y. Chen, Opt. Express, 2017, 25, 11598,

doi: 10.1364/OE.25.011598.

[117] X. Liu, S. Yi, X. Zhou, Z. Fang, Z. J. Qiu, L. Hu, C. Cong,

L. Zheng, R. Liu, and P. Tian, Opt. Express, 2017, 25, 27937-

27947, doi: 10.1364/OE.25.027937.

[118] Y. Chen, M. Kong, T. Ali, J. Wang, R. Sarwar, J. Han, C.

Guo, B. Sun, N. Deng, and J. Xu, Opt. Express, 2017, 25, 14760-

14765, doi: 10.1364/OE.25.014760.

[119] T.-C. Wu, Y.-C. Chi, H.-Y. Wang, C.-T. Tsai, G.-R. Lin, Sci

Rep, 2017, 7, 40480, doi: 10.1038/srep40480.

[120] P. Tian, X. Liu, S. Yi, Y. Huang, S. Zhang, X. Zhou, L. Hu,

L. Zheng, and R. Liu, Opt. Express, 2017, 25, 1193-1201, doi:

10.1364/OE.25.001193.

[121] B. Zhuang, C. Li, N. Wu, Z. Xu, paper presented at the

Conference on Lasers and Electro-Optics, San Jose, California,

2017, doi: 10.1364/CLEO_SI.2017.STh3O.3.

[122] T. Liu, H. Zhang, Y. Zhang, J. Song, paper presented at the

2017 4th International Conference on Information Science and

Control Engineering (ICISCE), 2017, doi:

10.1109/ICISCE.2017.313.

[123] S. Hamilton, C. DeVoe, A. Fletcher, I. Gaschits, F. Hakimi,

N. Hardy, T. Howe, N. Mittleman, H. Rao, M. Schienbart, T.

Yarnall, paper presented at Ocean Sensing and Monitoring IX ,

2017,doi: 10.1117/12.2264733

[124] T. Sawa, Study of adaptive underwater optical wireless

communication with photomultiplier tube, Japan Agency for

Marine-Earth Science and Technology, Suruga bay, Japan, KR17-

11 Leg2, Jul. 26, 2017. [Online]. Avaliable:

http://www.godac.jamstec.go.jp/catalog/data/

doc_catalog/media/KR17-11_leg2_all.pdf

[125] C. Fei, J. Zhang, G. Zhang, Y. Wu, X. Hong, and S. He, J.

Light. Technol., 2018, 36, 728-734, doi:

10.1109/JLT.2017.2780841.

[126] J. Shen, J. Wang, X. Chen, C. Zhang, M. Kong, Z. Tong,

and J. Xu, Opt. Express, 2018, 26, 23565-23571, doi:

10.1364/OE.26.023565.

[127] G. Cossu, A. Sturniolo, A. Messa, D. Scaradozzi, E.

Ciaramella, IEEE J. Sel. Area. Commun., 2018, 36, 194-202, doi:

10.1109/JSAC.2017.2774702.

[128] N. Chi, Y. Zhao, M. Shi, P. Zou, X. Lu, Opt. Express, 2018,

26, 26700-26712, doi: 10.1364/OE.26.026700.

[129] I. Lu, Y. Liu, paper presented at the 2018 OCEANS -

MTS/IEEE Kobe Techno-Oceans (OTO), 2018, doi:

10.1109/OCEANSKOBE.2018.8559430.

[130] M. Kong, Y. Chen, R. Sarwar, B. Sun, Z. Xu, J. Han, J.

Chen, H. Qin, and J. Xu., Opt. Express, 2018, 26, 3087-3097, doi:

10.1364/OE.26.003087.

[131] C. Tsai, Y. Lu, C. Yu, Y. Chen, IEEE T. Electron Devices,

2018, 65, 4346-4352, doi: 10.1109/TED.2018.2861892.

[132] S. Hu, L. Mi, T. Zhou, W. Chen, Opt. Express, 2018, 26,

21685-21699, doi: 10.1364/OE.26.021685.

[133] Y. Huang, C. Tsai, Y. Chi, D. Huang, G. Lin, J. Light.

Technol., 2018, 36, 1739-1745, doi: 10.1109/JLT.2017.2782840.

[134] C. Y. Li, H. H. Lu, W. S. Tsai, Z. H. Wang, C. W. Hung, C.

W. Su, and Y. F. Lu, IEEE Photonics J., 2018, 10, 1-9, doi:

10.1109/JPHOT.2018.2842762.

[135] X. H. Huang, C. Y. Li, H. H. Lu, C. W. Su, Y. R. Wu, Z. H.

Wang, Y. N. Chen, Optical Engr., 2018, 57, 066110, doi:

10.1117/1.OE.57.6.066110.

[136] C. Fei, X. Hong, G. Zhang, J. Du, Y. Gong, J. Evans, and S.

He, Opt. Express, 2018, 26, 34060-34069, doi:

10.1364/oe.26.034060

[137] F. Wang, Y. Liu, F. Jiang, N. Chi, Opt. Commun., 2018, 425,

106-112, doi: 10.1016/j.optcom.2018.04.073.

[138] J. Wang, X. Yang, W. Lv, C. Yu, J. Wu, M. Zhao, F. Qu, Z.

Xu, J. Han, J. Xu, Opt. Commun., 2019, 451, 181-185, doi:

10.1016/j.optcom.2019.06.053.

[139] J. Wang, C. Tian, X. Yang, W. Shi, Q. Niu, and T. A.

Gulliver, Appl. Opt., 2019, 58, 4553-4559, doi:

10.1364/AO.58.004553.

[140] C. Lu, J. Wang, S. Li, Z. Xu, paper presented at the

Conference on Lasers and Electro-Optics, San Jose, California,

2019, doi: 10.1364/CLEO_SI.2019.SM2G.6.

[141] X. Hong, C. Fei, G. Zhang, J. Du, S. He, Opt. Lett., 2019,

44, 558-561, doi: 10.1364/OL.44.000558.

[142] W.-S. Tsai, H.-H. Lu, H.-W. Wu, C.-W. Su, Y.-C. Huang,

Sci. Rep., 2019,9, 8605, doi: 10.1038/s41598-019-45125-y.

[143] B. Han, W. Zhao, Y. Zheng, J. Meng, T. Wang, Y. Han, W.

Wang, Y. Su, T. Duan, X. Xie, Sci. Rep., 2019, 434, 184-190, doi:

10.1016/j.optcom.2018.10.037.

[144] C. L. Tsai, Y.-C. Lu, S.-H. Chang, Opt. Laser Technol.,

2019, 118, 69-74, doi: 10.1016/j.optlastec.2019.05.013.

[145] Y. Zhou, X. Zhu, F. Hu, J. Shi, F. Wang, P. Zou, J. Liu, F.

Jiang, and N. Chi, Photon. Res., 2019, 7, 1019-1029, doi:

10.1364/PRJ.7.001019.

[146] F. Wang, Y. Liu, M. Shi, H. Chen, N. Chi, Opt. Eng., 2019,

58, 056117, doi: 10.1117/1.OE.58.5.056117.

[147] J. Shen, J. Wang, C. Yu, X. Chen, J. Wu, M. Zhao, F. Qu, Z.

Xu, J. Han, J. Xu, Opt. Commun., 2019, 438, 78-82, doi:

10.1016/j.optcom.2019.01.031.

[148] J. Wang, C. Lu, S. Li, Z. Xu, Opt. Express, 2019, 27, 12171-

12181, doi: 10.1364/OE.27.012171.

[149] J. Li, F. Wang, M. Zhao, F. Jiang, N. Chi, Appl. Opt., 2019,

58, 383-388, doi: 10.1364/AO.58.000383.

[150] H. Chen, X. Chen, J. Lu, X. Liu, J. Shi, L. Zheng, R. Liu,

X. Zhou, and P. Tian, IEEE Photonics J., 2020, 12, 1-10, doi:

10.1109/JPHOT.2020.2985205.

[151] F. Hu, G. Li, P. Zou, J. Hu, S. Chen, Q. Liu, J. Zhang, F.

Jiang, S. Wang, and N. Chi, paper presented at the Optical Fiber

Communication Conference (OFC) 2020, San Diego, California,

2020, doi: 10.1364/OFC.2020.M3I.4.

[152] P. N. Ramavath, S. Acharya Udupi, P. Krishnan, Opt.

Commun., 2020, 461, 125229, doi:

10.1016/j.optcom.2019.125229.

[153] R. Hema, S. Sudha, K. Aarthi, J Mar Sci Technol, 2020, 26,

97–107, doi: 10.1007/s00773-020-00724-7.

[154] G. N. Arvanitakis, R. Bian, J. J. D. McKendry, C. Cheng,

E. Xie, X. He, G. Yang, M. S. Islim, A. A. Purwita, E. Gu, H. Haas,

and M. D. Dawson, IEEE Photonics J., 2020, 12, 1-10, doi:

10.1109/JPHOT.2019.2959656.

[155] X. Chen, W. Lyu, Z. Zhang, J. Zhao, J. Xu, Opt. Express,

2020, 28, 23784-23795, doi: 10.1364/OE.399794.

[156] J. Du, Y. Wang, C. Fei, R. Chen, G. Zhang, X. Hong, and S.

He, Opt. Express, 2021, 29, 783-796, doi: 10.1364/OE.416117.

[157] L. J. Johnson, R. J. Green, M. S. Leeson, Appl. Opt., 2013,

52, 7867-7873, doi: 10.1364/AO.52.007867.

[158] S. Arnon, Opt. Eng., 2010, 49, 015001, doi:

10.1117/1.3280288.

[159] Y. Dong, S. Tang, X. Zhang, IEEE Commun. Lett., 2013, 17,

2164-2167, doi: 10.1109/LCOMM.2013.091113.131363.

[160] N. Farr, A. Bowen, J. Ware, C. Pontbriand, M. Tivey, paper

presented at the OCEANS'10 IEEE SYDNEY, 2010, doi:

10.1109/OCEANSSYD.2010.5603510.

[161] D. McKee, A. Cunningham, Estuar. Coast. Shelf. Sci., 2006,

68, 305-316, doi: 10.1016/j.ecss.2006.02.010.

[162] M. Z. Chowdhury, M. K. Hasan, M. Shahjalal, M. T.

Hossan, Y. M. Jang, IEEE Commun. Surv. Tutor., 2020, 22, 930-

966, doi: 10.1109/COMST.2020.2966855.

[163] I. Vasilescu, K. Kotay, D. Rus, M. Dunbabin, P. Corke,

paper presented at the Proceedings of the 3rd international

conference on Embedded networked sensor systems, 2005, doi:

10.1145/1098918.1098936

[164] M. Dunbabin, P. Corke, I. Vasilescu, D. Rus, paper

presented at the Proceedings 2006 IEEE International Conference

on Robotics and Automation, 2006. ICRA 2006., 2006, doi:

10.1109/ROBOT.2006.1642013.

[165] K. Y. Islam, I. Ahmad, D. Habibi, M. I. A. Zahed, J.

Kamruzzaman, IEEE Access, 2021, doi:

10.1109/ACCESS.2021.3088467.

[166] M. Mostafa, H. Esmaiel, E. M. Mohamed, paper presented

at the 2018 IEEE Wireless Communications and Networking

Conference (WCNC), 2018, doi: 10.1109/WCNC.2018.8377209.

[167] V. Haltrin. (Praxis Publ. Ltd., Chichester, UK, 2006).

[168] C. Mobley, Light and Water: Radiative Transfer in Natural

Waters' Academic Press. New York, 1994, vol. 565.

[169] E. Leymarie, D. Doxaran, M. Babin, Appl. Opt., 2010, 49,

5415-5436, doi: 10.1364/AO.49.005415.

[170] H. Buiteveld, J. H. M. Hakvoort, M. Donze, Ocean Opt. XII,

1994, 2258, doi: 10.1117/12.190060.

[171] H. R. Gordon, Limnol. Oceanogr., 1989, 34, 1389-1409, doi:

10.4319/lo.1989.34.8.1389.

[171] R. W. Spinrad, K. L. Carder, M. J. Perry, Ocean Opt.,

Oxford University Press, 1994.

[172] H. R. Gordon, O. B. Brown, M. M. Jacobs, Appl. Opt., 1975,

14, 417-427, doi: 10.1364/AO.14.000417.

[173] A. Morel, H. Loisel, Appl. Opt., 1998, 37, 4765-4776, doi:

10.1364/AO.37.004765.

[174] L. J. Johnson, F. Jasman, R. J. Green, M. S. Leeson, Underw.

Technol. 2014, 32, 167-175, doi: 10.3723/ut.32.167.

[175] G. Giuliano, Underwater optical communication systems,

University of Glasgow, (2019).

[175] B. M. Cochenour, L. J. Mullen, A. E. Laux, IEEE J. Ocean.

Eng., 2008, 33, 513-521, doi: 10.1109/JOE.2008.2005341.

[178] L. Håkanson, Ecol. Res., 2006, 21, 75-90, doi:

10.1007/s11284-005-0098-x.

[179] S. A. H. M. M. Mehedi, A. M. Hasan, M. A. Sadiq, H.

Akhtar, L. S. R. Islam. (IJACSA, 2020).

[180] Z. Zeng, S. Fu, H. Zhang, Y. Dong, J. Cheng, IEEE

Commun. Surv. Tutor., 2016, 19, 204-238, doi:

10.1109/COMST.2016.2618841.

[181] C. Mobley, E. Boss, C. Roesler, Ocean optics web book,

URL http://www.oceanopticsbook. info, 2010.

[182] N. G. Jerlov, Marine optics, Elsevier, 1976.

[183] R. C. Smith, K. S. Baker, Appl. Opt., 1981, 20, 177-184,

doi: 10.1364/AO.20.000177.

[184] A. Bricaud, A. Morel, L. Prieur, Limnol. Oceanogr., 1981,

26, 43-53, doi: 10.4319/lo.1981.26.1.0043.

[185] T. Garrison, Wadsworth Publishing, Belmont, CA, 1996.

[186] H. M. Sosik, B. G. Mitchell, Deep Sea Res. Part I Oceanogr.

Res. Pap., 1995, 42, 1717-1748, doi: 10.1016/0967-

0637(95)00081-G.

[187] A. Bricaud, A. Morel, M. Babin, K. Allali, H. Claustre,

Geophys. Res. Oceans, 1998, 103, 31033-31044, doi:

10.1029/98JC02712.

[188] J. R. Morrison, N. B. Nelson, Limnol. Oceanogr., 2004, 49,

215-224, doi: 10.4319/lo.2004.49.1.0215.

[189] https://www.oceanopticsbook.info/view/optical-

constituents-of-the-ocean/level-2/new-iop-model-case-1-water.

[190] A. P. Vasilkov, J. R. Herman, Z. Ahmad, M. Kahru, B. G.

Mitchell, Appl. Opt., 2005, 44, 2863-2869, doi:

10.1364/AO.44.002863.

[191] J. Wei, Z. Lee, Methods Oceanogr.,, 2013, 8, 56-74, doi:

10.1016/j.mio.2013.12.001.

[192] D. A. Hansell, C. A. Carlson, Biogeochemistry of marine

dissolved organic matter, Academic Press, 2014.

[193] R. Liu, Q. Ling, Q. Zhang, Y. Zhou, C. Le, Y. Chen, Q. Liu,

W. Chen, J. Tang and D. Liu, Remote Sens., 2020, 12, 3021, doi:

10.3390/rs12183021.

[194] W. Breves, R. Reuter, Earth Syst. Sci. Data, 2000, 109, 415-

425, doi: 10.1007/bf02708329.

[195] L. Sun, J. Wang, K. Yang, M. Xia, J. Han, Sens.

Transducers, 2014, 163, 107.

[196] D. Chadha, Terrestrial wireless optical communication.

McGraw Hill Professional, 2013.

[197] R. Austin, G. Halikas, 1976, Tech. Rep. [online]. Available:

https://escholarship.org/content/qt8px2019m/qt8px2019m.pdf.

[198] V. Nikishov, V. Nikishov, Int. J. Fluid Mech. Res., 2000, 27,

doi: 10.1615/InterJFluidMechRes.v27.i1.70.

[199] Y. Ata, Y. Baykal, Wave. Random Complex Media, 2014, 24,

164-173, doi: 10.1080/17455030.2014.884735.

[200] S. Tang, X. Zhang, Y. Dong, paper presented at the 2013

MTS/IEEE OCEANS-Bergen, 2013, doi: 10.1109/OCEANS-

Bergen.2013.6607967.

[201] N. Farwell, Optical beam propagation in oceanic turbulence,

[202] R. E. Green, H. M. Sosik, J. Geophys. Res. Oceans, 2004,

109, doi: 10.1029/2003JC001977.

[203] G. C. Mooradian, M. Geller, Appl. Opt., 1982, 21, 1572-

1577, doi: 10.1364/AO.21.001572.

[204] H. Zhang, L. Hui, Y. Dong, IEEE Commun. Lett., 2015, 19,

2162-2165, doi: 10.1109/LCOMM.2015.2484351.

[205] R. A. Leathers, T. V. Downes, C. O. Davis, C. D. Mobley,

"Monte Carlo radiative transfer simulations for ocean optics: a

practical guide," Naval Research Lab Washington Dc Appl. Opt.

Branch, 2004

[206] T. J. Petzold, "Volume scattering functions for selected

ocean waters," (Scripps Institution of Oceanography La Jolla Ca

Visibility Lab, 1972), doi: 10.21236/ad0753474.

[207]https://www.oceanopticsbook.info/view/scattering/petzolds

-measurements.

[208] L. G. Henyey, J. L. Greenstein, ApJ, 1941, 93, 70-83, doi:

10.1086/144246

[209] C. Gabriel, M.-A. Khalighi, S. Bourennane, P. Léon, V.

Rigaud, J. Opt. Commun. Netw., 2013, 5, 1-12, doi:

10.1364/JOCN.5.000001.

[210] T. Binzoni, T. S. Leung, A. H. Gandjbakhche, D.

Ruefenacht, D. Delpy, Phys. Med. Biol, 2006, 51, doi:

10.1088/0031-9155/51/17/n04

[211] S. A. Prahl, Light transport in tissue, University of Texas at

Austin,1989.

[212] L. Wang, S. L. Jacques, Monte Carlo Modeling of Light

Transport in Multi-layered Tissues in Standard C, University of

Texas, MD Anderson Cancer Center, Houston, 1992.

[213] https://www.oceanopticsbook.info/view/scattering/level-

2/the-henyey-greenstein-phase-function.

[214] V. I. Haltrin, Appl. Opt., 2002, 41, 1022-1028, doi:

10.1364/AO.41.001022.

[215] C. Gabriel, M.-A. Khalighi, S. Bourennane, P. Leon, V.

Rigaud, paper presented at the 2011 IEEE GLOBECOM

Workshops (GC Wkshps), 2011, doi:

10.1109/GLOCOMW.2011.6162571.

[216] L. K. Gkoura, G. Roumelas, H. Nistazakis, H. Sandalidis,

A. Vavoulas, A. Tsigoulos, G. Tombras, Turbulence Modelling

Approaches–Current State, Development Prospects,

Applications., 2017.

[217] A. L. Alldredge, M. W. Silver, Prog. Oceanogr, 1988, 20,

41-82, doi: 10.1016/0079-6611(88)90053-5.

[218] L. J. Johnson, R. J. Green, M. S. Leeson, Appl. Opt., 2014,

53, 7273-7277, doi: 10.1364/AO.53.007273.

[219] W. Cox, J. Muth, , J. Op.t Soc. Am. A,, 2014, 31, 920-934,

doi: 10.1364/JOSAA.31.000920.

[220] H. Manor, S. Arnon, Appl. Opt., 2003, 42, 4285-4294, doi:

10.1364/AO.42.004285.

[221] X. Wang, M. Zhang, H. Zhou, X. Ren, Electronics, 2021,

10(5), 632, doi: 10.3390/electronics10050632

[222] G. Keiser, Wiley Encyclopedia of Telecommunications,

2003, doi: 10.1002/0471219282.eot158.

[223] M. V. Jamali, J. A. Salehi, F. Akhoundi, IEEE Trans.

Commun., 2016, 65, 1176-1192, doi:

10.1109/TCOMM.2016.2642943.

[224] X. Sun, M. Kong, O. Alkhazragi, C. Shen, E. N. Ooi, X.

Zhang, U. Buttner, T. K. Ng, B. S. Ooi, Opt. Commun., 2020, 461,

125264, doi: 10.1016/j.optcom.2020.125264.

[225] H. M. Oubei, R. T. ElAfandy, K. H. Park, T. K. Ng, M. S.

Alouini, and B. S. Ooi, IEEE Photonics J., 2017, 9, 1-9, doi:

10.1109/JPHOT.2017.2682198.

[226] H. M. Oubei, E. Zedini, R. T. Elafandy, A. Kammoun, M.

Abdallah, T. K. Ng, M. Hamdi, M. S. Alouini, and B. S. Ooi, Opt.

Lett., 2017, 42, 2455-2458, doi: 10.1364/OL.42.002455.

[227] M. A. Khalighi, M. Uysal, IEEE Commun. Surv. Tutor.,

2014, 16, 2231-2258, doi: 10.1109/COMST.2014.2329501.

[228] H. M. Oubei, C. Shen, A. Kammoun, E. Zedini, K. H. Park,

X. Sun, G. Liu, C. H. Kang, T. K. Ng, M. S. Alouini, and B. S.

Ooi, Jpn. J. Appl. Phys., 2018, 57, 08PA06, doi:

10.7567/jjap.57.08pa06.

[229] A. Kakati, D. Sharma, N. N. Aggarwal, Int. J. Res.

Granthaalayah, 2018, 6, 238-245, doi:

10.29121/granthaalayah.v6.i6.2018.1370.

[230] W. C. Cox, K. F. Gray, J. A. Simpson, B. Cochenour, B. L.

Hughes and J. F. Muth, paper presented at OCEANS 2010

MTS/IEEE SEATTLE, 20210, doi:

10.1109/OCEANS.2010.5664432.

[231] L. Mullen, B. Cochenour, W. Rabinovich, R. Mahon, J.

Muth, Appl. Opt., 2009, 48, 328-337, doi:

10.1364/AO.48.000328.

[232] B. Cochenour, L. Mullen, W. Rabinovich, R. Mahon, Proc.

SPIE, 2009, 7317, 73170G, doi: 10.1117/12.818639.

[233] W. Liu, D. Zou, Z. Xu, J. Yu, paper presented at the 2015

IEEE International Conference on Cyber Technology in

Automation, Control, and Intelligent Systems (CYBER), 2015,

doi: 10.1109/CYBER.2015.7288125.

[234] S. Tang, Y. Dong, X. Zhang, paper presented at the 2013

MTS/IEEE OCEANS-Bergen, 2013, doi: 10.1109/OCEANS-

Bergen.2013.6608002.

[235] S. Arnon, D. Kedar, J. Opt. Soc. Am. A, 2009, 26, 530-539,

doi: 10.1364/josaa.26.000530.

[236] D. Alley, L. Mullen, A. Laux, paper presented at the

OCEANS'11 MTS/IEEE KONA, 2011, doi:

10.23919/OCEANS.2011.6107273.

[237] B. Cochenour, L. Mullen, J. Muth, paper presented at the

Ocean Sensing and Monitoring IV, 2012, doi: 10.1117/12.918711.

[238] D. K. Sharma, A. Mishra, R. Saxena, Int. J. Comput. Sci.

Commun. Technol., 2010, 3, 2007.

[239] S. B. Alexander, Optical communication receiver design.

IET, 1997.

[240] T. Okoshi, K. Kikuchi, Coherent optical fiber

communications, Springer Science & Business Media, 1988, vol.

[241] R. M. Hagem, D. V. Thiel, S. G. O'Keefe, T. Fickenscher,

doi: 10.1109/ISCIT.2012.6380853.

[242] Z. Ghassemlooy, W. Popoola, S. Rajbhandari, Optical

wireless communications: system and channel modelling with

Matlab®. CRC press, 2019.

[243] Y. Fan, R. J. Green, Opt. Eng., 2007, 46, 065001, doi:

10.1117/1.2746010.

[244] C. Gabriel, M.-A. Khalighi, S. Bourennane, P. Léon, V.

Rigaud, paper presented at the 2012 International Workshop on

Optical Wireless Communications (IWOW), 2012, doi:

10.1109/IWOW.2012.6349691.

[245] J. M. Senior, M. Y. Jamro, Optical fiber communications:

principles and practice, Pearson Education, 2009.

[246] D.-s. Shiu, J. M. Kahn, IEEE Trans. Commun., 1999, 47,

1201-1210, doi: 10.1109/26.780456.

[247] Z. Ghassemlooy, A. Hayes, N. Seed, E. Kaluarachchi, IEEE

Commun. Mag., 1998, 36, 95-99, doi: 10.1109/35.735885.

[248] Z. Ghassemlooy, N. Aldibbiat, paper presented at the 2006

International Conference on Transparent Optical Networks, 2006,

doi: 10.1109/ICTON.2006.248423.

[249] S. Meihong, Y. Xinsheng, Z. Zhangguo, paper presented at

the 2009 international conference on communication software

and networks, 2009, doi: 10.1109/ICCSN.2009.95.

[250] M. Chen, S. Zhou, T. Li, paper presented at the 2006

International Conference on Communications, Circuits and

Systems, 2006, doi: 10.1109/ICCCAS.2006.285044.

[251] H. Sari, B. Woodward, paper presented at the IEEE Oceanic

Engineering Society. OCEANS'98. Conference Proceedings (Cat.

No. 98CH36259), 1998, doi: 10.1109/OCEANS.1998.724422.

[252] K.-P. Ho, Phase-modulated optical communication systems.

Springer Science & Business Media, 2005.

[253] S. Meihong, Y. Xinsheng, Z. Fengli, paper presented at the

2009 International Conference on Communication Software and

Networks, 2009, doi: 10.1109/ICCSN.2009.97.

[254] D. K. Kim, H. S. Lee, IEICE Trans. Commun., 2009, 92,

2324-2326, doi: 10.1587/transcom.E92.B.2324.

[255] T. J. Lee, M. S. Han, J. W. Han, K. M. Kim, S. Y. Chun, K.

Son, paper presented at the OCEANS'11 MTS/IEEE KONA,

2011, doi: 10.23919/OCEANS.2011.6107186.

[256] M. Z. Hassan, M. J. Hossain, J. Cheng, V. C. M. Leung,

ZTE Commun., 2019, 14, 2-12, doi: 10.3969/j. issn. 1673-5188.

2016. 02. 001.

[257] P. Corvini, T. Koch, J. Light. Technol., 1987, 5, 1591-1595,

doi: 10.1109/JLT.1987.1075448.

[258] J. S. Everett, Forward-error correction coding for

underwater free-space optical communication, 2009.

[259] B. Cochenour, L. Mullen, J. Muth, IEEE J. Ocean. Eng.,

2013, 38, 730-742, doi: 10.1109/JOE.2013.2255811.

[260] M. Sun, B. Zheng, L. Zhao, X. Zhao, F. Kong, paper

presented at the 2014 Oceans-St. John's, 2014, doi:

10.1109/OCEANS.2014.7003241.

[261] D. Anguita, D. Brizzolara, G. Parodi, Q. Hu, paper

presented at OCEANS 2011 IEEE – Spain, 2011, doi:

10.1109/Oceans-Spain.2011.6003598.

[261] S. U. Rehman, S. Ullah, P. H. J. Chong, S. Yongchareon, D.

Komosny, Sensors, 2019, 19, 1153, doi: 10.3390/s19051153

[263] Z. Tong, X. Yang, X. Chen, H. Zhang, Y. Zhang, H. Zou, L.

Zhao, and J. Xu, Opt. Express, 2021, 29, 20262-20274, doi:

10.1364/OE.429974.

[264] T. Wiener, S. Karp, IEEE Trans. Commun., 1980, 28, 1602-

1607, doi: 10.1109/TCOM.1980.1094858.

[265] J. Loo, J. L. Mauri, J. H. Ortiz, Mobile ad hoc networks:

current status and future trends. CRC Press, 2016.

[266] B. E. A. Saleh, M. C. Teich, Fundamentals of photonics,

[267] J. A. Simpson, B. L. Hughes, J. F. Muth, paper presented at

the OCEANS 2009, 2009, doi:

10.23919/OCEANS.2009.5422262.

[268] B.Cochenour, L. Mullen, and J. Muth , SPIE , 2012, 8372,

83720S, doi: 10.1117/12.918711.

[269] B. Cochenour, L. Mullen, paper presented at the

OCEANS'11 MTS/IEEE KONA, 2011, doi:

10.23919/OCEANS.2011.6107264.

[270] S. Bloom, E. Korevaar, J. Schuster, H. Willebrand, J. Opt.

Commun. Netw., 2003, 2, 178-200, doi: 10.1364/jon.2.000178

[271] S. Hranilovic, Wireless optical communication systems.

Springer Science & Business Media, 2006.

[272] F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, W. B.

Britton and B. Ramos, paper presented at the Ocean Sensing and

Monitoring II, 2010, doi: 10.1117/12.854775.

[273] L. Mullen, A. Laux, B. Cochenour, Appl. Opt., 2009, 48,

2607-2612, doi: 10.1364/AO.48.002607.

[274] L. Mullen, A. Laux, B. Cochenour, paper presented at the

Ocean Sensing and Monitoring, 2009, doi: 10.1117/12.818588.

[275] D. Anguita, D. Brizzolara, G. Parodi, paper presented at the

OCEANS 2010 MTS/IEEE SEATTLE, 2010, doi:

10.1109/OCEANS.2010.5664321.

[276] D. Anguita, D. Brizzolara, G. Parodi, ECCSC'10,(IEEE,

2010), pp. 185-188.

[277] J. A. Simpson, B. L. Hughes, J. F. Muth, J-SAC, 2012, 30,

964-974, doi: 10.1109/JSAC.2012.120611.

[278] H. Hemmati, A. Biswas, Proc. SPIE, 2014, 8971, doi:

10.1117/12.2042254.

[279] N. E. Farr, N. E., L.Freitag, J. Preisig., D. R Yoerger, S.

N. White, & A. D. Chave, (2011). U.S. Patent No. 7,953,326.

Washington, DC: U.S. Patent and Trademark Office.

[280] M. Lanzagorta, San Rafael, CA, USA Morgan & Claypool,

2013, doi: 10.2200/S00409ED1V01Y201203COM006.

[281] M. Sarkar, A. Theuwissen, Design of a CMOS Image

Sensor in A Biologically Inspired CMOS Image Sensor. Springer,

2013, pp. 49-104.

[282] C. Creatore, M. A. Parker, S. Emmott, A. W. Chin, Phys.

Rev. Lett., 2013, 111, 253601, 10.1103/PhysRevLett.111.253601.

[283] S. Viollet, N. Franceschini, paper presented at the

Proceedings 1999 IEEE/RSJ International Conference on

Intelligent Robots and Systems. Human and Environment

Friendly Robots with High Intelligence and Emotional Quotients

(Cat. No. 99CH36289), 1999, doi: 10.1109/IROS.1999.813005.

[284] Q.-R. Yan, M. Wang, W.-H. Dai, Y.-H. Wang, Opt.

Commun.,2021, 495, 127024, doi:

10.1016/j.optcom.2021.127024.

[285] IEEE Std 802.15.7-2011, 2011, 1-309, doi:

10.1109/IEEESTD.2011.6016195.

[286] L. Johnson, R. Green, M. Leeson, paper presented at the

2013 2nd International Workshop on Optical Wireless

Communications (IWOW), 2013, doi:

10.1109/IWOW.2013.6777765.

[287] A. Al-Kinani, C.-X. Wang, L. Zhou, W. Zhang, IEEE

Commun. Surv. Tutor., 2018, 20, 1939-1962, doi:

10.1109/COMST.2018.2838096.

[288] C. T. Geldard, J. Thompson, W. O. Popoola, paper

presented at the 2019 International Symposium on Electronics

and Smart Devices (ISESD), 2019, doi:

10.1109/ISESD.2019.8909494.

[289] G. C. Clark Jr, J. B. Cain, Error-correction coding for digital

communications. Springer Science & Business Media, 2013.

[290] Z. Yuan, X. Zhao, paper presented at 2012 2nd International

Conference on Consumer Electronics, Communications and

Networks (CECNet), 2012, doi: 10.1109/CECNet.2012.6201904

[291] S. Faruque, Radio frequency channel coding made easy.

Springer, 2016.

[292] K. D. Rao, Channel coding techniques for wireless

communications. Springer, 2015.

[293] K. Elaiyarani, K. Kannadasan, R. Sivarajan, doi:

10.1109/ICCSP.2016.7754111.

[294] A. V. Oppenheim, A. S. Willsky, S. H. Nawab, Señales y

sistemas, Pearson Educación, 1998.

[295] A. Nafaa, T. Taleb, L. Murphy, IEEE Commun. Mag., 2008,

46, 72-79, doi: 10.1109/MCOM.2008.4427233.

[296] C. E. Shannon, Bell Syst. Tech. J., 1948, 27, 379-423, doi:

10.1002/j.1538-7305.1948.tb01338.x.

[297] P. Elias, IRE Conv. Rec. 1955, 3, 37-46.

[298] W.-P. Wang, B. Zheng, paper presented at the 2013 10th

International Computer Conference on Wavelet Active Media

Technology and Information Processing (ICCWAMTIP), 2013,

doi: 10.1109/ICCWAMTIP.2013.6716649.

[299] M. Doniec, M. Angermann, D. Rus, IEEE J. Ocean. Eng.,

2013, 38, 743-757, doi: 10.1109/JOE.2013.2278932.

[300] M. Doniec, A. Xu, D. Rus, paper presented at the 2013

IEEE International Conference on Robotics and Automation,

2013, doi: 10.1109/ICRA.2013.6631308.

[301] G. K. Reddy, A. Tapaswi, G. M. Sheeba, Mater. Today:

Proc., 2021, doi: 10.1016/j.matpr.2020.11.499.

[302] A. A. Sahrab, I. Marghescu, paper presented at 2014 10th

International Conference on Communications (COMM), 2014,

doi: 10.1109/ICComm.2014.6866759.

[303] D. C. Li, C. C. Chen, S. K. Liaw, S. Afifah, J. Y. Sung, and

C. H. Yeh, paper presented at the Photonics (MDPI), 2021, 8, 74

doi: 10.3390/photonics8030074.

[304] D. Large, J. Farmer, Modern cable television technology.

Elsevier, 2004.

[305] https://www.malvernpanalytical.com/en.

Author information

Saleha Al-Zhrani received her B.Sc. degree in physics (first

class with honors) from Umm Al-Qura University(UQU)-

Makkah, KSA, in 2014. In 2017, she was accepted as a

teaching assistant in the Physics Department at Al-Qunfudhah

University College - Umm Al-Qura University(UQU), KSA. In

2019, she was granted a scholarship to study for a master's

degree at King Abdulaziz University (KAU), KSA, specializing

in lasers. She is interested in computer skills and the Python

programming language, and she has many courses in the field

of scientific research and its tools. Since 2019, Saleha involved

in conducting research on underwater optical

communications working on experimental work, design and

construction of a turbidity sensors studying the relationship of

turbidity with voltage and intensity of the absorbed beam,

respectively. Theoretical work was also done in the field

performance estimation of underwater optical wireless

communication channel models.

Nada M. Bedaiwi is currently a PhD student working on a

novel approach to solve optical channel nonlinearities and

Optical Signal Evaluation Inside the Optical Receiver. The

approach is a combination of Clustering K-Means (CKM) and

Support Vector Machine (SVM) with data support provided by

continually expanding the Blockchain Data Pool (BDP). Nada

(in collaboration with Prof. I F Al-Ramli and Prof Y Al-

Hadeethi) is determined to combine Blockchain and machine

language/artificial intelligence (ML/AI). Furthermore, she is

aiming to introduce how to use such technologies together to

enhance the performance of optical receivers for UWOC and

FSO systems. Nada is experienced with COMSOL

Multiphysics software, Python programming language,

MATLAB for deep learning and machine learning, signal

processing and communications. Nada holds a master's

degree in laser and spectra physics - from King Abdulaziz

University - with an overall grade (excellent). She obtained

her Bachelor’s degree in Science and Education - major in

Physics from Tabuk University - with a general grade

(excellent with honors). Nada awarded many certificates of

excellence and good conduct from KAU. She also obtained the

Tabuk Award for Academic Excellence from His Royal

Highness, the Prince of Tabuk Province. She holds certificates

of excellence and awards from the General Presidency for

Girls' Education in all years of study (primary / intermediate

/ secondary) and a certificate of thanks and appreciation from

the School of Memorizing the Holy Qur’an in Duba. Nada

completed many training courses, the most important of which

is (CYBERSECURITY using AI with python, and Machine

Learning using Python Workshop).

Intesar F El-Ramley was born in Al Adamia, Baghdad, Iraq,

on December 13, 1956. He received the B.Sc. Physics (Honors

– Ranked First) degree from the University of Baghdad, Iraq,

in 1976, and the M.Sc. in Laser Applications and Ph.D. in

Electronic Systems Engineering from the University of Essex,

Colchester, Essex, UK, in 1981 and 1985, respectively.

Between 1985 and 1988, Intesar worked as research professor

in University of Al Mustansiriya and University of Technology

in Baghdad – Iraq. Between 1988 and 1992, he published

several papers in the field of Optical Communication

Modelling and Simulation. Between 1993 and 2019 Intesar

worked in the software industry. During this period, he

founded Meridex Software Corporation in 1999. In 2000,

Intesar filed a full USA patent in 2000 for remote data storage

management, which was later sold. Since then this patent has

been cited by more than ten technology companies like Nokia

Corporation, Research In Motion, and Dropbox. Currently, he

is pursuing his academic interest in Optical Communication

(Optical Fiber, FSO, UWOC) in collaboration with several

research groups in the UK and Middle East.

Abeer Z. Barasheed is a self-motivated, hardworking and

collaborative person with an extreme passion and

determination to solve problems and conduct scientific

research. The approach I strongly believe in, is projecting a

theory on an experiment and interfacing both. On one hand,

working on mathematical modeling has allowed me to build

very good analytical and numerical skills, where I have

intensively worked with COMSOL, Python, MATLAB and

object-oriented programming (OOP). On the other hand, I

have developed great troubleshooting abilities and hands-on

experience through working in experimental laboratories

since 2010, in general, and in microfabrication of membranes

and thin films in specific. The nature of the education I

received and the research I have done since I started this

career is highly multidisciplinary, computational physics, thin

film deposition, material characterization, microfabrication

and big data driven modeling (Machine learning and Artificial

intelligence). In addition, working locally and abroad has

greatly expanded my networking and communication skills

and offered me the pleasure to appreciate diversity and work

in multicultural environments. My current position in KAU as

an assistant professor in the physics department and the

intensive engagement in teaching graduate and

undergraduate courses have further strengthened my skills

scientifically, verbally, and publicly. Dr. Abeer completed his

BSc in Physics in 2006 from King Abdulaziz University, Saudi

Arabia, MS in Materials Science and Engineering in 2010

from King Abdullah University for Science and Technology,

Saudi Arabia and PHD in Physics in 2018 from McGill

University, Canada. Dr. Abeer has published several research

papers in high rank ISI Journals on photonic crystal

membranes (Fabrication and Characterization), Optically

defined mechanical geometry, High-Temperature

Thermoelectric Properties of Strontium Titanate Thin Films

with Oxygen Vacancy and Niobium Doping, Temperature-

dependent thermoelectric properties of chemically derived

gallium zinc oxide thin films, and so on.

Ali Abduldaiem received his Bachelor of Physics from

Zagazig University in 1981 with a grade of excellent with

honors, then he obtained a master’s degree in studying the

electrical properties of some semiconductors in 1987 from

Zagazig University, then he obtained a Doctor of Philosophy

of Science degree in studying the mechanical and electrical

properties and the exact composition of tin-zinc alloys

Bilateral from Zagazig University 1991. Ali worked as a

lecturer at Zagazig University in the Arab Republic of Egypt,

Sana’a University in the Yemen from 1987-1988, at Qar

Younis University in Benghazi from 1994 to 1996, at Al-

Marqab University in Tarhuna in the Libyan Arab Jamahiriya

from 2005-2008 and at King Abdulaziz University in Saudi

Arabia from 2009-2021 as an Associate Professor. Ali Worked

as a visiting researcher in the Department of Material Design,

Faculty of Engineering, Nagoya University, Japan 2004-2005.

He has supervised more than forty graduation projects for

undergraduate students. Ali supervised and co-supervised

three doctoral theses and seven master’s theses at Zagazig

University and King Abdulaziz University in Saudi Arabia.

Also, participated in publishing about thirty papers in

international journals with impact factor. Ali has interests in

designing and manufacturing some practical experiments for

undergraduate, master's and doctoral students.

Yas Al-Hadeethi received his B.Sc. degree in physics (first

class with honors) from Al-Mustansiriya University-Baghdad,

Iraq, in 1982, the Postgraduate diploma; M.Sc. and Ph.D. in

Laser-Physics from Essex University, UK, in 1985,1986 and

1995, respectively. In 1995, Yas joined the Max-Born Institute

for nonlinear-optics and short-pulse spectroscopy, Berlin, as

postdoc fellow. He joined many Arab and European

Universities as professor of physics, chief of researchers and

director of National research programs. Yas received seven

European research awards and 59 funded research projects,

regional and National shields, medals, scientific awards and

decorations. He also acted as principal investigator in more

than 46 projects. He worked for HiPER, the European High-

Power Laser Energy Research facility for Laser‐induced

thermonuclear fusion supervising the High Power Laser

Research Lab at Milano Bicocca University-Italy. Yas

supervised the construction and running of class 100 and class

1000 clean rooms equipped with the most sophisticated nano-

fabrication and characterizations facilities at KAU. He is a

Professor of Laser Physics at the Physics Dept., King

Abdulaziz University (KAU) and the head of the lithography

research group at KAU, Deanship of Scientific research. Yas

was a supervisor and examiner for more than 120 PhD and

Msc Theses in Europe, Arab countries, Malaysia etc. He is

also heading many academic and scientific committees and a

frequent expert to the International conferences of the Arab

Industrial Development and Mining Organization, Associate

of the INFN-Italian National Institute of Nuclear Physics

(INFN) in 2009, and member of the SPIE- The International

Society for Photo-Optical Instrumentation Engineers-

Washington DC since 1987. His h-index=21, Highly Cited in

Field (8), Hot Papers in Field (5). Yas published more than

160 papers, a significantly high number of them at top 5% to

10% Q1 ranking ISI Journals.

Ahmad Umar received his Ph.D. in semiconductor and

chemical engineering from Chonbuk National University,

South Korea. He worked as a research scientist in Brain Korea

21, Centre for Future Energy Materials and Devices, Chonbuk

National University, South Korea, in 2007–2008. Afterwards,

he joined the Department of Chemistry in Najran University,

Najran, Saudi Arabia. He is a distinguished professor of

chemistry and served as deputy director of the Promising

Centre for Sensors and Electronic Devices (PCSED), Najran

University, Najran, Saudi Arabia. Professor Ahmad Umar is

specialized in ‘semiconductor nanotechnology’, which

includes growth, properties and their various high

technological applications, for instance, gas, chemicals and

biosensors, optoelectronic and electronic devices, field effect

transistors (FETs), nanostructure-based energy-harvesting

devices, such as solar cells, Li-ion batteries, super-capacitors,

semiconductor nanomaterial- based environmental

remediation, and so on. He is also specialized in the modern

analytical and spectroscopic techniques used for the

characterizations and applications of semiconductor

nanomaterials. He contributed to the world of science by

editing world’s first handbook series on Metal Oxide

Nanostructures and Their Applications (5-volume set, 3500

printed pages, www.aspbs.com/mona) and handbook series on

Encyclopedia of Semiconductor Nanotechnology (7-volume

set; www.aspbs.com/esn), both published by American

Scientific Publishers (www.aspbs.com). He has published

more than 600 research papers in reputed journals with h-

index of 75 and i10-index of 377 with total citations over

21000 (According to Google scholar).

Publisher’s Note: Engineered Science Publisher remains

neutral with regard to jurisdictional claims in published maps

and institutional affiliations.

Underwater Optical Communications: A Brief Overview and ...

Documents

Transcript of Underwater Optical Communications: A Brief Overview and ...

Turismo archeologico subacqueo (Underwater archaeological tourism)

Experimental assessment of time-reversed OFDM underwater communications

Characterization of Underwater Acoustic Communication ...

Legislative Council Brief

The Application of Recent Advances in Underwater Detection and Survey Techniques to Underwater Archaeology / Underwater Archaelogical Survey on Cilician Coasts: Discovering an Anchorage

Communications - Unilog

Underwater Explorers: Becoming an Ambassador for Underwater Archaeology

CoCoRo -- The Self-Aware Underwater Swarm

Biology of Underwater Caves

WIRELESS COMMUNICATIONS

Brief history

Control of High-Speed Underwater Vehicles

COMMUNICATIONS - NCBI

UNDERWATER WORK MEASUREMENT TECHNIQUES - DTIC

Underwater filters

Underwater acoustic communication report

Correspondence and Brief Communications

Antifouling Mortars for Underwater Restoration - MDPI

UNDERWATER WELDING

MIMO-OFDM for High-Rate Underwater Acoustic Communications