A Top-Down Survey on Optical Wireless Communications for the Internet of Things

Abstract

p>The Internet of Things (IoT) is a transformative technology marking the beginning of a new era where physical and digital worlds are integrated by connecting a plethora of uniquely identifiable smart objects. Although the Internet of terrestrial things (IoTT) has been at the center of our IoT perception, it has been recently extended to different environments, such as the Internet of underWater things (IoWT), the Internet of Biomedical things (IoBT), and Internet of underGround things (IoGT). Even though radio frequency (RF) based wireless networks are regarded as the default means of connectivity, they are not always the best option due to the limited spectrum, interference limitations caused by the ever-increasing number of devices, and severe propagation loss in transmission mediums other than air. As a remedy, optical wireless communication (OWC) technologies can complement, replace, or co-exist with audio and radio wave-based wireless systems to improve overall network performance. To this aim, this paper reveals the full potential of OWC-based IoT networks by providing a top-down survey of four main IoT domains: IoTT, IoBT, and IoGT. Each domain is covered by a dedicated and self-contained section that starts with a comparative analysis, explains how OWC can be hybridized with existing wireless technologies, points out potential OWC applications fitting best the related IoT domain, and discusses open communication and networking research problems. More importantly, instead of presenting a visionary OWC-IoT framework, the survey discloses that OWC-IoT has become a reality by emphasizing ongoing proof-of-concept prototyping efforts and available commercial off-the-shelf (COTS) OWC-IoT products.

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A Top-Down Survey on Optical Wireless
Communications for the Internet of Things
Abdulkadir Celik, Senior Member, IEEE, Imene Romdhane, Student Member, IEEE,
Georges Kaddoum, Senior Member, IEEE, and Ahmed M. Eltawil, Senior Member, IEEE.
Abstract—The Internet of Things (IoT) is a transformative
technology marking the beginning of a new era where physical
and digital worlds are integrated by connecting a plethora of
uniquely identifiable smart objects. Although the Internet of
terrestrial things (IoTT) has been at the center of our IoT per-
ception, it has been recently extended to different environments,
such as the Internet of underWater things (IoWT), the Internet
of Biomedical things (IoBT), and Internet of underGround
things (IoGT). Even though radio frequency (RF) based wireless
networks are regarded as the default means of connectivity, they
are not always the best option due to the limited spectrum,
interference limitations caused by the ever-increasing number of
devices, and severe propagation loss in transmission mediums
other than air. As a remedy, optical wireless communication
(OWC) technologies can complement, replace, or co-exist with
audio and radio wave-based wireless systems to improve overall
network performance. To this aim, this paper reveals the full
potential of OWC-based IoT networks by providing a top-down
survey of four main IoT domains: IoTT, IoBT, and IoGT. Each
domain is covered by a dedicated and self-contained section
that starts with a comparative analysis, explains how OWC
can be hybridized with existing wireless technologies, points
out potential OWC applications fitting best the related IoT
domain, and discusses open communication and networking
research problems. More importantly, instead of presenting a
visionary OWC-IoT framework, the survey discloses that OWC-
IoT has become a reality by emphasizing ongoing proof-of-
concept prototyping efforts and available commercial off-the-
shelf (COTS) OWC-IoT products.
Index Terms—Free Space Optical, Optical Wireless Commu-
nication, Visible Light Communication, Optical Camera Com-
munication, Internet of Things, Internet of Terrestrial Things,
Internet of Underwater Things, Internet of Biomedical Things,
Internet of Underground Things.
I. INTRODUCTION
THE IN TE RN ET OF THINGS (IOT) is a revolutionary tech-
nology to integrate the physical and digital worlds by
interconnecting uniquely identifiable smart objects. By paving
the way for a wide variety of applications, the IoT era imposes
a profound paradigm shift in our understanding of almost
all verticals, e.g., science, education, industry, public health
and safety, business, energy, transportation, media, logistics,
and so on. Recent research published by Transforma Insights1
revealed that the number of IoT devices connected globally is
A. Celik and A. M. Eltawil are with the Computer, Electrical and Mathemat-
ical Sciences and Engineering Division (CEMSE), King Abdullah University
of Science and Technology (KAUST), Thuwal, KSA 23955-6900.
I. Romdhane and G. Kaddoum are with the D´
epartement de g´
enie ´
electrique,
´
Ecole de technologie sup´
erieure, Montreal H3C 0L7, QC, Canada.
1https://transformainsights.com/news/iot-market-24-billion-usd15-trillion-
revenue-2030
expected to jump from 7.6 billion in 2019 to 24.1 billion in
2030, thereby generating revenue of more than $1.5trillion.
When the value captured by consumers and customers of IoT
products and services are also taken into account, McKinsey
& Company forecasts that the IoT could enable $5.5trillion
to $12.6trillion in value globally by 20302.
However, the massive traffic generated by a plethora of
devices with diverse quality of service (QoS) requirements
necessitates ubiquitous connectivity among anyone/anything
at any place/time for any service over any network [1].
The International Data Corporation’s recent report expects 22
billion active IoT devices in 2018 to attain 41.6 billion in 2025,
generating 79.4 zettabytes of data3. Wireless communication
technologies have become an indisputable means of connec-
tivity among IoT devices, considering the practical limitations
and challenges of wired infrastructure. Cisco’s 2018-2023
Annual Internet Report states that more than two-thirds of
total traffic is generated by mobile/wireless devices4.
Wireless communication can operate on electromagnetic
(EM) spectrum, which is depicted in Fig. 1 with various bands
along with corresponding frequency ranges and wavelengths.
The inverse relationship between frequency and wavelength
plays an essential role in signal propagation characteristics
as well as hardware complexity and size, which are mainly
determined by the size of the radio front-end, antenna, and bat-
tery. Existing wireless technologies are designed to extensively
exploit the sub-6 GHz region of the microwave bands (300
MHz – 30 GHz) mainly due to their ability to penetrate objects
(e.g., windows, walls, ceils, etc.), thereby causing interference
and co-existence issues among devices operating on the same
band. For this reason, the use of sub-6 GHz bands is strictly
controlled by regulatory bodies (e.g., the Federal Communi-
cations Commission and the Body of European Regulators for
Electronic Communications) and licensed to telecommunica-
tion companies. Albeit exclusive use of the licensed spectrum,
spectrum scarcity and interference management prolong to
be core problems of future generations of cellular networks.
Therefore, the cellular networks still face formidable chal-
lenges to provide provisioned three major service classes
[2]: enhanced mobile broadband (eMBB) for bandwidth-
hungry applications; massive machine-type communications
(mMTC) for device-to-device applications; and ultra-reliable
2https://www.mckinsey.com/business-functions/mckinsey-digital/our-
insights/iot-value-set-to-accelerate-through-2030-where-and-how-to-capture-it
3https://www.idc.com
4https://www.cisco.com/c/en/us/solutions/executive-perspectives/
annual-internet- report/index.html

2
Fig. 1: Electromagnetic spectrum and bands along with corresponding frequency and wavelengths.
low-latency communications (URLLC) for mission-critical ap-
plications. In the sub-6 GHz, only industrial, scientific and
medical (ISM) bands are reserved internationally for license-
free use and are heavily utilized by today’s most common
and mature wireless technologies such as Wi-Fi, Bluetooth,
ZigBee, etc. Although the ISM band is a first-choice if IoT
devices’ low-cost and low-complexity nature is taken into
account, it becomes overcrowded and interference-limited due
to the ever-increasing number of IoT devices.
Recently, the millimeter wave (mmWave) band (30–300
GHz) has recently received lots of attention to help next-
generation wireless networks overcome spectrum scarcity is-
sues. Shorter wavelengths allow a large number of antenna
elements to be placed on small aperture sizes and provide
substantial directivity gain to tackle severe path loss experi-
enced by mmWave systems [3]. To enable and promote multi-
gigabit wireless networks, the 60 GHz (57-71 GHz) mmWave
band is globally considered as an unlicensed band that is
already considered as an integral part of WI-FI technology
and standardized under IEEE 802.11ad Standard [?]. On the
other hand, 70 GHz (71-76 GHz), 80 GHz (81-86 GHz),
and 90 GHz (92-95 GHz) are generally licensed on a shared
basis with the Federal Government operations5. Moreover,
the terahertz (THz) band between 300 GHz and 3 THz is
the most recent topic of interest to support joint sensing
and communication applications to reap the full benefits of
the so-called ”THz gap.” Although THz experiences a more
severe propagation loss than the mmWave, it is expected
to be compensated by a higher directivity gain by packing
more antennas due to the reduced wavelength. However, THz
systems are far-fetched due to required joint advancements
in channel characterization, digital signal processing, and
optical/electronic/plasmonic transceiver design. Albeit abun-
dant spectrum and considerable antenna array gain, the cost
and complexity of mmWave and THz systems may not be
suitable to the spirit of low cost and complexity IoT hardware.
Therefore, all these endeavors towards exploiting extremely
5https://www.fcc.gov/millimeter-wave-708090-ghz-service
higher frequencies with ample spectrum have limited direct
applicability to the IoT hardware. As a consequence, most, if
not all, IoT networks are designed to utilize microwave bands,
at least over the long haul.
The above discussions implicitly focus on the suitability of
the radio frequency (RF) spectrum for over-the-air communi-
cations taking place in indoor/outdoor terrestrial environments.
Nowadays, the use of IoT expanded to a wide-variety of
environments and new variations of IoT are presented in
Internet of X-Things format where X may stand for underwater
[4], underground [5], biomedical [6], space [7], etc. Are RF
signals always the best choice for transmission mediums other
than air? Let us seek an answer for this critical question
through some examples: Even though RF signals are more
tolerant of water’s turbid and turbulent nature, water conduc-
tivity restricts their operational bandwidth and communication
range to 30–300 Hz and 10 m, respectively. Thus, underwater
RF systems are typically power-hungry, costly, and bulky
with large antennas. Alternatively, acoustic communication has
become a proven and widespread underwater communication
technology thanks to its several kilometers long transmission
range. Nonetheless, acoustic systems suffer from high latency
and low data rates due to the low propagation speed (1500 m/s)
and limited bandwidth (10-30 kHz), respectively [8]. More-
over, the RF channel attenuation dynamics in-on-and-around
the human body are quite distinct from regular off-body RF
channels because of the human body’s lossy, heterogeneous,
and dielectric nature. Since the body parts become comparable
to RF wavelengths over frequencies higher than 100 MHz, the
body antenna effects cause peculiar channel variations due
to bioelectromagnetic features of tissues and irregular body
shapes [1].
Since the 1970s, fiber optic communications (FOC) have
played a vital role in the advent of the information age
and transformed the telecommunications industry by high
bandwidth, long-distance, or immunity to electromagnetic
interference (EMI) advantages over electrical transmission.
Unlike the FOC, optical wireless communications (OWC) has
come into prominence over the last two decades to reap the

3
Sec. II
IoT/OWC
Prelims
Sec. III
IoTT
Sec. IV
IoWT
Sec. V
IoBT
Sec. VI
IoGT
Smart City
•
Industrial
•
Commercial
Environmental
Agricultural
•
Offshore Exploration
•
Disaster Prevention
•
Smart Fishing
•
Ocean Sampling
•
Assisted Navigation
•
eHealth
Wellness
Fitness
•
Sports
•
•
•
•
•
•
Mining
Down-Hole
Monitoring
Tunnel
Comm. &
Tracking
•
•
Terrestrial
underWater
Biomedical
underGround
Fig. 2: Survey organization and content.
full benefits of FOCs and the flexibility of wireless commu-
nications. To this aim, the OWC systems transmit modulated
visible/invisible light beams in an unguided medium in lieu
of audio or radio waves. As shown in Fig. 1, the OWC
can operate on a broad unregulated spectrum spanning over
infrared (IR) band between 3 THz and 300 THz, visible light
(VL) band between 300 THz and 3 PHz, and ultraviolet (UV)
bands between 3 PHz and 300 PHz, each has its own virtues
and drawbacks as explained in the next section. All these
OWC modalities pave the way for a broad range of IoT
applications at no cost of spectrum licensing. Therefore, the
OWC can be considered as a promising IoT technology since
most of the optical components used in OWC transceivers
enable a better size, weight, and power-cost (SWaP-C) design
compared to that of RF transceivers [9]–[11]. Nonetheless,
the OWC systems are subject to limitations such as high
dependency on line-of-sight (LoS); performance degradation
due to the characteristics of transmission medium and environ-
ment (e.g., atmospheric events, water turbidity, irregular shape
of reflectors, etc.); the need for pointing, acquisitioning, and
tracking to overcome misalignment; reliability issues caused
by sudden blockage of connections; interference created by
ambient/nearby light sources, etc.
The fundamental takeaway conclusion from the above com-
parative analysis is that no communication technology is the
best fit under all circumstances, especially considering various
transmission mediums and environments. This promotes the
hybridization of wireless technologies to converge offered
advantages to improve the overall performance of IoT net-
works. To this aim, this survey focuses on exploiting OWC
technologies to complement, replace, or co-exist with audio
and radio wave-based wireless systems to enable a wide range
of IoT applications in various mediums and environments.
A. Survey Contributions and Organization
In the literature, many surveys contribute to the field by
focusing on different aspects of OWC technology for a specific
environment. The terrestrial OWC technologies are covered
in the following studies: communication and information-
theoretic foundations are discussed in [9], emerging technolo-
gies and research trends are pointed out by [10], a survey
on various challenges faced by ground-to-satellite and inter-
satellite free space optical (FSO) links and their mitigation
techniques are presented in [11], technical aspects of optical
camera communications (OCC) are reviewed in [12], and VL
communication, sensing, and localization is surveyed from a
communication and networking perspective in [13]. On the
other hand, Physical (PHY) layer aspects of underwater OWC
are covered by [14], [15], which are followed by another
survey focusing more on networking and localization aspects
of underwater OWC [16]. The most of surveys and reviews, if
not all, presented in [9]–[16] mainly focus on replacing exist-
ing wireless infrastructure with OWC technologies instead of
providing a hybrid framework to show how OWC systems can
complement or co-exist with alternative wireless technologies.
Moreover, they mainly focus on PHY layer aspects of OWC
without delving into higher layer networking issues, which are
crucial to realize an OWC-based IoT network.
The main contributions of this survey can be summarized
as follows: To reveal the full potential of OWC-based IoT
networks, we follow a holistic presentation by focusing on
four main IoT domains based on the underlying environment;
Internet of terrestrial things (IoTT), Internet of underwater
things (IoWT), Internet of biomedical things (IoBT), and In-
ternet of underground things (IoGT). As shown in Fig. 2, each
domain is covered by a dedicated and self-contained section
that starts with a comparative analysis and explains how OWC
can replace, complement or co-exist with existing wireless
technologies. After that, each section points out potential
OWC applications fitting best the related IoT domain and
discusses challenges related to communication and networking
aspects of OWC infrastructure. More importantly, instead
of presenting a visionary OWC-IoT framework, the survey
discloses that OWC-IoT has become a reality by emphasizing
ongoing proof-of-concept prototyping efforts and available
COTS products. Each section is concluded with summary,
insights, and future research directions related to the OWC-IoT
domain of interest. Since existing OWC standards introduced
in Section II are mostly designed for the IoTT domain, each
section also concludes how these standards can be extended
to support OWC-IoT in other domains as well.
II. PRELIMINARIES ON OWC SYSTEMS,
NET WORKS,AND STAN DARDS
This section provides readers with preliminaries on OWC
systems, networks, and standards to establish a fundamental
background on the topic and facilitate a better perception of
discussions and analyses. To this aim, we first introduced
the basics of OWC systems by covering various types of
transceiver components and comparing them in terms of key
performance metrics. Then, a brief overview of OWC networks
is presented in a layer-by-layer fashion. Finally, available com-
munication and networking standards on the OWC technology
are listed and compared.

4
TABLE I: List of abbreviations.
AAP
ACK
AMI
AP
APD
AUV
BCC
BER
CFR
CSK
CSMA
CSMA/CA
DCF
DLL
ECG
EMI
FC-LC
FOC
FoCS
FoV
FSO
HVAC
IM/DD
IoBT
IoGT
IoT
IoTT
IoWT
IrDA
IR
ISI
ISM
LD
LED
LiFi
LIFS
LoS
LPT
MAC
MAI
MIMO
mmWave
MP2MP
NIR
NLoS
NPT
OBS
OCC
OFDM
OOK
OWC
P2MP
P2P
PD
PHY
PLC
PPM
PWM
QoS
RF
RoI
ROV
RR
SiPM
SLIPT
SNR
Acoustic Access Point
Acknowledgment
Active Medical Implant
Access Point
Avalanche Photodiode
Autonomous Underwater Vehicle
Body Channel Communication
Bit Error Rate
Camera Frame
Color-Shift Keying
Carrier Sense Multiple Access
Carrier Sense Multiple Access with Collision Avoidance
Distributed Coordination Function
Data Link Layer
Electrocardiography
Electromagnetic Interference
Fiber-coupled Luminescent Concentrators
Fiber Optic Communications
First-order Channel Statistics
Field of View
Free Space Optical
Heating, Ventilation, and Air Conditioning
Intensity Modulation/ Direct Detection
Internet of Biomedical Things
Internet of Underground Things
Internet of Things
Internet of Terrestrial Things
Internet of Underwater Things
Infrared Data Association
Infrared
Inter-Symbol Interference
Industrial, Scientific, and Medical
Laser Diode
Light-Emitting Diode
Light Fidelity
Laser-Induced Fluorescence Spectrum
Line-of-Sight
Lightwave Power Transfer
Medium Access Control
Multiple Access Interference
Multiple Input Multiple Output
millimeter Wave
Multipoint-to-Multipoint
Near-IR
Non-Line-of-Sight
Neuroprosthetic Telemetry
Optical Base Station
Optical Camera Communications
Orthogonal Frequency-Division Multiplexing
On-Off Keying
Optical Wireless Communications
Point-to-Multipoint
Point-to-Point
Photodiode
Physical
Power Line Communication
Pulse Position Modulation
Pulse Width Modulation
Quality of Service
Radio Frequency
Region of Interest
Remotely Operated Underwater Vehicle
Retro-Reflective
Silicon Photo Multipliers
Simultaneous Lightwave Information and Power Transfer
Signal-to-Noise Ratio
SoCS
SPI
THz
UDP
URLLC
UV
V2I
V2V
VCSEL
VL
VLC
WBAN
Second-order Channel Statistics
Serial Peripheral Interface
Terahertz
User Datagram Protocol
Ultra-Reliable Low-Latency Communications
Ultraviolet
Vehicle-to-Infrastructure
Vehicle-to-Vehicle
Vertical-Cavity Surface-Emitting Laser
Visible Light
Visible Light Communications
Wireless Body Area Network
A. A Taxonomy of OWC Systems
The OWC follows different naming conventions in the
literature depending on operational wavelength, underlying
environment, and hardware, which are explained in the sequel.
1) OWC Transceivers: The transmitter of an OWC-IoT
source node can utilize a single laser diode (LD), a single
light-emitting diode (LED), or an array of LDs/LEDs. LDs
emit high-bandwidth coherent and razor-sharp light beams
with a very narrow divergence angle, typically in the order
of milliradians. On the other hand, LEDs are wide-beam
light sources and enable multipoint communications, thus
typically suitable for short-range multicasting or broadcasting
applications. Even though LEDs generally deliver a data rate
performance far below LDs, recent advances in photonics
technology have shown that LED performance can be im-
proved with more complex modulation techniques, discussed
in the next subsection. Regardless of the light source type,
the operational wavelength of OWC systems is determined
based on the characteristics of the transmission medium and
surrounding environment.
On the other hand, OWC receivers generally use photo-
diodes (PDs), also known as photodetectors, which absorb
photons and generate an electrical current in proportion to
the received light intensity. Positive-intrinsic-negative (PIN)
diodes and avalanche photodiodes (APDs) are the two most
common PD types [17]: PIN diodes are suitable for low-cost
low-rate OWC applications as they are cheap PDs tolerant
to temperature fluctuations and low bias. On the other hand,
APDs operate at a very high reverse bias and experience a
higher signal-to-noise ratio (SNR), which makes them suit-
able for high-speed applications with limited ambient noise.
However, APDs are relatively expensive and their performance
is susceptible to temperature variations. A recent interesting
research direction is using solar panels as PDs and energy
harvester for a prolonged operational lifetime, which is espe-
cially critical for IoT nodes placed in hard to reach locations.
Furthermore, modulating retro-reflectors (MRRs) are enablers
of optical back-scatter communications, where an MRR re-
ceiver passively modulates a high intensity light emitted by
an interrogator and reflect back the modulated signal [18].
Another practical OWC receiver is an image sensor, e.g.,
complementary metal-oxide-semiconductor (CMOS) camera
with a rolling or global shutter built-in most consumer-grade
electronic devices. The shutter type determines how images
are captured; although a global shutter develops the entire
image in a single shot, a rolling shutter captures one row of

5
pixels at a time, working across the frame to develop the entire
image. The image sensor transforms the light emitted from the
source node into an electrical signal, quantize into an image,
and finally compress to a specific image format. The projected
result at the camera’s image plane is processed using image
processing techniques, and the information corresponding to
the considered application is extracted. The maximum rate of
an image sensor depends on shutter speed and camera frame
(CFR) rate, which typically range between 30-60 frames per
second, limiting image sensors to low-rate communications.
Nonetheless, image sensors still offer several advantages over
the aforementioned receiver types, such as the larger field
of view (FoV), spatial separation of light, and wavelength
separation [12].
2) Free-Space Optics: Considering the inverse relation be-
tween light diffusion and range, LDs are mostly preferred in
FSO systems to establish point-to-point (P2P) ultra-high-speed
and long-range outdoor links. LDs are generally subject to
emission power requirements, especially for indoor applica-
tions, since the high-power focused nature of laser beams can
be harmful to the eyes. While terrestrial FSO links typically
use the IR band, underwater FSO links prefer blue or green
parts of the VL band based on water type and depth.
3) Visible Light Communications (VLC): On the other
hand, VLC typically refers to LED-based indoor and outdoor
communications, where an access point (AP) equipped with
an array of LEDs serves to communicate with OWC-IoT
devices by establishing multi-point communications, which is
also referred to as Light-Fidelity (Li-Fi) technology taking a
cue from Wi-Fi standard. Although the VLC-APs generally
emit white light to provide a good quality of lighting and
communication at the same time, the uplink communication
avoids eye discomfort by exploiting the IR spectrum, which
is categorized into three bands: IR-A (780 nm-1.4 µm), IR-B
(1.4-3 µm), and IR-C, also known as far-IR (3 µm-1 mm).
Like underwater FSO, underwater VLC systems prefer blue
or green parts of the VL band based on water type and depth.
LEDs are known to be stable and low-cost light sources and
have minimal hazards to human health.
4) Optical Camera Communications (OCC): Another form
of OWC is OCC, where images and information are mo-
mentarily detected through camera sensors whose operational
wavelengths are typically on VL, and IR bands [12]. The OCC
can be considered a low-cost OWC solution given that om-
nipresence cameras are already deployed for several purposes,
such as surveillance cameras, vehicle cameras, smartphones,
etc. Even though OCC supports a low bit rate due to the
limitation, the image sensor can serve a large number of users
by mapping the information into a large number of pixels. The
OCC can be used for a wide range of IoT applications such
as localization, navigation, motion recognition, and augmented
reality.
B. An Overview of OWC Networks
1) Physical (PHY) Layer: The PHY layer is the lowest and
most fundamental layer of OWC networks as it deals with
the bit-level data transmission over the transmission medium.
Therefore, the PHY layer is responsible for many essential
communication functions, including channel estimation, mod-
ulation, power control, signal processing, and coding. For
reliable communication, these functions should account for
medium and environment-dependent propagation characteris-
tics of optical waves such as absorption, scattering, turbulence,
pointing, alignment, etc. In the subsequent sections, these
phenomena will be further brought to readers’ attention to
explain the medium and environment-specific nature of OWC
technologies. There exists three main physical links [16]:
•In a LoS link, light wave travel in a direct path from the
transceiver to the receiver.
•If LoS link is blocked by an obstacle, non-line-of-sight
(NLoS) link may be indirectly established outside of
the direct path between transceivers, typically reflecting
through nearby objects/surfaces.
•A retro-reflective (RR) link in case of MMR usage.
In what follows, we provide a brief overview of typical
modulation schemes suitable for OWC-IoT devices.
Intensity modulation and direct detection (IM/DD) is the
most common modulation framework that varies the light
intensity without the need for phase information. Its non-
coherent nature does not require a local oscillator, reducing
the cost and complexity of IoT devices. The IM/DD can
be implemented through various modulation schemes: On-
Off keying (OOK) is the most straightforward and common
scheme, which turns on and off the light source according
to the information bits. Its simplicity makes OOK suitable
for low-cost and low-complexity IoT devices with mild QoS
requirements. At the cost of time-domain equalization com-
plexity, a wide variety of pulse modulation schemes with better
performance than OOK can also be considered for OWC-IoT
nodes, such as pulse width modulation (PWM), pulse position
modulation (PPM), and pulse amplitude modulation (PAM).
These single-carrier modulation schemes have low spectral
efficiency and suffer from inter-symbol interference (ISI) at
higher bit rates. Therefore, wavelength division multiplex-
ing (WDM) and orthogonal frequency-division multiplexing
(OFDM) are mostly considered to boost spectral efficiency
and mitigate detrimental ISI effects. Of course, these highly
effective schemes face various technical challenges and require
sophisticated solutions, which is beyond the scope of this
work. Therefore, we refer readers to the surveys mentioned
in Section I for a more in-depth discussion of the matter.
It is worth noting that aforementioned modulation schemes
are typically faster than the CFR. Even if it is reduced to
the CFR, the frequency would be less than the human flicker
fusion threshold (FFT), which is usually taken between 60
and 90 Hz, though in certain cases can reach up to 500 Hz
[19], and cause visual inconvenience. To enable flicker free
communication, three main class of OCC modulation schemes
are proposed [20]: 1) screen-based modulation schemes use
visible (QR-like) or invisible (embedded) codes to modulate a
2D array of LEDs; 2) Color-based (e.g., color shift keying
(CSK), color intensity modulation, or their combination),
polorization-based (e.g., binary CSK) and rolling shutter-based
(e.g., frequency shift keying) are oversamples the received

6
signal during modulation; and 3) undersampled schemes mod-
ulate light source at a frequency higher than the FFT by
transforming signals from baseband to passband.
2) Data Link Layer (DLL): The DLL provides the func-
tional and procedural means to transfer data. Since it is
concerned with the local delivery of frames, frame collisions
may occur if the medium is simultaneously used by several
nodes across an OWC network segment. In such a case,
the DLL is also responsible to reduce, prevent, detect and
correct errors that may occur in the PHY layer. Based on
aforementioned physical links, the OWC can support following
logical topologies:
•P2P topology is formed by a unicast (one-to-one) link
between two nodes. One of them behaves as the coordi-
nator/master and is typically authorized to communicate
first on the channel.
•Point-to-multipoint (P2MP) topology consists of P2P
between a reference node (e.g., coordinator, master, end-
point, etc.) and neighboring nodes. The P2MP can be
further divided into the following subcategories:
1) In star topology, the reference node receives from the
rest of the nodes in an all-to-one fashion.
2) In broadcast topology, the reference node transmits the
same data frame to the rest of nodes in a one-to-all
fashion.
3) In multicast topology, the data frame is transmitted
only for intended nodes in one-to-many or many-to-
one fashions.
•Multipoint-to-multipoint (MP2MP) topology contains
several P2P, broadcast, multicast, and star topologies.
•Relay topology involves a cooperative node to connect
nodes who cannot establish any of the above topologies
due to the lack of coverage.
Having all these logical links operating in the same medium
inevitably causes multiple access interference (MAI), having
detrimental impacts on the overall IoT network performance.
Therefore, the DLL comprises two sub-layers: The medium
access control (MAC) lower layer and logical link control
(LLC) upper layer tackle flow control and multiplexing in the
transmission medium and logical links, respectively. Together,
these sub-layers are responsible for eliminating the collisions
of data frames concurrently transmitted and controlling the use
of the transmission medium. The MAC layer ensures control
by employing optical multiple access schemes by multiplexing
nodes in time, code, space, or frequency domains. In this way,
the MAC layer makes PHY layer complexities invisible to the
LLC and upper layers of the network stack by providing a
control abstraction.
3) Network and Transport Layers: The network layer is
responsible for transferring variable-length network packets
from a source to a destination host by means of packet
forwarding and routing through intermediate routers. Being
placed between data link and transport layer, the network
layer translates service requests from transport layer and issues
them to the DLL. On the other hand, transport layer provides
services such as connection-oriented communication, relia-
bility, flow control, and multiplexing. Transmission Control
Protocol (TCP) and User Datagram Protocol (UDP) are two
most common transport protocols used for connection-oriented
and connectionless data transmission, respectively.
4) Application Layer: The application layer specifies
shared interface methods and communications protocols IoT
nodes use in an OWC network. It is an abstraction layer
that standardizes communication and depends on the trans-
port layer protocols to establish node-to-node connections
and manage data exchange. Therefore, this layer introduces
application-specific QoS requirements to the network and
requires lower layers to configure the network and allocate
resources accordingly.
C. OWC Standards
In the light of the recent increase in interest in OWC, several
standardization attempts have been made. We will summarize
the most important ones in this section.
1) Infrared Data Association (IrDA) standard [21]: The
IrDA standard was initially defined by the IrDA, which is
a group of over 160 companies worldwide that intends to
issue standards for wireless IR communications. The first
version, IrDA 1.0, was issued in April 1994 and regularized
the PHY and DLLs. It included the specifications of the
serial IR link, the IR link access protocol (IrLAP), and the
IR link management protocol. It supported communications
with speeds ranging from 2400 bps to 115 Kbps. The second
version of the standard, named IrDA 1.1, was released in
October 1995 to improve communication speeds by extending
the data rate to 4 Mbps. It supports short-range communica-
tions up to 1m distance. IrDA 1.1 uses the 4PPM modulation
scheme. This standard is designed for infrared emitting diodes
(IREDs) operating in the 850-900nm band and supports ad-
hoc and walk-up connections. The IrLAP frame contains three
fields: the address field (A) of the receiver, the control field
(C) specifying the type of frame, and field I containing the
transmitted information. Field C can have one of the following
three values defining the three possible frame types:
•Unnumbered (U): It is used for data link management,
responsible for link connection/disconnection, error re-
porting, and data transmission.
•Supervisory (S): It supervises information transfer by
acknowledging the packet reception, the channel state
(ready or busy), and reporting the frame-sequencing er-
rors.
•Information transfer (I): It contains the transmitted infor-
mation.
2) IEEE 802.11 [22]: This standard was defined by IEEE
in 1997 and focuses on the PHY and MAC layers. It depicts a
single MAC control to be deployed for any PHY layer. Unlike
the IrDA standard, IEEE 802.11 supports diffuse communi-
cation with one or more receivers, which permits only P2P
communication. However, it is considered more sophisticated
than IrDA, with increased hardware cost and complexity.
IEEE 802.11 supports two frequency bands: the 2.4GHz band,
known as WiFi, and the 316-353 THz band, which corre-
sponds to IR-OWC, with a communication range of 10m. This
standard divides the PHY layer into two sublayers: the PHY

7
layer convergence procedure (PLCP) and the physical medium
(PMD). The PLCP ensures error-free transmission and sim-
plifies data reception by adding a header and a preamble to
the transmitted packet. The PMD defines the signal’s format
and the communication requirements. The adopted modulation
schemes are 4PPM and 16PPM with supported data rates of
1Mbps and 2Mbps, respectively. IEEE 802.11 consists of basic
service sets, defined as a group of stations interconnected with
a distribution system. It supports the AP-oriented star topology,
the ad hoc topology, asynchronous and time-critical traffic
(named time-bounded services in the standard), and power
management. This standard adopts three main access methods:
•The distributed coordination function (DCF): The DCF
is based on a carrier sense multiple access (CSMA)
with collision avoidance (CSMA/CA) protocol. In IEEE
802.11, the information is transmitted using the MAC
protocol data unit (MPDU) frame. It is a complete data
unit sent from the MAC to the PHY layer. It contains the
transmitted information, the payload, and a 32-bit cyclic
redundancy check (CRC).
•The DCF with handshaking: Before starting a transmis-
sion, the transmitter sends a request to send (RTS) frame,
and the receiver sends back a clear to send (CTS) frame.
The control frames are used to limit the issue of hidden
stations.
•The point coordination function: In this case, only one
station per cell has priority access to the medium at each
time.
In July 2017, the IEEE 802.11bb initiative was created to
make the needed changes to the MAC layer in IEEE 802.11 to
use light as a wireless communication medium. This standard
considers bandwidths ranging from 380 to 5000 nm with a
single-link throughput of 10 Mbps and a minimum of 5 Gbps
for at least one operation mode.
3) JEITA CP 1221 and 1222 [23]: The JEITA CP 1221 and
JEITA CP 1222 standards were proposed by the Visible Light
Communication Consortium in 2007. While the first standard
is designed mainly for VLC systems, the second is intended
for VL ID systems. The two standards adopt the sub-carrier
pulse modulation scheme, whith JEITA CP 1222 specifically
suggesting using the sub-carrier 4PPM (SC-4PPM). In JEITA
CP 1221, only the 15kHz to 40kHz frequency range is used
for communication purposes, where the data rate is around 4.8
Kbps with a subcarrier frequency of 28.8kHz. JEITA CP 1221
is mainly proposed for localization applications, but it can
also be extended to other applications. JEITA CP 1222 differs
slightly from JEITA CP 1221 by restricting the subcarrier
frequency to 28.8 kHz and specifying the modulation scheme
to be SC-4PPM. It also demands CRC for error detection and
correction.
4) IEEE 802.15.7 [24]: This standard is defined by IEEE
and defines the PHY and MAC layers for short-range VLC
for local and metropolitan area networks. The first version,
IEEE 802.15.7-2011, was released in 2011. Then, a revision
was approved in 2018, and a revised version (IEEE 802.15.7-
2018) was released. Unlike IEEE 802.15.7-2011, which mainly
regularizes VLC communications, IEEE 802.15.7-2018 is ex-
tended to IR, near-UV, and OCC. IEEE 802.15.7 supports the
P2P, star, and broadcast topologies. Moreover, the PHY layer
in this standard can be divided into six classes:
•PHY I supports data rates ranging from 11.67 Kbps
to 266.6 Kbps and adopts the OOK and variable PPM
(VPPM) schemes. It is mainly used for outdoor applica-
tions characterized by low rates and long distances, such
as vehicular communications.
•PHY II supports data rates ranging from 1.25 Mbps to
96 Mbps. It is modeled for indoor and P2P applications
requiring high data rates.
•PHY III supports data rates ranging from 12 Mbps to
96 Mbps. It is dedicated to multiple optical sources and
adopts the CSK modulation scheme. It is optimized for
indoor P2P applications in which multiple LEDs are
joined to produce white light.
•PHY IV supports data rates up to 22Kbps and is intended
for use with discrete light sources.
•PHY V supports data rates up to 5.71Kbps and is used
with diffused surface light sources.
•PHY VI supports data rates in the order of Kbps and is
deployed for video displays.
In this standard, the MAC layer is responsible for generating
network beacons (in the case of a network coordinator),
synchronizing with network beacons, and providing a reliable
link between two peer MAC entities. It also supports unique
optical wireless personal area network association and dissoci-
ation, color function, visibility, dimming, visual indication of
device status and channel quality, device security, and mobility.
This standard has four random access methods: unslotted
random access, slotted random access, unslotted CSMA/CA,
and slotted CSMA/CA. It can support different optical clock
rates to enlarge the range of admissible optical transmitters
and receivers. Considering the independence between the
transmitter and receiver in a device, the standard supports
asymmetric clock rates between two devices. IEEE 802.15.7
adopts symmetric-key cryptography to reinforce communica-
tion security where higher layers provide the key. The stan-
dard’s frame structure can be summarized as follows: a beacon
frame is used by the coordinator to send beacons; a data
frame is used for data transfer; an acknowledgment (ACK)
frame is sent to confirm successful reception of the data; a
MAC command frame is responsible for dealing with all MAC
peer entity control transfers; and a color visibility dimming
(CVD) frame controls the light intensity between data frames
to support dimming and visually provide information such as
communication status and channel quality to the user.
5) IEEE 802.15.13 [25]: This standard is mainly a revision
of the IEEE 802.15.7 standard. It is designed for high-speed
and bidirectional mobile communications such as audio and
video multimedia services. It supports data rates of up to 10
Gbps over a range of 200 m. It mainly regularizes the PHY
and MAC layers for VLC communications. It can accomodate
advanced PHY layer techniques such as adaptive modulation,
optical OFDM, relaying, and multiple input multiple output
(MIMO) communications. This standard can be used in a vari-
ety of scenarios, such as smart homes, industrial environments,
and vehicular communications.

8
TABLE II: OWC Standards.
Standard Year Band Range (m) Topology Modulation MAC protocol Frame types Security
IrDA 1994 IR 1 ad/hoc
walk-up 4PPM N/A U/S/I N/A
IEEE 802.11 1997 IR 10 AP oriented
ad-hoc
4PPM
16PPM CSMA/CA
MPDU
RTS
CTS
N/A
Jeita CP-1222 2007 VLC N/A N/A SC–4PPM N/A N/A N/A
IEEE 802.15.7 2018 VLC/IR/UV Short range Peer-to-peer
Star
Broadcast
OOK
VPPM
CSK
CSMA/CA
Beacon
Data
Acknowledgement
MAC command
CVD
Symmetric-key
cryptography
IEEE 802.15.13 2021 200
ITU G. VLC 2019 VLC/IR N/A
P2P
P2MP
MP2MP
Relayed mode
Centralized
OFDM N/A
MAP/RMAP
MSG
ACK
RTS
CTS
STMG
PROBE
ACKRQ
GMSG
BACK
ACTMG
IND
FTE
N/A
6) ITU G.VLC [26]: This standard is also known as ITU
G.1991. It specifies the system architecture, the PHY layer,
and the DLL for high-speed VLC and IR communications.
This standard uses the OFDM modulation scheme and can
support data rates of up to 1.7 Gbps. ITU G.VLC is suitable
for the following topologies: P2P, P2MP, MP2MP, relay,
and centalized, where a global master coordinates different
P2MP and MP2MP domains. Moreover, different frame types
are defined for this standard, such as MAP/RMAP frames;
unidirectional/bidirectional message (MSG)/(BMSG) frames;
control frames (e.g., ACK, RTS, CTS); ACK retransmission
request frame (ACKRQ); probe frames (PROBE), etc.
D. Summary and Insights
In this section, we first provided OWC transceiver types
and pointed out their suitability for different applications by
comparing their virtues and drawbacks from key performance
metrics. A taxonomy of OWC technologies is also introduced
to facilitate discussions in the subsequent sections. Then,
we briefly explained OWC networks based on a simple 5-
layer approach and presented available standards on OWC
technologies.
It is worth noting that only IEEE standards provide both
PHY and MAC layer specifications, while the rest is merely
designed for the PHY layer. Why do not the IEEE standards
offer a whole network protocol stack and limit themselves
to PHY and MAC layers? The main reason is that OWC
specific part of the network occurs in the first two layers and
higher layers follow the wired internet backbone protocols.
At this point, it is important to note that two critical aspects
limit all these standards: 1) They merely focus on terrestrial
networks and are not designed to define other mediums and
environments, and 2) They are designed for a pure OWC
network and are not suitable for the hybrid operation of OWC
networks with existing RF-based wireless networks. In the rest
of the paper, we further discuss these issues based on the
underlying transmission medium and environment.
III. INT ER NE T OF TERRESTRIAL THINGS (IOTT)
Lately, we have witnessed an upsurge in smart devices
that are used by almost everyone. These smart devices are
interconnected through the internet, which emphasizes the
importance of the IoTT in our era. IoTT is omnipresent in
many agricultural, smart city, and commercial applications.
Figures 3, 4, 5, and 6 present a detailed overview of the
different IoTT applications.
A. The OWC-IoTT in Smart Agriculture
1) The OWC-IoTT for Smart Farming: To meet the ex-
pected food demand of the ever-increasing human population,
agricultural production is required to be doubled by 2050 [27].
The agriculture sector must achieve such a challenging goal
under a diverse set of significant difficulties, such as land
degradation, lack of farmable land, labor force shortage, and
climate change threats (e.g., frequent and intense drought,
storms, and heatwaves) [27]. Therefore, IoTT can help achiev-
ing this goal by enabling smart and precision farming to
improve the quality and quantity of polyhouse/greenhouse veg-
etation, increase cost efficiency, better manage the resources
such as water and soil, and manage crops. The current IoTT
devices developed for agriculture mostly, if not all, exploit RF
waves [28], [29], which have harmful impacts on the health
condition and growth of plants [30], [31]. On the contrary,

9
Fig. 3: OWC-IoTT based smart farming.
OWC can be extremely helpful as lightwaves at specific
wavelengths have been shown to improve crop productivity,
quality, and taste. This section discusses how LEDs and optical
cameras can facilitate smart and precision farming together
and facilitate a safe, reliable, and energy-efficient OWC-IoTT
infrastructure, as depicted in Fig. 3, requiring little or no
additional cost.
Leveraging LEDs and Cameras on Smart Farms: Before
discussing how the OWC-IoTT can facilitate smart and pre-
cision farming, let us first explain how LED-based colored
illumination and optical camera sensing can boost overall
productivity. Investigations on the response of tomato leaves’
photosynthetic capacity under different light wavelengths have
shown that a combination of white, red, and blue lights
improves photosynthetic efficiency, while red and purple light
increases crop yield [32]. Another study found that a mixture
of red and blue light or red, green, and blue light optimized
the performance of the photosynthetic apparatus. Moreover,
an increase in the proportion of blue light in the red and
blue light mixture induced the yield growth [33]. The impact
of illumination with different wavelengths oncherry tomato
quality was tested at different growth stages of the cultivar
in [34]. It was demonstrated that the red light illumination
significantly improves the quality and other health-related
elements of the cherry tomato cultivar at the green-mature
stage. Similar studies have been conducted for other types
of vegetables and herbs. For instance, it has been found that
purple light obtained by combining red and blue light speeded
the growth of lettuce plants [35]. Likewise, a blue, red, and
far-red light mixture and blue and red light mixture boost the
growth of the sweet basil yield compared to white illumination
[36]. All these illumination benefits can be leveraged by using
low-cost LEDs, which are recognized to be more energy-
efficient than traditional light sources and allow fast-and-easy
color change. Since LEDs are already an integral part of VLC
transmitters, VLC-APs can facilitate both plant illumination
and communication simultaneously.
The precision agriculture mainly collects crop growth and
health indicators through various sensing methodologies and
exploit data analytics to make decisions for breeding, pruning,
fertilizer and pesticide management, and automated harvesting.
In particular, optical cameras can estimate phenotyping vari-
ables from intensity, spectral, and volumetric measurements
to characterize plants, detect plants/fruits, and assess plant
physiology [27]. As mentioned in previous sections, optical
cameras can be used beyond sensing and imaging purposes.
Modulated light beams emitted from VLC-APs are reflected
from plants and received by the camera as images, thereby
allowing optimal cameras to be used for joint sensing and
communication.
Integrating VLC, OCC, and FC-LC
In light of the above discussions, overall crop productivity and
quality can be improved significantly by leveraging low-cost
LEDs and optical cameras for smart and precision farming.
Indeed, combining the two opens up a new perspective on
OWC research that has not yet been fully explored. To the best
of our knowledge, OWC-IoTT-based smart farming has been
only considered in [37], [38], and [39]. In [37], Javed et al.
exploit VLC and OCC technology to create a smart farm where
white ceiling LEDs provide both downlink signaling and grow
lights needed for photosynthesis, while optical cameras capture
the modulated green light reflected by the vegetables in the
uplink. Although the authors demonstrate a very appealing and
complete OWC-IoTT system that integrates VLC and OCC
technologies in an indoor smart farming scenario, they do not
harness the true potential of LEDs and cameras by reaping the
aforementioned benefits. The authors in [39] propose using
VLC to sense the temperature, humidity, soil moisture level,
and luminosity in an environment. The data collected by
sensors is processed in the cloud for business intelligence
and analytics to automate polyhouse countermeasures and
fertilizer suggestions for automated and sustainable polyhouse
farming. In [38], the authors investigate the performance
of an outdoor OCC-based wireless sensor network (WSN)
that is implemented in an emulated farm environment and
linked to the internet. They found that scalable and low-cost
communication with a 100 m range is feasible under a 7.5 bps
rate.
An interesting future research direction is the design of
energy self-sufficient OWC-IoTT in an indoor farming en-
vironment, where plants are constantly illuminated by LEDs
that also wirelessly powers OWC-IoTT nodes located across
the polyhouse. This concept can be further extended to si-
multaneous lightwave information and power transfer (SLIPT)
for better results. Another potential OWC technology is fiber-
coupled luminescent concentrators (FC-LC), mainly designed
to harvest sunlight and convert its energy into electricity.
In [40], Makarov et al. used FC-LC technology for lower
canopy lighting and reported a 7% boost in tomato yield.
Since they are adjustable to deliver peak photoluminescence
at different wavelengths, FC-LCs can also be excited by VLC-
APs to deliver light to lower canopy, i.e., delivery of both light
connection and power to shaded areas. More importantly, the

10
authors also developed an LC detector to show how FC-LC
can be used for both illumination and communication at the
same time.
The OCC is another promising technology for smart farm-
ing, considering the omnipresence of cameras on farms for
surveillance purposes or in the mobile phones everyone car-
ries. In [41], three optical sensing instruments, namely the
Agriserver, the Agrigadget, and the laser-induced fluorescence
spectrum (LIFS) monitor. Agriserver sensing nodes in farms
include single reflex lens cameras and are controlled re-
motely (in laboratories) over the internet. The use of cameras
ensures detailed remote tracking of the farm by capturing
high-definition images that can detect an insect measuring
less than 1cm long over 10 m away. The Agrigadget, on
the other hand, is designed for instant mobile tracking of
farms via a smartphone-based spectroscopic device and a hand
framing camera. The farmer can scan the color spectrum of
the plant’s surface using his phone to evaluate the quality of
the product, such as the maturity and growth of the fruit.
The collected data can be processed using existing online
agriculture software applications. As for the LIFS monitor,
it assembles the physiological characteristics of vegetation.
To be able to use this technology for outdoor farms, mobile
LIFS monitor and LIFS light detection and ranging (Lidar)
are proposed to instantly diagnose plants using chlorophyll
fluorescence.
2) The OWC-IoTT for Smart Livestock Farming: As illus-
trated in Fig. 4 and Fig. 5 , another important agriculture
field for OWC-IoTT is animal and fish farming, respectively.
Global demand for animal products is expected to increase
by 40% in the next 15 years, which emphasizes the urgency
of ensuring production sustainability and safety in this sector.
However, animals are threatened by stock theft and illness,
which can sometimes be detected too late and leads to the
loss of the animal. According to the United States Department
of Agriculture, almost 3.9 million cattle and calves died from
various causes in 2015, resulting in a loss of $3.87 billion loss
[42]. Several works have been performed in the literature have
investigated smart animal farming for the supervision and care
of livestock. IoT has been used on smart farms to monitor
animals and their environment. For instance, an IoT-based
monitoring system has been proposed in [43] that enables
remote control of the farm using wireless sensors by filling
feed and water containers, tracking temperature and humidity,
exhausting biogas produced by the animals’ waste, detecting
potential fires, and surveilling the farm via an IP camera.
Animal health can also be diagnosed remotely through internet
using wireless sensors that collect physiological information
about the animal such as its temperature, heart rate, and
rumination with surrounding temperature and humidity [44].
IoT solutions have been introduced for smart aquaculture
farming as well [45]–[47]. Huy et. al. proposed a WSN that
automates, remotely controls, and monitors shrimp farms to
limit energy consumption and human intervention and ensure
a quick response to changes in the production pond [45].
Farmers can also remotely monitor water parameters in fish
farming ponds such as the pH level, temperature, luminosity,
and water level [46], [47].
Fig. 4: OWC-IoTT based smart livestock farming.
Fig. 5: OWC-IoTT based smart fish farming.
Leveraging LEDs and Cameras in Livestock Farming:
Scientific results have shown that light conditions can improve
animal’s health, behavior, and physiology, and thereby signif-
icantly impact business profitability [48]–[53]. Light plays an
essential role in the development and functioning of poultry’s
reproductive system. The intensity and color of light, and the
duration of exposure to it can be tuned to optimize the bird’s
maturity and egg production depending on its age and type
[48]. It has also been proven that light characteristics affect
the welfare and health of poultry [49]. Moreover, studies have
shown that an optimal photoperiod has a remarkable impact on
dairy production, reproduction, feed efficiency, and maturity
[50]. Light can also be beneficial for marine life. For instance,

11
Jung et al. demonstrated that green light LEDs are useful for
improving the health of goldfish when exposed to thermal
stress by enhancing their antioxidant capacity and reducing
oxidative stress [51]. The work in [52] proved that the blue
and white light spectrums play a vital role in manipulating the
acute stress response of the sea bass fish. The impact of blue,
green, red, and white light on the performance of Atlantic cod
and turbot are investigated in [53], where blue light has the
best effect on the growth of the larvae for both considered
species and the use of light improves the performance of the
larval and its survival. Furthermore, good lighting improves
the working conditions in the barn. It relieves farmers’ eyes,
simplifies animal control, and reduces the risk of occupational
accidents. In addition, modern, efficient light fittings with a
long service life reduce energy and maintenance costs.
Even though smart farming applications proposed in [44]–
[47] exploit RF-IoTT solutions, the illumination advantages
mentioned above highlight the importance of light in animal
farming, proving the eligibility of introducing OWC-based
IoTT solutions for smart animal farming. To the extent of
our knowledge, no work has proposed an OWC-IoTT based
system for smart animal farming yet. Similar to smart farming,
the LEDs deployed for illumination purposes can be used as an
AP to provide connectivity to OWC-IoTT nodes located in the
surrounding environment as well as nodes placed on animals
to track their physiological signs. It is worth noting that OWC-
IoTT nodes placed on farm animals’ bodies experience differ-
ent channel characteristics and require various considerations.
Therefore, we refer readers to Section V for more details to
understand how OWC around a body is different from regular
OWC. For OWC-IoT nodes placed on fish, it is better to
communicate with an AP deployed underwater, which falls
into the realm of OWC-IoWT presented in Section IV.
Precision animal farming introduces process engineering
techniques to ensure the real-time management of animals’
wellbeing and production. Specifically, optical cameras can
supervise dairy cows to detect potential lameness, which
affects almost a quarter of dairy cows. They can also be used
to monitor the behavior and weight of birds and notify the
farmers about potential problems in the poultry house [54],
[55]. Furthermore, 2D/3D cameras can be used to supervise
pigs’ behavior in barns to identify a potential illness at an
early stage [56]. As previously mentioned, cameras deployed
to surveil/monitor animal farms can be used for OCC systems,
where the light emitted by LEDs situated on an animal’s body
or reflected on it from the ceiling can be detected by the
camera to ensure hybrid sensing and communication.
B. The OWC-IOTT in Smart Cities
Smart cities are one of the most prominent digital ecosys-
tems where IoTT devices can facilitate a convenient life
through applications tailored for indoor or outdoor digital
services. For indoor services, the IoTT integrates smart homes;
residential, commercial, industrial, and educational buildings;
and essential city services such as public health and safety
(e.g., hospitals, fire/police departments), smart grid, and smart
water. Likewise, the IoT can consolidate the mobility ecosys-
tem for outdoor services by facilitating vehicular networks
interconnected with traffic signs and smart infrastructures
mentioned above. This is useful in protecting pedestrians,
avoiding potential traffic accidents, collecting up-to-date traffic
information, and optimizing the quality of transportation sys-
tems [57]. However, the remarkable increase in these devices
and applications requires much more bandwidth than what the
RF spectrum can provide. Also, RF bands have limited use in
specific environments where health-related concerns are prior-
itized [58]. At this point, OWC-IoTT devices can be a perfect
fit for specific smart city applications and environments where
the required infrastructure is readily available. Accordingly,
this section will focus on how OWC-IoTT can complement its
RF counterparts, offload traffic, and reduce the ever-increasing
radio interference, which is illustrated in Fig. 6.
1) Smart Infrastructures: Smart homes include various IoT
devices and applications that provide a wide variety of services
such as environment control (lighting, heating, water, and gas),
climate sensing, health monitoring, camera surveillance, en-
ergy management, to name a few [59]. Smart home technology
aims to comfort human life; provide independent living for
the elderly, disabled people, and rehabilitating patients; and
protect occupants from home accidents and home invasion
crimes (e.g., burglary, robbery, and trespassing). Smart homes
are further extended to smart building applications that collect
information from various IoT sensors to reduce the energy cost
of heating, ventilation, and air conditioning (HVAC); facilitate
residential security and surveillance; provide fire safety; im-
prove and optimize lighting; and protect from natural disasters
( e.g., earthquakes, floods, etc.). Although RF-IoT devices are
heavily employed for smart homes and buildings, OWC-IoTT
devices can be a viable alternative because illumination is
already needed and internet connectivity is readily available
in smart homes and buildings. Moreover, OWC is known
to be safer and healthier than RF waves and can provide a
higher level of PHY layer security as the light does not go
through walls, which ensures the privacy and confidentiality
of information exchanged indoor space [60]–[62].
VLC, OCC, and IR communications are the three main
OWC technologies used for indoor systems. Since cameras
and energy-efficient LED lamps are already required in smart
homes and buildings for surveillance and illumination pur-
poses, respectively, the cost of their use for communication
and networking can be expected to be minimal. Moreover, a
VLC-based smart home system guarantees better data rates,
bit error rates (BER), and power efficiency compared to RF-
based smart home systems [63]. Besides, using optical waves
to deploy smart home technologies minimizes the interference
with RF devices. For these reasons, OWC is a suitable
means of communication for smart homes and buildings. The
rest of this sub-section discusses how VLC, OCC, and IR
communications can be leveraged for indoor communication,
positioning, tracking, and navigation.
VLC-Based Smart Homes and Buildings: In the past
few years, a variety of solutions have been proposed in the
literature for controlling smart home appliances using VLC. It
includes smart temperature and HVAC monitoring [64]–[66],
smart lighting [67], smart door lock [68], and different other
services. The work in [69] proposed a VLC and augmented

12
Fig. 6: OWC-IoTT based smart city and mobility.
reality-based monitoring application for smart home devices in
airbnb rentals. The presence of various solutions in the same
indoor environment leads to MAI that can degrade the signal
quality and hence the performance of these technologies.
For this, multiple access solutions are stated in the literature
to overcome this challenge. Time division duplexing is one
procedure that ensures the interconnection between the various
sensors of a home automation system [70], [71]. Orthogonal
code-based wavelength division and color-coded multiple ac-
cess schemes can also ensure multi-device bidirectional com-
munication and inter-device synchronization for smart home
technologies [72], [73]. The KNX communication standard is
another option for intercommunication between the different
technologies existing in smart homes, such as the HVAC and
lighting [74], [75].
Similar to the role of Ethernet for WiFi, power line com-
munications (PLCs) can be used as a backbone network for
VLC-based smart home systems. Power lines can transmit
data to LEDs in the room’s ceiling or in-wall sockets. Af-
terward, the forwarded information reaches users through a
VLC link [76]. With the use of PLC, no implementation
of new cables is needed. Hence, they are easier andless
expensive to deploy. However, since power line networks
were not designed initially for communication purposes, their
transmission suffers from low data rates. Some works in the
literature have focused on integrated PLC/VLC systems for
smart homes and invested improving the communication by
proposing adequate modulation schemes such as the discrete
multitone quadrature amplitude modulation (DMT-QAM) and
OFDM [77], [78].
Furthermore, VLC systems can be used for detection in
smart homes and buildings. Authors in [79] showed that an
LED-based VLC system could detect the presence of people
in a building and their activities. This is done by combining the
detected information with available human activity models and
automating parameters such as lighting, heating, ventilation,
and security. Since light is a safe wave, VLC solutions are
convenient for health-related applications. They are used to
protect human lives by monitoring microscopic entities such
as particulate matter [80], [81]. In RF-free environments,
biomedical data can be transmitted using VLC in a simple,
safe, and cost-effective way to ensure real-time medical signal
monitoring [82]. It became possible to provide secure and
constant assistance of disabled people and the elderly using
LED-based sensors that transmit the collected information
using VLC links [83], [84].
IR-Based Smart Homes and Buildings: Moreover, IR
communications are another promising solution for smart
homes. Since IR provides reliable communication for both
daytime and nighttime, it helps avoid eye discomfort that may
be caused by VL during the night or coming from locations
other than the ceiling [85], which makes IR transceivers
common for uplink communications. IR sensors have been
widely used to remotely control smart home appliances such
as the AC, TV, and projector [86]. In [87], a low-cost human-
detection method is proposed using IR temperature sensors for

13
smart home systems. The IR sensors are placed at the entrance
of a room to detect the entry of a person by distinguishing
the human body temperature from the room temperature.
IR temperature sensors are also used to supervise objects
and ambient room temperature. The collected data can be
accessed through a web application [88]. IR analyzers are
also deployed to control the air quality by tracking the CO2
level [89]. In [90], IR array sensors are used to monitor
building occupancy. IR sensors can also replace cameras in
situations where privacy is a point of concern by detecting
human activity without needing images [91]. Human posture
is also detected using low-resolution IR sensors and a deep
convolutional neural network [92]. Authors in [93] proposed
a home appliance automation system for severely disabled
people that supervises residents by analyzing the frequency
of the operation of these appliances. Near-IR (NIR) cameras
are utilized to remotely monitor the heart rate using facial
video data [94]. IR communications can also be handy for
biomedical data transmission in hospitals and nursing homes
[95]. Information such as the electrocardiography (ECG),
blood pressure, and body temperature of each patient can be
transmitted periodically using IR-LEDs and IR-PDs.
IR communications can also be combined with other tech-
nologies. For instance, a joint VL-IR communication can be
integrated with PLC for indoor positioning applications in
hospitals [96]. A combined RF-IR fingerprint identification
method for multi-resident homes is proposed in [97]. Residents
are identified by measuring the RF received signal strength and
tracking the timing information provided by wall-mounted RF
transceivers and IR sensors, respectively. In [98], a joint RF-
IR indoor high-definition video streaming is proposed where
the uplink and downlink are done using RF and IR waves,
respectively. Passive IR sensors are also used along with
ultrasonic sensors to detect motion by being connected to a
web camera located at the home doorstep. This is done using
a face recognition algorithm to reinforce the security of the
house [99].
OCC-Based Smart Homes and Buildings: OCC is another
adequate means of communication in smart homes. It is effi-
cient at detecting human presence indoors. A low-cost commu-
nication solution can be implemented using ceiling-mounted
LEDs and the camera of a smartphone to automatically control
the different parameters of the room [100]. It is used in
environment monitoring as well where temperature, humidity,
and CO2 sensors can transmit information to cameras using
LEDs [101]–[103].
OWC-Based Indoor Positioning, Tracking, and Naviga-
tion: OWC is especially suitable for positioning, tracking,
and navigation in private and public indoor spaces, shopping
centers, factories, airports, and healthcare units [104]. VLC
systems can be used for indoor positioning applications where
various LEDs send their location to a PD placed on the user’s
device or the object to be located [105]–[107]. VLC-based
positioning systems are also feasible in situations where the
transmitter [108] or receiver [109], [110] is tilted. Similarly,
VLC systems are implemented for indoor tracking applications
such as remotely controlling a mobile robot or tracking an
intruder for security purposes [111], [112]. Moreover, VLC-
based navigation services proved to be safe and reliable
support for blind people to find objects and locations in an
unfamiliar indoor environment. The light signals sent by the
fixed transmitters on the different angles of the room enables
the blind person to continuously relocate himself. [113].
IR sensors are another alternative for positioning applica-
tions. Pyroelectric IR sensors mounted on the ceiling are used
for non-terminal indoor localization systems where the user is
not equipped with a terminal device [114], [115]. Alternatively,
IR-based localization can be achieved by placing IR-LEDs
on moving objects that emit IR light, which is detected by
receivers on the ceiling [116]. In a similar fashion, IR sensors
are deployed for indoor tracking applications [117]–[119].
Cameras are equally convenient for indoor positioning ap-
plications. The position information emitted from VL LEDs
is detected by a camera, aiming to localize the user or the
device [120], [121]. Indoor localization is also possible using
IR cameras equipped with IR-LEDs and markers attached to
walls in the indoor space. The person is detected when he
passes in front of the camera and blocks the propagation of
the emitted IR light [122]. Otherwise, indoor positioning can
be performed using smartphone IR-LEDs as transmitters and
surveillance cameras as receivers [123].
Although OWC solutions for localization, tracking, and
navigation have been widely investigated in the literature
recently [124], [125], these technologies still face challenges.
First comes the LoS problem where the presence of any
object between the transmitter and the receiver can fail the
communication. Leveraging shadows can improve the system
performance, but it still does not reach the LoS performance
[126]. Hence, more extensive future research should consider
this problem. Interference is another challenge that arises
in the presence of multiple light sources and threatens the
detection accuracy of these systems. It is still considered an
open problem to be investigated. Eventually, machine learning-
based solutions have been proposed recently for VLC-based
indoor localization. For instance, some researchers used the
K-nearest neighbour (KNN) classification algorithm [127]–
[129], some used the neural network [130]–[132], while others
used deep long short-term memory (LSTM) model [133].
Considering the impact machine learning techniques, including
deep learning and reinforcement learning, have had on detec-
tion techniques such as smart sensing, we believe that these
techniques should be further incorporated into indoor optical
localization, tracking, and navigation technologies.
2) Smart Mobility: Recently, the remarkable increase in
means of transportation has aggravated problems such as de-
lays caused by traffic congestion, fatal accidents, fuel and en-
ergy consumption, and pollution. Hence, an essential section of
smart city technologies is focused on intelligent transportation
systems [134], [135] to improve road safety, solve traffic prob-
lems, and make driving easier thanks to vehicle-to-everything
(V2X) communications [136], [137]. The majority of the work
that has been led in this field has focused on the use of RF
solutions [138], [139]. Despite the long-range communication
offered by radio waves, it suffers from limited spectrum,
transmission delays, and security issues. Consequently, OWC
technologies can be seen as an excellent complement to RF for

14
vehicular communications. The omnipresence of light sources
and surveillance cameras in vehicles and roads makes the
implementation of OWC easier and cheaper. Also, it affords
much larger bandwidth and faster communication compared
to RF, which allows high data rates. However, OWCs suffer
from short ranges and are highly affected by several challenges
related to the nature of light and the surrounding environment
[140], [141]. The rest of this subsection discusses how VLC,
OCC, and FSO communications can be leveraged for vehicular
communications considering the faced challenges.
VLC-Based Vehicular Communication:
Unlike the indoor environment, VLC-based vehicular com-
munications face challenges related to the nature of light
propagation and the surrounding environment. First, VLC
links are strongly dependent on the light source [142]–[144].
For instance, standard headlights have an irregular and more
challenging radiation pattern than taillamps [145]. In fact,
even the presence of some dirt in front of the light source
may change the shape of the radiation pattern, which affects
the quality of the communication [146], [147]. Second, the
reflection of emitted light on different objects like walls, cars,
and the ground creates NLoS links that affect the overall
performance [148], [149]. Also, the mobility of vehicles and
the road conditions constitute other challenges for VLC-based
vehicular communications, as they introduce instability in the
distance and orientation between the source and the receiver as
well as alignment problems [150], [151]. Furthermore, outdoor
ambient light sources as well as MAI affect the quality of the
communication depending on the power strength of the light
that may saturate the receiver [149], [152]. The interference
can also happen between different vehicular VLC systems
located in the same area, especially during rush hours, which
may lead to packet loss and link quality deterioration [153].
Weather conditions are another significant outdoor challenge
faced by VLC-based vehicular communications [154]. The
presence of fog, rain, snow, turbulence, and solar irradiance
leads to the divergence and attenuation of the light signal,
which degrades the range and reliability of the VLC link
[154]–[159].
In the light of these challenges, several works have proposed
VLC-based solutions for vehicular communication. In [160],
Kobbert et al. focused on enhancing road safety at night by as-
sessing the effect of various automotive headlamp parameters
on drivers and optimizing the light intensity depending on the
driving distance. In [161], a highly linear transceiver system
is presented for VLC-based vehicular communications using
white LED headlights. The problem of strong background
radiation is addressed in [162] by introducing a vehicular VLC
solution that enables dynamic saturation control by using ad-
justable attenuators (i.e., density filters). To maintain a reliable
link despite cars’ mobility, a dynamic PHY layer design that
predicts real-time SNR values considering the current location
of vehicles [163]. The MAI issue is addressed in the literature
as well. The interference experienced in vehicular VLC can be
reduced at the receiver end by implementing a liquid-crystal-
panel spatial light modulator or integrating CMOS current
mirroring to filter ambient light [164], [165]. It can also
be diminished using matrix headlights-based adaptive front
lighting systems that identify the most convenient LEDs of
the headlight to communicate with the receiver [166]. Single-
photon avalanche diodes (SPADs), characterized by their high
sensitivity, can withstand adverse weather conditions when
used in vehicular VLC systems [167]. Moreover, the low
latency of light propagation makes VLC an adequate tool to
communicate safety-related and critical messages [168].
Several vehicular VLC standards have been defined lately,
namely the IEEE 802.15.13 [169] and the IEEE 802.15.7
[170], [171]. The implementation of vehicular VLC using
the IEEE 802.11 WiFi standard has also been tested in the
literature. In [172], an IEEE 802.11-compliant vehicular VLC
system is tested by integrating custom-made driver hardware,
commercial vehicle light modules, and an open-source imple-
mentation in GNU Radio.
VLC solutions have been proposed in the literature for
vehicle-to-vehicle (V2V) communications [173]. Using car
lights, the 2019 Consumer Electronic Show presented an OWC
system that enables intercommunication between vehicles
[174] using OFDM modulation. In [175], Bachedergue et al.
evaluated the reliability of V2V VLC in real-world driving
scenarios and compared the performances of OFDM and
OOK modulations. The short communication range problem
is also fixed by a multi-hop vehicular VLC, where relay
vehicles are included in the transmission [176]–[178]. VLC
can also be implemented for vehicle-to-infrastructure (V2I),
and infrastructure-to-vehicle (I2V) communications where cars
communicate with traffic lights and street lamps to exchange
information [179], [180]. Furthermore, a cascaded I2V and
V2V VLC communication system has also been investigated
where the first vehicle receives safety messages from an LED
traffic light and forwards them to the next car [181], [182].
Bidirectional communications are also studied for V2V, and
V2I VLC, where a full-duplex communication is enabled
between communicating vehicles and between individual ve-
hicles and traffic lights [183]–[185]. In [186], Demir et al.
proposed a dynamic soft handover technique based on coor-
dinated multipoint transmission. A vehicle speed estimation
system based on sensing the headlamp’s VL variation is tested
in [187]. For path-control purposes, vehicles can keep track
of the distance between them via exchanging a clock signal
contained in Manchester-encoded signals [188]. VLC also
supports the exchange of kinetic information between cars via
the use of a control area network bus implemented on each
vehicle to collect data from the car’s sensors, and actuators
[189]. In [190], Shen et al. proposed a VLC-based solution
for smart parking that performs three functions, namely cars ,
free parking spots identification, and positioning.
VLC solutions have also been proposed for platooning, an
application of intelligent transportation system that aims to
enhance road safety and increase road capacity by grouping
driving cars. VLC systems showed to be convenient for
minimizing transmission latency, which is a critical factor for
such applications [191]. VLC interference is another challenge
faced in platooning, mainly because of the small distances be-
tween the grouped vehicles. Implementing spatial multiplexing
for modern adaptive front-lighting decreases interference and
increases the robustness and reliability for VLC platooning

15
technologies [192].
OCC-Based Vehicular Communications:
Over the previous years, the deployment of OCC for ve-
hicular communication has been studied by researchers [193].
Considering the dynamicity included in vehicular communi-
cation scenarios, increasing the data rate is crucial to maintain
fast communications [194]–[197]. Also, outdoor environments
are characterized by the presence of sunlight and various
artificial light sources, which intensify the interference issue
for OCC links. Specific modulation schemes and constellations
are suggested in the literature to solve the interference problem
and increase the data reception accuracy [198]–[200]. Interfer-
ence can equally be reduced by limiting the camera’s FoV or
by adapting a region selection approach in capturing images
[195], [201]. In [202], a bit detection algorithm based on the
average greyscale ratio and the gradient radial inwardness is
evaluated to improve the detection accuracy. Furthermore, the
region of interest (RoI) tracking is a considerable challenge
faced by OCC due to the mobility of vehicles. It can be
resolved using the Bayesian tracking technique, or a neu-
ral network-based encoding and decoding mechanism [203]–
[205]. In [206], Sturniolo et al. proposed a new RoI technique
that fixes the signal distortion and diminishes the packet loss
for bursty channels. Moreover, omitting the flickering problem
at the transmitter and decreasing the packet error rate at the
receiver are significant matters in OCC systems. Implementing
a low-frame-rate camera-based solution that increases the
transmission bandwidth and applies undersampling techniques
proved to be a good solution for the flickering problem [207],
[208]. But to the extent of our knowledge, the issue of high
error rates in bursty channels and bad weather conditions
has not yet been covered in the literature. In [209], the case
of blurred image detection is addressed using an Artificial
Intelligence based decoding method. Additionally, new posi-
tioning and detection methods and algorithms are proposed
in the literature for vehicular OCC [210]–[212]. In [213], a
traffic sign detection technique is proposed for a V2I OCC
communication using dual cameras. Finally, hybrid VLC/OCC
scenarios are also treated in literature where hybrid modulation
schemes and RoI-signalling techniques are discussed [214],
[215].
FSO-Based Vehicular Communications:
FSO communications is another possible solution for vehic-
ular communication. In [216], an FSO-based real-time recog-
nition and tracking system is proposed for vehicular networks.
Authors in [217] presented a laser alignment technique for
FSO-based vehicular communication, considering the effects
of vehicle mobility, tilting, and vibration. Most of FSO-based
vehicular communications are jointly using RF waves as well.
These solutions are discussed in more details in the following
section.
We witnessed the lack of IR-based vehicular communication
solutions in literature. Considering the characteristics of IR
waves, we believe it would be a convenient solution for
vehicular communications.
OWC+RF for Vehicular Communications:
Considering the advantages and limitations of RF and
VLC communications, it is convenient to hybridize these two
technologies in the same platform [218]. A joint VLC+RF
V2X system can be used where high-speed critical information
is transmitted using VL [219]. Driving supervision can also
be offered to drivers using a combined VLC and Bluetooth
solution. Pre-information about the road, like speed breakers
situated on the road to slowdown cars and sudden cracks, is
exchanged between cars through VLC. Then the instruction is
sent through Bluetooth to an Android app that performs a text-
to-speech task and alerts the driver [220]. Hybrid VLC+RF
solutions proved to be robust for platooning applications
in treating urban environment scenarios [221], [222] or in
improving security issues [223].
FSO+RF is another promising combination for vehicular
communication. In [224], an FSO-based vehicular communi-
cation system is proposed where vehicles interchange their
coordinates using RF waves to align their laser sources. A hy-
brid FSO+RF communication is also implemented to optimize
the throughput in multi-hop vehicular ad-hoc networks [225].
Eventually, we can state in literature various works that used
vehicular communications between garbage bins and garbage
collection tracks to monitor waste management [226]–[228].
Yet to the extent of our knowledge, all these solutions use
RF waves. Hence, we believe that leveraging OWC into smart
waste treatment by proposing joint RF/OWC solutions may
benefit smart cities considering the benefits introduced by
light-based communications.
3) Smart Shopping: In the past decade, we have witnessed
the integration of IoT into the commercial field. This latter
is constantly evolving by incorporating new options and fa-
cilities that make it easier to access. Most of the IoT-based
commercial solutions proposed in the literature use RF waves.
However, due to the lack of available RF bandwidth and
its related interference problems, optical waves appear to be
a good complement to RF for commercial solutions. This
section covers the most relevant optical solutions proposed
for shopping systems.
Optical communication proved to be convenient for smart
shopping. In [229], [230], Light Fidelity (LiFi)-based solutions
for item detection and smart payment are proposed. Navigation
and indoor positioning in supermarkets, as well as product
recommendation, are also possible using VLC [231], [232].
Furthermore, a joint VLC+RF solution for 5G, called the
internet of radio-light, has been developed for supermarkets
where the customer can find directions and access the internet
and cloud-based services [233]. In [234], a hybrid RF iden-
tification (RFID)/IR solution is proposed for the smart and
effective organization and extraction of items in a store. It
is important to mention here that most of the existing smart
shopping solutions in literature use RF wave [235]–[239] and
that the leveraging of optical waves for smart shopping has
been explored only very recently and to a limited extent.
Hence, we believe that researchers in the field should further
analyze the use of optical waves in smart shopping.
4) Smart Industry: Industry is a vital sector in every
country. Also known as Industry 4.0, the modern industry
requires reliable high-speed communication links. Although
the majority of the smart industry solutions are based on RF
communications, this technology suffers from low data rates

16
(up to 250 kbps [240]) and EMI that limit the performance
of production-related applications. Consequently, VLC has
recently made its way into industry, considering its large
bandwidth spectrum, low latency, relatively high security,
and absence of interference with RF waves. Furthermore, the
ubiquity of LEDs for illumination purposes makes the VLC
solutions cheap to implement. Nevertheless, OWC systems
face some challenges when applied in industrial environments.
The main challenge is light’s limited coverage, primarily when
implemented in large warehouses with high ceilings [241].
Also, the pollution existing in industrial environments can
degrade the performance of VLC systems [242]. The industrial
VLC-based solutions reported in the literature are limited
compared to those offered for the smart city. VLC-based
applications for smart industry can be fruitful in manufac-
turing [243]. For instance, robot manufacturing has gained
particular attention in recent years. This is reflected in the fast
growth of the robot market [244]. VLC-based solutions have
been proposed in the literature for the automotive industry.
The OWICELLS (Optical Wireless networks for flexible car
manufacturing CELLS) project considered implementing a
VLC system in car manufacturing cells. Although this solution
needs further improvement to be commercialized, it succeeded
in maintaining fast transmissions [245]. The work in [246]
investigated the possibility of implementing a VLC-based
solution for mobile assembly lines where LEDs can serve
for both illumination and communication with the central
controller. Furthermore, the feasibility of using VLC systems
in industrial production environments has been examined in
literature [247], [248]. In [249], [250], the performance of
VLC-based systems for multi-user MIMO architectures is
investigated.
C. COTS Products
The recent interest in the OWC-IoTT has led to an upsurge
of several COTS products as listed in Table III. For instance,
Signify, one of the leading companies in professional lighting,
has proposed the Trulifi series, which comes with four prod-
ucts, namely the Trulifi 6002.2, Trulifi 6013, Trulifi 6014.02,
and Trulifi 6800. The Trulifi 6002.2 AP has data rates of 220
Mbps for download and 160 Mbps for upload over a range
of up to 2.8 meters. The Trulifi 6013 Securelink guarantees
reliable high-speed optical communication with less than two
milliseconds latency over an 8 m range. Its data rate is 250
Mbps for both uplink and downlink. The 6014.02 AP/endpoint
system is characterized by a high data rate reaching 845
Mbps over a distance of 0.5 m and 12 m. The latency of
this communication system is less than three milliseconds.
The CitySwan BrightSites C7001 luminaire is another product
from Signify that ensures 15 Gbps communication over a
range of 300 m.
Oledcomm, a company that focuses on LiFi solutions, has
also proposed several products in this vein. One is the LiFiMax
set composed of an AP and a dongle. It affords LiFi-based
communication with data rates of 70 Mbps for download and
60 Mbps for upload for up to 16 users.
VLNComm is another company specialized in LiFi solu-
tions and has proposed products worth mentioning in this
section. The first is the Luminex LiFi-enabled LED panel.
Unlike the previously mentioned products that use the IR band,
this product proposes a hybrid VL/IR communication with a
70 Mbps rate for download and 60 Mbps for upload to up
to 15 users per AP. The second product is the Lumi Stick 2,
which connects devices to LiFi with data rates of 108 Mbps
for download and 53 Mbps for upload. It uses the waveband
420-680nm for downlink and 800-875nm for uplink.
The French company Lucibel also offers LiFi-based prod-
ucts for smart homes. The first product is the LifiCup, which
enables a high-speed bidirectional connection with a data rate
of up to 54 Mbps. It can support up to 16 simultaneous LiFi
USB keys while offering mobile users a handover service be-
tween different LiFi luminaires. The LiFi USB key is another
product of this company through which users can connect to
the LiFiCup with a data rate of up to 42 Mbps for uplink.
This LiFiCup / LiFi USB key communication system uses
VL for downlink and IR for uplink. Lucibel’s Barentino and
LuciPanel solutions ensure a bidirectional communication with
a data rate reaching 100 Mbps for 16 users simultaneously.
The aforementioned off-the-shelf products can be classified
as LiFi products that use VL or IR LEDs. Meanwhile, several
companies commercialized laser-based FSO products in the
market. These products are designed for outdoor use and
are characterized by long range. For instance, AIRLINX
proposes the CANOBEAM DT-100 series that include four
FSO products that guarantee a high data rate communication
reaching 1250 Mbps over a distance up to 1 Km. The company
fSONA offers the SONABEAM E2series that includes three
products ensuring up to 10 Gbps communication for a reach
extending to 1 Km and 1.25 Gbps for a distance of 3.6 Km.
The company EC System offers four products. The product
EL-1GL establishes a communication up to 4.4 Km with a
1.25 Gbps data rate, while the product EL-10gex guarantees
a high-speed communication exceeding 30 Gbps for a range
of 1.3 Km. Eventually, CableFree comes with three product
series: ‘Gigabit Range’, ‘Access Range’, and ‘FSO 622’. The
Gigabit Range series ensures communication over up to 2 Km
with a 1.5 Gbps data rate. The Access Range series offers a
link that can extend up to 4 Km with a 155 Mbps data rate.
The FSO 622 series guarantees a data rate of up to 622 Mbps
for up to 1.5 Km distance.
D. Summary and Insights
With the omnipresence of smartphones in the present era,
smart applications have taken over modern life on different
levels. From smart agriculture to smart cities, IoT-based ap-
plications have been introduced to facilitate people’s lives,
whether on farms, at home, or outdoors. IoT solutions are
implemented to monitor plants, livestock, homes, hospitals,
road traffic, supermarkets, and warehouses. Most of the solu-
tions proposed in this vein are based on RF communications.
However, this latter suffers from several limitations, such as
the limited available waveband and interference problems. It is
also forbidden in specific areas such as hospitals. This is due
to the potential effect on the human body and the performance
of the coexisting medical machines. Hence, optical

17
(a) Trulifi 6002 (b) Trulifi 6013 (c) Trulifi 6014 (d) Trulifi 6800 (e) LiFiMax (f) MyLiFi (g) LiFiXC (h) LumiNex (i) LumiStick
(j) LiFi Cup
(k) Lucibel
USB (l) CanoBeam (m) SonaBeam (n) EC System (o) CableFree
Fig. 7: Illustration of commercial OWC-IoTT products listed in Table III
TABLE III: Technical specifications of commercial OWC-IoTT products.
Company Product Ref. Size [mm] Weight [g] Range [m] Coverage [m2] Power [W] Wavelength [nm] Rate [Mbps] Modulation Latency [ms] Angle Tx/Rx Transmission mode Operation mode
Signify Trulifi
6002.2 [251] N/A N/A 1.2 - 2.8 1.3 - 7.1 35 940 (IR) 220 download
160 upload N/A N/A N/A Half duplex M2P
6013 [252] 130×75×35 380 8 N/A 4 N/A 250 download
250 upload OFDM <28/17 TDMA P2P/P2M
6014.02 [253] 146×106×37 430 0.5 - 12 0.09 - 0.5 <5940 845 Mbps OFDM <310/6 TDMA P2P/P2M
6800 [254] N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A P2M
BrightSites CitySwan [255] 190×725 18000 300 N/A 35 N/A 15000 N/A N/A N/A TDD/TDMA P2P/P2M/Mesh
Oledcomm LifiMax Access Point [256] 110 ×25 400 N/A 12 <5940 100 download
40 upload
N/A N/A N/A TDMA <16 users
Dongle [256] 63×17 100 2.5 N/A N/A N/A
MyLiFi [257] N/A N/A N/A N/A 13 N/A 23 N/A N/A N/A N/A N/A
PureLiFi LiFI-XC [258] N/A N/A N/A N/A N/A IR 42 N/A N/A N/A N/A <8stations
VLNComm Luminex [259] 7029.45×7029.45×93.345 N/A 2.13 37 35 Visible Light
and IR
70 download
60 upload HCM <0.4N/A N/A <15
Lumi Stick 2 [260] 59×35×10.8 N/A N/A N/A 1.7 420-680 Downlink
800-875 Uplink
108 Download
53 Upload N/A N/A 120 N/A N/A
Lucibel
LIFICUP [261] 200×104 1500 3 38.48 30 White 54 N/A N/A 76 N/A <16 users
LIFI USB Key [262] 29.4×10.2×85 42 N/A N/A 2.5 N/A 42 N/A N/A N/A N/A N/A
Barentino [263] 595×595×13 3000 3 95 28 White 100 N/A N/A 66 N/A <16 users
Lucipanel [264] 595×595×45 4500 3 95 30 White 100 N/A N/A 120 N/A <16 users
AIRLINX Canobeam
DT-100
DT-110
[265] 246 ×168×487 8000
20-500
N/A 20 785 (FSO)
25-156
N/A N/A N/A N/A N/A
DT-120 100-2000 25-156
DT-130 100-1000 1250
fSONA SONABEAM E+
1250-E+
[266] 250×330×460 8000
500-3600
N/A 40 1550
1250
N/A N/A N/A Full-Duplex N/A
2500-E+500-2900 2500
10G-E+100-1000 10000
EC System
EL-1GL [267] 480×300×285 9000 4400 N/A 40-67 1550 1250 N/A <0.125 N/A Full duplex N/A
EC-1GS [268] 480×300×285 9000 1200 N/A 40-50 1550 1250 N/A <0.125 N/A Full duplex N/A
EL-10G [269] 480×300×285 9000 1500 N/A 37-67 1550 10312,5 N/A 0.02-0.05 N/A Full duplex N/A
EL-10gex [270] 480×285×300 9400 1300 N/A N/A 1550 10312,5-30937,5 N/A <0.005 N/A Full duplex N/A
CableFree
Gigabit Range
G200
[271]
478×233×139 4200 200
N/A
40
780 1500 N/A N/A N/A N/A N/A
G500 531×391×211 9000 500 40
G700/G1000 531×391×211 9000 700/1000 45
G1500 531×391×211 9000 1500 45
G2000 531×391×211 9000 2000 45
Access Range
A1000-LH
[272] 522.5×371×211 9000
1000
N/A 25-35 980
100
N/A N/A N/A N/A N/A
A1000 1000 155
A2000 2000 155
A4000 4000 155
FSO 622
CF200
[273]
478×233×139 4200 200
N/A
40
780
622
N/A N/A N/A N/A N/A
CF200-LH 478×233×139 4200 200 40 100
CF500 478×233×139 4200 500 40 622
CF500-LH 478×233×139 4200 500 40 100
CF1000 522.5×371×211 9000 1000 60 622
CF1500 522.5×371×211 9000 1500 60 622

18
Fig. 8: Illustration of the opto-acoustic network architecture for IoWT [4].
communication is a good complement in this regard. It
comes with high data rates ranging between Mbps and Gbps. It
ensures high-speed and low-latency communication due to the
fast propagation of light. It guarantees certain confidentiality
indoors since light does not go through walls. It also has
a low implementation cost considering the omnipresence of
light sources in daily life. Lately, researchers have proposed
OWC-based IoT solutions in various fields. These solutions
are classified as VLC, IR, or FSO solutions. Moreover, sev-
eral companies have commercialized OWC-based off-the-shelf
products for various purposes, whether for indoor or outdoor
use. Despite the advantages offered by OWC solutions, this
wave still suffers from specific issues such as the short-range,
the alignment problems, and its strong dependence on weather
conditions in the case of outdoor use. For this reason, we
believe that optical waves can indeed complement RF waves,
but they are not developed enough to replace them.
IV. INT ER NE T OF U ND ERWATER THINGS (IOWT)
Oceans and seas form a continuous body of water covers 71
percent of Earth’s surface to provide humanity with abundant
benefits such as natural resources, food supply, climate regula-
tion, transportation, medicine, and recreation. Early efforts and
interests in IoT research, development, and commercialization
efforts have mostly focused on the aforementioned terrestrial
indoor and outdoor applications. Likewise, creating a network
of IoWT devices could mark the beginning of a new era for
scientific, industrial, and military underwater applications such
as offshore exploration, environmental monitoring, disaster
prevention, assisted navigation, and tactical surveillance.
Nonetheless, an underwater network built upon traditional
RF and acoustic underwater communication paradigms may
not be sufficient to realize an effective IoWT ecosystem due
to the following reasons [274]. Since RF signals are more
tolerant to water’s turbid and turbulent nature, they can support
a low transmission delay by reaching a desirable propagation
speed. Nonetheless, water conductivity mainly restricts their
operational bandwidth to 30–300 Hz and communication range
to 10 m. Therefore, underwater RF systems are typically
power-hungry, costly, and bulky with large antennas. For these
reasons, they cannot be used for deep-sea communications and
are limited to work in sea surface interface systems. Thanks
to its long transmission range of several kilometers, acoustic
communication is a proven and wide-spread technology used
for underwater systems. Nevertheless, acoustic systems suffer
from high latency and low data rates due to the low propa-
gation speed (1500 m/s) and limited bandwidth (10-30 KHz),
respectively [8]. Acoustic systems are also prone to Doppler
spread, ambient noise caused by hydrodynamics and vessel
traffic, and multi-path fading.

19
At the expense of a limited communication range (50-100
m), underwater optical wireless communications can support
high data rates in the order of Gbps and very low latency
thanks to the speed of light in the water (≈2.55 ×108
m/s). The superposition of absorption and scattering effects
constitutes the extinction coefficient that primarily charac-
terizes the propagation loss of the aqua’s light waves. The
extinction-level depends on wavelength, water depth, water,
and types (e.g., pure, clear, coastal, harbor) [14]. For instance,
blue and green lights exhibit better propagation characteristics
in clear and coastal waters, respectively. On the other hand,
the divergence angle (i.e., directivity) of the light source
beamwidth governs the fundamental trade-off between range
and beamwidth. For example, LEDs can reach many nearby
nodes thanks to its wide-beam, collimated beams of LDs can
communicate with far away nodes at desirable rates. UOWC
also suffers from channel impairments such as turbulence,
pointing errors, misalignment [275]. Albeit its advantages,
limited range, and highly directed nature of OWC are the
main limitations, especially when the sparsity of underwater
networks are considered. At this point, the hybridization of
optic and acoustic systems can reap the full benefit of these
systems as they complement one another’s disadvantages.
In this section, we first explain a hybrid optic and acoustic,
namely opto-acoustic, network architecture to explain how
integration of these technologies can enable an IoWT network
architecture. Then, we discuss technical challenges of OWC-
IoWT systems and networks and present recent advances
towards prototypes, testbeds, and commercial OWC-IoWT
products. Lastly, we conclude the section with a summary,
insights, open problems, and future research directions.
A. An Opto-Acoustic IoWT Network Architecture
Although IoTT devices can be integrated with existing
indoor/outdoor wired/wireless network infrastructure, there is
not a readily available underwater network infrastructure for
ubiquitous connectivity of IoWT devices. Therefore, a hybrid
IoWT network architecture is necessary, which can be de-
signed in either an ad hoc or infrastructural, or mixed structure
as demonstrated in Fig. 8 [4]. In the ad-hoc fashion, IoWT
nodes are distributed across the network are connected through
the participation of IoWT nodes along a routing path, which
is dynamically calculated centrally or distributively as per the
network conditions. On the other hand, infrastructure networks
deploy acoustic APs (AAPs) and optical base stations (OBSs)
to serve as a gateway for nodes located in their coverage
regions. In the mixed architecture, the available coverage
provided by the infrastructure can be extended through multi-
hop communications between ad hoc IoWT nodes in both
horizontal and vertical directions.
The backbone network of mixed architecture may consist of
wired or wireless links between OBSs, AAPs, surface stations,
and underwater data/cloud centers. OBSs can be designed as
multi-faceted spheres that can provide 360◦connectivity using
transceivers built on each face. Indeed, OBSs are already
implemented in [276], and a cellular UOWC network is
conceptualized in [277]. Sea-bed OBSs can communicate with
each other via fiber optical cables and/or horizontal collimated
light beams (i.e., H-Haul links) and/or in the seabed. Similarly,
vertical collimated light beams (i.e., V-Haul links) can be used
to reach the central/surface OBS via intermediate OBSs that
are hung on the tether of buoys along with AAPs down to the
moor at the seabed. The recent breakthroughs in LD based
UOWC systems listed in Table V show that both V-Haul and
H-Haul links can be realized by using long-range and high
data rate laser beams. If the tethered buoys are equipped with
solar-panels and RF modules, they can supply power and con-
nectivity to AAPs and intermediate OBSs through power+data
cables on the tether. Likewise, a tidal turbine could also power
the fixed infrastructural network elements on the seabed by
means of power cable lay-down along with fibers. Moreover,
solar-powered floating buoys can also be used as an alternative
mobile air-water interface. The interconnection between the
seabed and sea-surface systems enables the integration of
IoWT and IoTT ecosystems via mobile stations, unmanned
aerial vehicles (UAVs), and satellites.
The access network may be comprised of IoWT devices
which may have 1) actuators to interact with the environment;
2) sensors that measure multiple physical phenomena (e.g.,
temperature, pollution, pH levels, salinity, etc.), and 3) au-
tonomous underwater vehicles (AUVs) to carry out collabora-
tive mobile tasks. As an alternative to active transceivers, low-
cost IoWT devices with limited size and battery may have pas-
sive transceivers such as acoustic tags, optical retro-reflectors,
and passive integrated transponders. AUVs are generally pow-
ered by batteries that can be charged by onboard solar panels
and can operate at different depths depending on hardware
specifications. They are sophisticated platforms equipped with
several subsystems such as positioning-acquisitioning-and-
tracking (PAT) mechanisms and navigation systems, onboard
data processing, and various sensors/actuators.
Interestingly, an underwater data/cloud center can orches-
trate the mixed-structure hybrid opto-acoustic underwater net-
work illustrated in Fig. 8. Microsoft has recently launched
project Natick6where a cylindrical tube-shaped data center
is sunk into the sea. Although the purpose of this project is
to reduce cooling costs and benefit from offshore renewable
energy sources, this concept can also be used to provide
necessary computational power and data storage for the IoWT
ecosystem as well as its integrity with terrestrial telecommu-
nication infrastructure.
B. Technical Challenges of OWC-IoWT Networking
In order to understand OWC-IoWT networking challenges,
it is important to provide a background on fundamental
tradeoffs between key UOWC performance metrics. Based on
the Beer-Lambert channel model, the opposite behavior of data
rate and BER is illustrated with respect to increasing distance
in Fig. 9a, where the default values of BER and rate are
set to forward error correction (FEC) threshold (3.8×10−8)
and 1 Mbps, respectively. Fig. 9a also shows that data rate
and BER performs differently at different divergence angles
(i.e., beamwidths). For instance, 1 Mbps rate is achievable at
6https://natick.research.microsoft.com

20
20 40 60 80 100
Range [m]
104
106
108
1010
1012
Rate [bps]
10-8
10-6
10-4
10-2
100
BER
R ( min)
R ( max)
BER ( min)
BER ( max)
FEC Threshold
(a)
10-3 10-2 10-1
Divergence Angle [rad]
40
60
80
100
120
140
160
180
Range [m]
1 Kbps
1 Mbps
1 Gbps
(b)
0 50 100 150 200
x [m]
-40
-30
-20
-10
0
10
20
30
40
y [m]
1 Kbps
0
20
40
60
80
100
120
140
160
180
(c)
0 50 100 150 200
x [m]
-40
-30
-20
-10
0
10
20
30
40
y [m]
1 Mbps
0
10
20
30
40
50
60
70
80
90
(d)
0 50 100 150 200
x [m]
-40
-30
-20
-10
0
10
20
30
40
y [m]
1 Gbps
0
10
20
30
40
50
(e)
Fig. 9: Fundamental tradeoffs between key UOWC perfor-
mance metrics [278]: a) range vs. rate and BER, b) range vs.
divergence angle, c) coverage region at 1 Kbps, d) coverage
region at 1 Mbps, and e) coverage region at 1 Gbps.
TABLE IV: Literature on connectivity, reliability, routing, and
localization aspects of opto-acoustic IoWT networks.
Ref. Year Topic Network Description
[279] 2018 Connectivity Optic A graph theoretic connectivity analysis
[280] 2018 Connectivity
Localization
Optic Impacts of limited connectivity on localization accuracy
[281] 2020 Optic Performance analysis for connectivity and localization
[4] 2020 Connectivity Hybrid Degree of connectivity under various beam widths
[282] 2019 Reliability
Routing
Optic Distributed URLLC routing protocol
[283] 2020 Optic End-to-end performance analysis of relaying and
routingtechniques under location uncertainty
[284] 2012
Routing
Hybrid Multi-level Q-learning based routing protocol
[285] 2018 Optic Modeling and performance analysis of decode and
amplify relaying based relaying protocol
[286] 2019 Optic Sector-based distributed opportunistic routing protocol
[287] 2019 Optic Multi-agent reinforcement learning routing protocol
[278] 2020 Hybrid Opportunistic routing protocol tailored for maximum
rate, minimum delay and energy consumption.
[4] 2020 Hybrid Widest-path routing for maximum capacity
[288] 2018
Localization
Optic Robust 3D Localization via Low Rank Matrix Completion
[289] 2018 Hybrid Energy harvesting impacts on network localization
[290] 2018 Optic 3D outlier detection and optimal anchor placement
[291] 2020 Optic Analysis of 3D localization with uncertain anchor positions
[292] 2020 Optic Localization of energy harvesting empowered networks
[4] 2020 Hybrid Impacts of divergence angle on network localization
ranges 80 m and 90 m by setting the minimum and maximum
divergence angles to θmin = 0.25 radian and θmax = 100
milliradian, respectively. Therefore, Fig. 9b shows how com-
munication range decreases as the divergence angle and data
rate increase. One can deduce from the 1 Kbps curve in Fig. 9b
that UOWC does not deliver significantly better performance
than acoustic systems, which can already reach several Kbps
over several hundred meters. In Fig. 9c-9e, the coverage region
of a transmitter located at the origin is shown for data rates
of 1 Kbps, 1 Mbps, and 1 Gbps, respectively. The colorful
shape is obtained by a combination of sector shapes, which are
obtained by changing the divergence angle from 1 milliradian
to 0.1 rad, and color represents the radius of the coverage
region at a given beam width. It can be seen that the coverage
region expands as the data requirement is relaxed. It can be
concluded from Fig. 9 that UOWC range and coverage is a
subjective metric that closely depends on hardware parameters
as well as required QoS levels. In light of this background,
we next discuss the major technical challenges faced by OWC-
IoWT networking. We refer interested readers to Table IV for
a list of references covered in the following subsections.
1) Connectivity: The IoWT node density is expected to
be low due to the cost and deployment challenges. The
node sparsity directly impacts the degree of connectivity that
determines the interwoven relations among basic network per-
formance metrics such as routing, localization, and reliability.
No matter what kind of optimal routing algorithm employed,
there is no way to find a multi-hop communication path if
the network is partitioned [285], [286]. On the other hand,
network localization accuracy is proportional to the degree of
connectivity as well-connected network yields more pair-wise
range measurements, which naturally reduces the localization
error [279]–[281]. Since the highly directed nature of OWC
requires LoS links, the node location is the most critical
information for the P2P link performance between OWC-
IoWT nodes, which intuitively affect the overall performance
of the OWC-IoWT network [283].
Considering this challenge, a reinforcement learning-based
solution for a P2P UOWC system has been recently proposed
in [315] to solve PAT problems by defining a beam adaptation
method that includes both beamwidth and beam orientation
adaptation to improve the link quality while maintaining a
high success rate.
2) Routing: Since one of the main disadvantages of UOWC
is its short communication in comparison with the network
area, multi-hop communication is a must to boost network
connectivity by extending the communication range, improve
the end-to-end system performance by expanding the coverage
area, decrease latency, and increase energy efficiency [283].
The full benefits of multi-hop communications can only be
attained with an expeditious routing algorithm that accounts
for the underwater channel characteristics. Although there are
many routing protocols developed for underwater acoustic
networks [316], none of them is applicable for IoWT devices
due to the directivity of OWC.
As shown in Table IV, new protocols have recently been
developed to account for the aforementioned fundamental
tradeoffs of UOWC. In [4], authors employ the widest-path
algorithm to find a route with the maximum end-to-end
capacity and evaluate its performance at different divergence
angles. In [284] and [287], authors propose routing protocols
based on multi-level and multi-agent reinforcement learning,
respectively. In [285], modeling and performance analysis of
decode-and-forward and amplify-and-forward based multihop
communications. In [286], Celik et al. develop a sector-based
opportunistic routing by leveraging the broadcast nature of
OWC propagation. The opportunistic routing has shown been
to improve overall reliability and reduce the total number of
retransmission since another node can take over the forwarding
responsibility if the selected forwarder fails in reception.
This opportunistic routing scheme is further extended to
both distributed and centralized schemes in [278] where the
protocol can be tailored for maximum rate, minimum delay,
and minimum energy consumption objectives.
The directivity and short-communication range of UOWC
also causes performance degradation in routing performance.
Therefore, the authors of [284] and [278] mitigate such

21
TABLE V: Laboratory testbeds and prototypes for OWC-IoWT.
OWC
Ref. Study
Type Year Application IoT
MWL
Band
[nm] (C) Topology Tx
Type
Rx
Type
Data
Rate
Error
Rate
Distance
[m] Mod.
Comp.
Tech.
Higher
Layers
[293] 2016 Tap
Water Tank N/A B P2P LD PD 2 G
1G
2.8E-5
3.0E-3
12
20 OOK N/A N/A
[294] 2017 Tap
Water Tank N/A G P2P LD PD 3.5 G
2.7 G FEC 21
35 OOK N/A N/A
[295] 2017 Air-Water
Interface N/A G P2P LD PD 5.5 G 2.6E-3
2.4E-3
5 (A)
21 (W)
OFDM
32-QAM FSO N/A
[296] 2017 Tap
Water Tank N/A
R
G
B
P2P VCSEL PD 25 G
2.2E-3
2.0E-3
2.3E-3
5WDM
QAM N/A N/A
[297] 2018 Turbid
Water Tank N/A B P2P VCSEL PD 25 G 3.0E-9 5 OOK N/A N/A
[298] 2015 Tap/Turbid
Water Tank N/A B P2P LD PD 7.3 G 3.5E-3 15 DMT N/A N/A
[299] 2019 Tap
Water Tank N/A G P2P LD PD 0.5 G 2.5E-3 100 OOK N/A N/A
[300] 2019 Tap
Water Tank N/A B P2P LD PD 9 G 1.0E-9 82 PAM4 FSO
Fiber N/A
[301] 2019 Tap
Water Tank N/A B P2P LD PD 2.5 G 3.5E-3 60 OOK N/A N/A
[302]
Labaratory Experiments
2020 Tap
Water Tank N/A G P2P LD PD 3.3 G 3.8E-3 56 OFDM
32-QAM N/A N/A
[303], [304] 2006 ROV N/A B P2P LD PD 1 M N/A 100 OOK N/A N/A
[305] 2007 ROV
OBS N/A B P2P
Broadcast LED PD 10 M N/A 10 N/A N/A N/A
[306], [307] ROV 1.2 M 30 ASK
[308], [309]
2010
2013 Video Stream N/A B P2P LED PD 2.8 M N/A 50 DPIM N/A UDP
SPI
[310], [311] 2016 Modem N/A B P2P LED PD 10 M N/A 10 N/A Acoustic SDN
[312] 2017 Modem N/A B P2P LED SiPM 3 M N/A 17-60 OOK N/A N/A
[313] 2018 Modem N/A R/G/B P2P LD PD 12.5 M N/A 46 N/A N/A RS232C
TCP/UDP
[314]
Prototypes
2018 ROV N/A B P2P LED PD 10 M N/A 10 N/A N/A SDN
Legend ROV: Remotely Operated underwater Vehicle, QAM: Quadrature Amplitude Modulation, ASK: Amplitude Shift Keying,
SiPM: Silicon Photo Multiplier, SPI: Serial Peripheral Interface
shortcomings by leveraging the omni-directional long-range
propagation of acoustic systems for node discovery, network
control, and node coordination purposes.
3) Localization: The network localization is of utmost
importance since the data gathered by an IoWT node is useful
only if it refers to a geographical location. It is also necessary
for applications such as target/intruder detection, data tagging,
routing protocols. For UOWC, it is particularly a must as mis-
alignment, and pointing errors caused by location uncertainty
deteriorate the performance significantly [283]. Unfortunately,
the GPS cannot be used for underwater applications as its
weak signals cannot propagate through the water.
The recent advances in optic and opto-acoustic localization
techniques are listed in Table IV. Since the range measurement
based localization methods depends on received signal strength
information and not associated with data rate at all, the hybrid
localization approach was shown to perform much better
than purely acoustic or optic algorithms [4], [289]. Since
the energy availability directly impacts the node density and
degree connectivity of underwater networks, the localization
accuracy of the energy harvesting empowered IoWT nodes
are also considered in [289], [292]. Since anchor locations
are typically considered to be given and important to convert
local network position to the global coordinates, a precise and
stable anchor position is needed. Different from the above
works, there are also efforts on 3D localization methods
that investigate localization robustness [288], optimal anchor
placement to improve localization errors [290], and impact of
anchor location uncertainty on the localization performance
[291].
C. Testbeds, Prototypes, and COTS Products
In the last decade, there has been a growing interest in
developing proof of concept testbeds and prototypes to ad-
dress technical challenges of developing OWC-IoWT devices
and demonstrate their performance in water tanks, swimming
pools, rivers, and the sea. The interest in academy finally ended
up with several commercially available OWC-IoWT devices.
In the consequent subsections, we preset the recent advances
that evolved OWC-IoWT concept into a reality.
1) Laboratory Testbeds: As shown in Table V, the majority
of laboratory testbeds are developed with laser transmitters and
experiments are conducted in water tanks. Although it is not
possible to make a fair comparison between these works as
testbed are not identical, following conclusions can be drawn
from the reported throughput and BER values along with the
channel length: A narrow beam OWC-IoWT system can reach
several Gbps rate over several ten meters while keeping the
BER below the FEC threshold. This is reduced to several
hundreds Mbps if the distance is in the order of hundred
meters. Albeit their remarkable performance, the narrow-
beam OWC-IoWT systems require efficient PAT mechanism
for precise alignment between the transceivers, which limits
their use to fixed terminals and advanced mobile terminals
(e.g., remotely operated underwater vehicles (ROVs), AUVs,
etc.). That is, they are not suitable for relatively lost-cost
and low form-factor ad-hoc IoWT devices. Indeed, reported
performances in Table V supports the idea of using V-Haul

22
TABLE VI: Commercial OWC-IoWT products.
Company Product Ref. Size
[cm]
Weight
[g]
Depth
[m]
Range
[m]
Rate
[bps]
Tx/Rx
Type
Power
Tx. [W]
Wavelength
[nm] (Color)
Angle
Tx/Rx
Comm. & Netw.
Interface
Hydromea LUMA
100 [317]
10 ×5×3 250 6000
2 100 K
LED/PD
1-2
N/A (B) 60/60
RS 232
RS 485
Ethernet
250LP [318] 7 250-600 K 2-5
500ER [319] >50 500 K 2-5
X [320] 10 ×6 650 >50 10 M 2-5
Sonardyne BlueComm
100 [321] 24 ×12 5200
4000
15 1-5 M LED/PD 6 450 (B) 60/60 DL/UL,
TDMA,
UDP,
TCP/IP,
Ethernet
200 (Tx) [322] 20 ×14 3600 150 2.5-10 M LED 6
400-800
(B/W)
Omni D.
200 (Rx) 38 ×14 7100 PD N/A
200UV (Tx) [323] 20 ×14 3600 75 2.5-10 M LED 6 Omni D.
200UV (Rx) 38 ×14 7100 PD N/A
5000 [324] N/A N/A 7 500 M LD/PD N/A N/A Focused
Aquatec Aqua
Modem
Op2 [325] 28 ×74000 3500 1 80 K LED/PD 9-
36 N/A (B) N/A RS 232
RS 485Op2L [326] 1000 500 N/A
UON OMM [327] 21 ×14 N/A 4000 15 115 K LED/PD 3.3 N/A (B) Omni D. RS 232
Ambalux 1013C1 [328] 28 ×10 2500 61 40 10 M LED/PD N/A N/A (B) 25/25
±5
Ethernet/TCP
IP/UDP
Shimadzu MC100 [329] 25 ×13 2850 3500 >10 95 M LD/PD N/A 450-640 (B/G) Focused N/A
and H-Haul links between infrastructure based IoWT network
elements (e.g., OBS) to provide high-speed connectivity.
Noting that the testbeds listed in Table V is not exhaustive,
we would like to emphasize the following two works: In [295],
Chen et al. developed an FSO-UOWC interface system that
can reach a gross bit rate 5.5 Gbps over 5 m and 21 m air
and water channel distance, respectively. Since the bottleneck
of the entire system is the underwater link, the same end-
to-end system performance could be reached over a longer air
channel distance. Indeed, this work can be regarded as a proof
of air-water interface shown in Fig. 8. A similar interface is
developed in [300] where Li et al. develop a system that can
reach 9 Gbps gross bit rate over 50 m FSO link, 30 m graded-
index fiber, and 2 m UOWC links. Such a system is especially
useful to provide UOWC to ROVs/AUVs by extending fiber
links from a surface station.
2) Prototypes: One of the earliest example of UOWC
system were developed by Farr et al. in [303] where authors
implement a hemispherical omni-directional OWC transceiver
that can achieve 10 Mbps rate over 100 m by using six blue
LEDs. In addition to mounting the developed modem to a
ROV, authors conceptualized their use as OBSs moored to the
sea bed. In [304], the developed systems are further exploited
for untethered ROV that muling data from sea floor borehole
observatories equipped with developed hemispherical OWC
transceivers.
To the best of our knowledge, the cellular OWC concept
and its implementation is presented by Baiden and Bissiri
in [305], which is based on a project supported by The
Canadian Research Chair, The National Science Foundation
(NSF), and The National Aeronautics and Space Admin-
istration (NASA) in 2002. Throughout the project, authors
developed an icosahedrons shaped underwater optical OBS to
provide 360◦coverage and achieved 10 Mbps rates over 10
m distance after several trials between a floating laboratory
and the OBS placed at the lake bed. Considering both the
promising results achieved by this early proof of concept, we
believe more effective OBS systems can be developed thanks
to technological advances seen in photonics in the last two
decades.
In [306], Doniec et al. developed AquaOptical system that
is capable of reaching 1.2 Mbps up to 30 m using blue LEDs
and PDs. In [308], this system is upgraded to bidirectional
AquaOptical II that can achieve 2.28 Mbps up to 50 m using
discrete pulse interval modulation (DPIM). Both systems are
designed to use UDP over a serial peripheral interface (SPI).
Authors also demonstrated applications of both AquaOptical
and AquaOptical II in [307] and [309], respectively. AquaOp-
tical is used for the control of AMOUR VI ROV in [307]
where various system performance metrics (e.g., delay, packet
loss, etc.) were tested at various distances inside a swimming
pool. On the other hand, AquaOptical II is used for robust
real-time underwater digital video streaming in [309] where
authors tested frame success rate at different image quality,
resolution, and channel distances also in a swimming pool.
In [330], Mora et al. developed sensorbots, an omni-
directional ad-hoc UOWC system consisting of several LEDs
encapsulated in a transparent sphere. Noting that sensorbots
are able to operate at 2 km water depths, they are very inter-
esting examples of floating OWC-IoWT devices illustrated in
Fig. 8. Since there is no mention to rates and range, [330] is
not included in Table V.
In [310], Bartolini et al. developed an UOWC modem,
namely OptoComm, that can achieve 10 Mbps over 10 m dis-
tance using LEDs and PDs. In [311], authors then hybridized
OptoComm with an acoustic modem and integrated under the
SUNSET framework, a whole software defined protocol stack
with capability of supporting different protocols at different
layers. Although OptoComm is similar to other prototypes
listed in Table V, its hybridization and integration within
a software defined networking (SDN) framework is quite
inspiring and revolutionary. The developed whole protocol
stack system was able to transfer up to 1.5 GBytes of data in
a short duration of time. The SDN based hybrid opto-acoustic
system developed in [311] is further improved and integrated
to a ROV system in [314] where numerical results showed 10
Mbps is achievable over 10 m distance in sea water trials.
In [312], Pierre et al. developed a prototype that can achieve
3 Mbps over 17 m and 60 m distance under Jerlov 1 and
Jerlov 5 water classification, respectively. Different from other
prototypes in Table V, authors developed an omnidiretional
receiver by using silicon photo multipliers (SiPM). Notice
in Table V that all prototypes are built on LED transmitter,
excluding [313] where RBG LD is shown to achieve 12.5

23
(a) (b) (c) (d)
(e) (f) (g) (h)
Fig. 10: Commercial OWC-IoWT products of Hydromea [a)
LUMA 100, b) LUMA 250, c) LUMA 500ER, and d) LUMA-
X], Sonardyne [e) Bluecomm 100, f) Bluecomm 200, g)
Bluecomm 200 UV]; and Auquatech [h) Op2/Op2L].
Mbps over 46 m channel length.
3) COTS Products: The growing scientific interest in
OWC-IoWT systems has continued with many successful
commercial products as listed in Table VI, some of which
are also shown in Fig. 10. Hydromenia offers LUMA product
series, which come with four different types: LUMA 100
[317], LUMA 250 [318], LUMA 500ER [319], and LUMA X
[320]. LUMA products support RS232, RS485, and Ethernet
interface and communicate over a LED/PD transmitter/receiver
in waters as deep as 6 km. LUMA 500 ER is an extended
range (>50 m) version of LUMA 100 (2 m) and LUMA
200 (7 m). All these three products have a very small form
factor compared to LUMA X, which can provide 10 Mbps
speed over 50 m. One can observe that the packaging size
and transmission power requirements increases as data rate
and range increases.
Sonardyne is another company that offers a wide va-
riety of products: Bluecomm 100 [321], Bluecomm 200
[322], Bluecomm 200UV [323], and Bluecomm 5000 [324].
Bluecomm 100 has LED transmitters and PD receivers in-
stalled together to provide 15 Mbps bi-directional communica-
tions over 5 meters. On the other hand, Bluecomm 200 UV and
Bluecomm 200 can provide up to 10 Mbps over 75 m and 150
m channel length, respectively. Of course, this performance
enhancement is achieved at the expense of separate transmitter
and receiver units and extra power consumption. Even if
Sonardyne mentions another product that can achieve 500
Mbps using LD transmitter, no further information is provided
in their website. Bluecomm products support a wide range of
communication protocols and interfaces (time division mul-
tiple access (TDMA), UDP, TCP/IP, Ethernet) and designed
especially for OWC-IoWT vehicles (e.g., ROV/AUC).
Aquatec also developed two OWC-IoWT modes: Op2 [325]
and its lighter version Op2L [326]. Although they have the
same performance, the operational depth of Op2L is limited
reduced from 4 km to 1 km. As can be seen from Table VI
that these products weight several kilograms in the air, while
their weight in water is much lower. Their size and weight is
mostly because of the waterproof materials and fabrication.
D. Summary and Insights
Even though IoWT could mark the beginning of a new
era for scientific, industrial, and military underwater appli-
cations, realizing IoWT is an engineering challenge due to
the harsh aquatic environment and its peculiar impacts on
wireless channels regardless of the underlying communication
technology. Therefore, there is no best-fit wireless method to
facilitate IoWT networks as each has its virtues and draw-
backs. While an RF system can support a low transmission
delay by reaching a desirable propagation speed, thanks to
their tolerance to water’s turbid and turbulent nature, their
operational bandwidth to 30–300 Hz and communication range
to 10 m. Therefore, RF systems are mostly considered to
serve as an air-water interface at the sea surface stations.
On the other hand, acoustic communication is a proven and
widespread technology used for underwater systems thanks to
its long transmission range of several kilometers. Nonetheless,
acoustic systems suffer from low data rates and high delay due
to limited bandwidth and low propagation speed, respectively.
On the contrary, UOWC systems can transmit at rates ranges
between Mbps and Gbps over several tens and hundreds of
meters, respectively. This is because the beamwidth of the light
source mainly governs the communication range and rates.
Moreover, UOWC does not suffer from transmission delays
since the speed of light in the aqua is very close to lightspeed
in the air. Therefore, UOWC can enable a high-speed and low-
latency infrastructure for IoWT networks. Although OWC-
IoWT networks are possible for small-scale cellular appli-
cations through OBSs with omnidirectional transceivers [c.f.
Fig. 8], their extension to large-scale IoWT networks requires
effective routing mechanisms, which is especially challenging
when the directivity of UOWC systems is taken into account.
At this point, hybridization of the optical and acoustic sys-
tems can mitigate the directivity/range and bandwidth/delay
limitations of optic and acoustic systems, respectively.
The academic interest in the OWC-IoWT concept has
finally ended up with several commercially available OWC-
IoWT devices. However, available COTS products are mainly
suitable for P2P communication purposes for fixed and mobile
platforms (e.g., AUVs). To the best of the authors’ knowledge,
these products are not exploited to build a small or large scale
OWC-IoWT network and integrated with terrestrial networks
yet. The indoor and outdoor OWC-IoTT networks are sup-
ported by various standardization efforts [c.f., Table ??], which
embrace many OWC technologies (VLC, IR, UV, OCC, etc.)
by defining different device classes (infrastructure, mobile,
vehicle) with five different PHY types for different QoS
requirements. Unfortunately, none of them recognizes aqua as
a transmission medium as well as its specific PHY and MAC
layer distinctions. Unlike the OWC-IoTT devices which can be
integrated to terrestrial wired/wireless network infrastructure,
there is no readily available underwater network for OWC-
IoWT devices. Therefore, OWC-IoWT networks also requires
a different approach at higher layers due to the aforementioned
challenges in connectivity, reliability, localization, and routing.
Therefore, we believe that the extension of these standards to
include UOWC systems will pave the way for OWC-IoWT

24
networks.
V. IN TE RN ET O F BIOMEDICAL THINGS (IOBT)
The IoBT, also referred to as Internet of Bodies, broadly
pertains to wearable, implantable, ingestible, and injectable
IoT devices which can be used for a broad scope of applica-
tions such as medicine, wellness, sport/fitness, entertainment,
to name but a few [1]. Having its root in wireless body
area networks (WBANs) [331], the IoBT is an imminent
extension to the vast IoT domain and has been recognized
as a critical technology for revolutionizing the public health
and safety sector, which has been proven to be inadequate
during the humanitarian and economic crisis caused by the
novel coronavirus pandemic (a.k.a, COVID-19) [332]. IoBT
differs from their indoor/outdoor IoTT counterparts because
of the distinctive QoS/Quality of Experience (QoE) demands
of medical applications as well as peculiar and dynamic
channel impairments in-on-and-around the human body. In
particular, IoBT designed for patient monitoring applications
has stringent reliability, latency, and security requirements as it
handles users’ critical and sensitive physiological data. How-
ever, miniaturization efforts to improve QoE of implantable,
ingestible, and injectable IoBT devices leave a limited room
for the battery size. Therefore, limited energy availability
stands as the major obstacle in the way of fulfilling these
multiple and conflicting QoS demands at the same time.
Accordingly, this section first provides a comparative anal-
ysis to provide valuable insights into how OWC can com-
plement traditional RF-IoBT. Then, we present subtle issues
related to in/on/off-body OWC-IoBT and survey the literature.
Since operational lifetime is one of the primary design issues,
SLIPT is also covered. Lastly, we conclude the section with
a summary, insights, open problems, and future research
directions.
A. A Comparative Analysis of RF-IoBT and OWC-IoBT
The RF channel attenuation dynamics in-on-and-around the
human body are quite distinct from regular RF channels
because of the lossy, heterogeneous, and dielectric nature
of the human body. Different tissue types exhibit various
propagation phenomena (e.g., reflection, refraction, diffraction,
absorption, scattering) at different frequencies with varying
levels. In-body channel gains are primarily determined by
the distance between the transceivers as well as dielectric
properties of tissues and organs along the propagation path.
On the other hand, placement of on/off-body RF-IoBT di-
rectly determines the link distance and type (LoS or NLoS)
as a result of irregular body shapes and curvatures. These
factors have a significant impact on the first-order channel
statistics (FoCS),i.e., path loss and shadowing. Unlike the in-
body RF-IoBT devices, on/off-body RF-IoBT devices are also
susceptible to the dynamic changes in the body postures/gaits
and surrounding environment. Therefore, both intentional and
involuntary mobility of the human body yield time-variant
changes in path loss and shadowing effects, which determines
the second-order channel statistics (SoCS) such as delay
spread, power delay profile, level crossing rate, average fade
duration, autocorrelation) channel statistics. Since FoCS/SoCS
follow different distributions at different frequency bands and
channel mediums (air, skin, deep tissue), the IEEE 802.15.6
standard specified a wide variety of narrowband (NB) and
ultra-wideband (UWB) channels for the use of WBANs [333].
Next, we provide a comparative analysis between NB/UWB
RF-IoBT and OWC-IoBT from different aspects:
•The radio front end is one of the most complex and
power-hungry sub-systems of RF-IoBT devices. Hence, it
limits the operational lifetime per charging cycle and ne-
cessitates a larger battery capacity. This naturally requires
a larger packaging and frequent replacement, which is not
a viable option, especially for implantable, ingestible, and
injectable IoBT. Alternatively, OWC-IoBT transceivers
can have package size in millimeter-scale thanks to
available pico LEDs with less than 1 mm3and PD
arrays of several mm2area. Moreover, recent advances
in LED fabrication has made it possible to have wall-
plug efficiency more than unity. For example, authors of
[334] reported 69 pW of light using 30 pW of supplied
electrical power. By also using simple light modulation
schemes, miniature and energy-efficient OWC-IoBT can
provide very high bit/joule levels for long-life yet high-
performance IoBT devices desired by many applications.
•RF-IoBT modules are susceptible to interference and co-
existence issues with the nearby IoT devices operating
on the same band, which exacerbates in crowded license-
free RF bands. For example, IoT devices are typically
designed to operate on ISM bands for two reasons: 1)
there is no associated licensing fee, and 2) the ISM
compatible RF front end modules are cheap and readily
available. Considering the ever-increasing number of IoT
devices, interference and co-existence problems are non-
trivial for IoBT applications that require URLLC. Noting
that light spectrum is also license-free, interference and
co-existence issues for OWC-IoBT is minimal thanks to
the vast spectrum availability, high directivity, and low
penetration attributes of lightwaves. Even though on/off-
body OWC-IoBT transceivers operating at VL spectrum
are susceptible to ambient light sources, NIR transceivers
are preferable by in/on/off-body OWC-IoBT thanks to
their innate immunity to ambient light as well as favorable
channel gains inside the body.
•As a result of highly radiative and omnidirectional RF
propagation, RF-IoBT inadvertently permits eavesdrop-
pers to intercept or even alter the original data. Thus,
it is crucial to guard confidentiality and privacy of sen-
sitive physiological information against eavesdropping,
overheard, and cyber-attacks. However, adding extra se-
curity measures increases both hardware complexity and
monetary cost, negatively impacting the miniature, low-
cost, and ultra-low-power design goals. Alternatively,
high directivity and low penetration features of lightwaves
also provide inherent PHY layer security.
•Exposing the body to excessive electromagnetic radiation
causes tissue burnt due to the increasing heat, raises
the likelihood of developing cancer and body rejection

25
Fig. 11: Illustration of LoS, NLoS, and RR link configurations for in/on/off-body OWC-IoBT.
of the implanted/injected devices. Therefore, RF-IoBT
devices are subject to stringent specific absorption rate
constraints, which stands as a main delimiter of the
overall communication performance. Alternatively, the
human safety regulations are relatively more lenient for
the light emission since a very limited electrical energy
transferred to heat thanks to the aforementioned high
wall-plug efficiency.
The IEEE 802.15.6 has also defined body channel communi-
cation (BCC), a.k.a. intrabody communication, as a third PHY
layer option, where transmission is confined to the human
body by coupling electrostatic or magnetostatic signals to the
skin through electrodes. In addition to being more energy-
efficient than RF-IoBT, the BCC also has relatively better PHY
layer security due to less signal leakage. However, the BCC
can merely be used for on-body IoBT devices and may not
provide very high throughput as it is limited to 10 kHz-100
MHz band. Albeit its inherent virtues described above, OWC-
IoBT should not be considered as a competitor or replacement
technology of the RF-IoBT. For example, OWC-IoBT can be
quite attractive solution for on/off-body applications. However,
its functionality for the in-body applications are limited to
transdermal telemetry as the penetration depth of lightwaves
are very limited for deep tissue communications. In what fol-
lows, we discuss where and how OWC-IoBT can complement
RF-IoBT devices in detail.
B. On-Body and Off-Body OWC-IoBT
As shown in Fig. 11, on-body OWC-IoBT devices can inter-
communicate in three ways: 1) on-body LoS links, 2) on-body
NLoS links through a nearby reflecting surface, and 3) travers-
ing an AP by means of off-body LoS/NLoS links. However,
due to the aforementioned dynamic channel conditions on and
around the human body, regular indoor OWC channel models
used by indoor OWC-IoTT devices are not directly applicable
to these three cases. One can observe from Fig. 11 that on-
body links can be realized by a time-variant combination of
the first and second case since having LoS links may always
not possible as a result of node orientation and deployment on
the body. A comprehensive study on channel characterization
and modeling for on/off-body OWC channels has recently
investigated FoCS and SoCS by considering both body-part
movement (local mobility) and whole-body movement (global
mobility) [355]. Although it has been shown that node place-
ment and orientation along with the body geometry have a
significant impact on channel statistics, the overall channel
gain was observed to be frequency non-selective, and ISI was
negligible. Unlike 0.2-4 dB attenuation changes caused by the
local mobility, the global mobility was the primary determinant
of the high attenuation and random variations. Moreover,
Gamma distributions were found to provide the best Akaike-
Information criteria fit models for the channel attenuation.
On the other hand, time-variations were shown to change
with node locations on the body and overall smaller than its
RF counterparts. In what follows, we present major research
efforts on on/off-body OWC-IoBT, which are categorized
based on research type (e.g., implementation, simulation) and
tabulated in Table VII.
In [335], Rachim et al. created an experimental LED/OCC
setup for transmitting electroencephalogram (EEG) data. This
study used a single white LED to transmit over LoS to
a smartphone located on a tripod stand within the same
room. By consuming 3 W power, they achieved an error-free
transmission with an upload speed of 2.4 Kbps at a distance

26
TABLE VII: The major OWC-IoBT studies based on node locations.
IoBT
Type
Study
Type Ref. Year Application IoT
MWL Band OWC Comp.
Tech.
Higher
Layers
Topology Tx
Type
Rx
Type
Data
Rate Distance Mod.
On-Body & Off-Body
Implement.
[335] 2017 EEG N/A VL Broadcast LED OC 2.4 K 4.5 m OOK N/A N/A
[336] 2017 ECG Custom VL Broadcast LED PD 40 K 8 m OOK RF N/A
[337] 2019 e-Health N/A NIR Broadcast LED PD 6.4 M 1.5 m OOK N/A N/A
[338] 2019 e-Health N/A VL Broadcast LED OC 1 K 1 m N/A N/A N/A
Simulation
[339] 2015 e-Health N/A NIR Star LED PD 118 K 5-7 m OOK N/A OCDMA
[340] 2015 e-Health N/A NIR Star LED PD <1 M 5-7 m OOK N/A N/A
[341] 2017 e-Health N/A VL Broadcast LED PD N/A N/A OOK N/A N/A
[342] 2019 ECG N/A VL Broadcast LED OC N/A 4 m N/A BLE N/A
In-Body IoBT (Transdermal OWC)
Implementation
[343] 1992 VAD N/A NIR P2P LED PD 9.6 K 15 mm FSK N/A N/A
[344] 2001 SLIPT N/A IR P2P L(E)D PD 1 M 10 mm Phase N/A N/A
[345] 2004 NPT N/A NIR P2P LED PD 40 M 4 mm AM RF N/A
[346] 2004 e-Health N/A NIR P2P LED PD 1 M 24 mm IrDA N/A N/A
[347] 2005 VAD N/A NIR P2P LED PD 9.6 K 45 mm ASK N/A N/A
[348] 2008 NPT N/A NIR P2P LD PD 16 M 2-8 mm N/A N/A N/A
[349] 2012 AMI N/A NIR, VL P2P, RR L(E)D PD N/A 1 mm OOK N/A N/A
[350] 2012 NPT N/A NIR P2P VCSEL PD 50 M 2-6 mm OOK N/A N/A
[350] 2014 NPT N/A NIR P2P VCSEL PD 75 M 2-6 mm OOK N/A N/A
[351] 2014 NPT N/A NIR P2P VCSEL PD 100 M 2-6 mm OOK N/A N/A
[352] 2015 BCI N/A NIR
VL
P2P-UL
P2P-DL VCSEL PD 100 M
1 M 2 mm OOK N/A WDM
[353] 2017 BCI N/A NIR P2P LED PD N/A 0.2 mm PWM N/A N/A
[354] 2020 ECG N/A IR P2P LED PD 4 K 4-16 mm UPIM N/A UART
Legend BCI: Brain Computer Interface, NPT: neuroprosthetic telemetry, VAD:ventricular assistance device, L(E)D: LED & LD, K: Kbps, M: Mbps
of 4 meters. They claimed that this type of data transfer may
replace common RF protocols used by wearable devices as
a physiologically safer alternative. Even though the authors
discussed no application protocol, the transmitted EEG data
could be wrapped in an IoT application protocol to enable
aggregation and automated healthcare monitoring to further
improve its utility in IoT.
In another implementation by An et al., an LED/PD link was
used to transmit data from multiple ECGs to a custom made
dashboard for cardiac health monitoring of patients [336]. By
using lenses with the LEDs, the authors were able to send data
at 40 Kbps at a distance of 8 m. This implementation explored
time hopping as a way to send multiple signals to the same
PD receiver. The authors also considered using RF technology
to supplement the link when the LoS link is broken.
Dhatchayeny et al. expanded their previous work in [341]
and offered a new use case in [337] for biomedical sensors to
transmit via IR-LED to reduce crowding of the RF spectrum
within hospitals and allow high data rate transmission in RF
sensitive environments. They implemented an LED/PD link to
transmit patient’s biomedical data from multiple health sensors
to a single overhead receiver, which allows multiple patients
to be monitored in the same room by using a transmission
scheduling scheme. An IR-LED choice means that there is no
VL to disturb patients or health-care providers, but retains high
data rate and secure LoS communications while not causing
RF interference. The real-time information can be monitored
by a server and send alerts to providers when coupled with
an IoT application protocol. The experimental setup enabled
transmission at 1.5 m at 6.4 Mbps, but no IoT Network layer
application protocol was tested in the research.
The same authors also propose an experimental LED/OCC
link in [338] that can be used to transmit vital sign data.
The main consideration was that the link would have a lower
BER to ensure that critical health data remains accurate over
the link. The setup involved a 4×4panel of RGB LEDs
to transmit 48 bits per frame and a 30 fps rolling shutter
camera. The experimental setup demonstrated a low BER
value transmission of 1.2×10−4with a rate of 960 bps at a
distance of 1 m. The transmissions were directly translated into
vital sign data, but an application protocol could be utilized
over such a link to enable data aggregation.
In [339], Chevalier et al. investigated the BER performance
of a star OWC-IoBT network topology. Theoretical analyses
are validated by a simulation set up where a patient is
moving in a hospital room. Since they consider multiple
nodes randomly located on the patient’s body, they exploit
optical code division multiple access (OCDMA) to avoid MAI
among the nodes. In [340], the same authors provide outage
performance analysis for NLoS communications based on a
similar simulation setup. They developed a fast, simple, and
adaptive method to consider mobility and the presence of
obstacles within an indoor environment.
In [341], Dhatchayeny et al. simulated an LED/PD link that
sent vital sign measurements to a gateway. The simulation did
not mention BER or distances but instead focused on SNR
versus BER. The team found that they were able to transmit
four different signals to the same receiver with a minimal
BER when the SNR value is around 12 dB, which shows that
the MIMO healthcare data aggregation is reliable under the
considered conditions.
In [342], Hasan et al. simulated a hybrid OWC/RF link
system to improve the reliability of the signal from healthcare
devices while lowering the amount of RF transmission. The
OWC link simulated is an LED/OCC link, and the main
component studied was the reliability of the link. When the
OCC link becomes unreliable, the RF channel was utilized
instead. The authors found that increasing the number of
cameras in the room decreased the need to switch to the RF
channel and that the OCC link was viable up to 4 meters.

27
500 600 700 800 900 1000
Wavelength [nm]
10-1
100
Absorption Coefficient [dB/mm]
4
7
2
1
5
3
6
Favorable Channel
Gain Window
VLC
Spectrum Near-IR
Fig. 12: Absorption levels of human skin tissues at VLC
and NIR wavelengths (reproduced after [356]): 1. stratum
corneum; 2. living epidermis; 3. papillary dermis; 4. upper
blood net dermis; 5. reticular dermis; 6. deep blood net dermis;
7. subcutaneous fat.
C. Transdermal OWC for In-Body IoBT
The injected and implanted in-body IoBT devices can be at
depths from a few millimeters to a few centimeters. In com-
parison with its on/off-body counterparts, in-body IoBT has
more stringent contradictory design requirements such as small
form-factor for users’ comfort and long battery life, which
requires ultra-low-power consumption at µW levels. As shown
in Fig. 11, the in-body OWC-IoBT devices can communicate
with on-body devices through P2P or RR transdermal (a.k.a.,
transcutaneous) OWC links. Unfortunately, among many other
tissue types, the skin has the most complex structure and the
highest absorbing losses due to its layered and relatively low-
water content. As shown in Fig. 11, the skin tissue consists
of four main layers: epidermis, dermis, hypodermis, and
transcutaneous layer. Fortunately, lightwaves within a specific
wavelength range can penetrate the skin with significantly low
absorption losses. The absorption losses [dB/mm] of various
tissue types at different wavelengths are shown in Fig. 12
where a favorable channel gain window can be observed
through the end (600-750 nm) and at the beginning (750-900
nm) of VL and NIR spectrum, respectively. Since commercial
LEDs are readily available at these wavelengths, there are
considerable theoretical and experimental research efforts on
both VL and NIR based transdermal OWC-IoBT. Although in-
body OWC links experience a much higher path loss compared
to over the air on/off-body OWC links, they are more stable
and reliable due to their isolation from body mobility and
environmental changes. In what follows, we present major
research efforts on transdermal OWC for in-body IoBT, which
are also tabulated in Table VII.
The earliest example of an LED/PD OWC link in IoT is the
work presented by Miller et al. [357]. In this work, IR-LEDs
are utilized to transmit data to and from a ventricular assistance
device (VAD) through an implanted PD. The application is
capable of maintaining an error-free link of 9600 bps at
150 mm. This paper’s main focus is to have the LED/PD
transceiver implanted in the patient to allow a wireless link
with the VAD. Using an LED/PD link Abita and Schneider
created a link that sent data through porcine skin samples at
1 Mbps [346]. They used an IR-LED and PD transceiver to
send and receive data with an Active Medical Implant (AMI)
at a distance of 24 mm. The AMI can be used in many
different situations and can allow care providers to receive
patient health information after the AMI is implanted quickly.
The authors did not discuss higher-level applications, such
as aggregating patient data over time. However, the AMI
devices used were capable of storing up to 512 Kbps so
that longer-term data could be given to the care provider or
wearer regularly. Another example of transcutaneous LED/PD
communication was found in [347], where Okamoto et al.
tested both IR and VL LEDs. They found that both IR and
VL were able to transmit unhindered at 9600 bps, but the IR-
LED transmitted without error at a distance of 45 mm while
the VL-LED was capable of transmitting error-free up to 20
mm.
In [345], Guillory et al. developed a hybrid RF/IR neu-
roprosthetic telemetry (NPT) system that uses constant-
frequency RF inductive links for energy and amplitude modu-
lated transcutaneous IR signals for data transfer. Numerical re-
sults showed that with commercially available IR components,
data rates of up to 40 Mbps can be transmitted through 5 mm
skin with an internal device power dissipation under 100 mW
and a BER of 10−14. In [348], Parmentier et al. developed
an IR-LD-based NPT system and evaluated its performance
in various operating conditions. The system can transmit at
data rates up to 16 Mbps through a skin thickness of 2-8 mm
while achieving a BER of 10−9with a consumption of 10 mW
or less. In [349], Gil et al. explored the feasibility of P2P
and RR transdermal OWC links through both mathematical
models and experimental validations. The P2P and RR link
measurements showed that an 800-950 nm wavelength window
is desirable for transdermal OWC. Although authors did not
specify achievable data rates, OOK modulation achieve a 10−5
BER over P2P and RR link by consuming 0.3 µW and 4 mW
transmission power, respectively. Since authors considered a 1
mm skin sample, the presented results could be optimistic for
the AMI placed in deeper tissues.
In [350], Liu et al. develop an NPT system by using vertical-
cavity surface-emitting lasers (VCSELs) in both transmitter
and implanted receiver modules. For a power consumption less
than 4.1 mW, the developed system is capable of achieving a
50 Mbps data rate through a 4 mm tissue with a BER less than
10−5and a tolerance of 2 mm misalignment. In [358], authors
improved the system throughput up to 75 Mbps by consuming
2.8 mW, which is almost half of the reported value in [350].
In [351], by conducting an in-vivo test on a sheepskin, authors
further improved the data rates up to 100 Mbps with a BER
of 2×10−7while limiting the power consumption to 2.1 mW.
In [352], Liu et al. also developed a bi-directional brain-
computer interface (BCI) using transdermal OWC links by
utilizing a VL-VCSEL and NIR-VCSEL in downlink and
uplink directions, respectively. In-vitro experiments on a 2
mm porcine skin showed that the developed OWC-BCI system
could achieve 1 and 100 Mbps rates in downlink and uplink
directions by consuming 290 µW and 3.2 mW, respectively.

28
In [353], Takehara et al. developed an injectable image
sensor of size 400 ×1200 µm2, which can modulate a small
NIR-LED with PWM. The modulated signal was transmitted
through a mouse skull bone of 200 µm thickness, which suc-
cessfully received the 2700 pixel/frame image. Most recently,
Sohn et al. developed an ultra-low-power AMI with a small
form factor of 10×10×1 mm3in [354]. The authors developed
an unsynchronized pulse-interval-modulation (UPIM) along
with a new protocol to account for the sparse, low-rate, but
delay-sensitive nature of transdermal OWC.
In the last couple of years, there is also a growing interest
in theoretical transdermal OWC studies such as performance
analysis and signal quality assessment in the presence of
misalignment [359], [360], [360]; modeling and analysis of
optical cochlear implants based on key performance indicators
such as the probability of hearing and neural damage [361],
[362]; and developing diversity techniques to improve outage
performance in the presence of pointing errors for P2P links
[363] and RR links [364], [365]. Although understanding the
fundamental issues through theoretical studies is important, we
believe their true impact can be unleashed only if proposed
models are validated by experimental setups.
D. SLIPT towards Energy Self-Sustainable OWC-IoBT
In addition to the ultra-low-power design goal, in-body
IoBT also requires energy self-sustainability through energy
harvesting techniques. The lightwave power transfer (LPT) has
already been considered as an effective solution for wireless
charging of body implants [366]–[370]. A generic LPT system
is shown in Fig. 11 where an external light source emits a
DC lightwave, which is received by a PD and fed into an
energy harvester circuit. The harvested energy is then used
for transmitting information to the external device. Therefore,
the LPT is limited to unidirectional (i.e., uplink) transdermal
OWC. The earliest example of LPT was presented in [366],
where a 10 ×10 mm PD was charged by an IR-LD to
empower a pacemaker that consumes about 2 mW. In [367],
Moon et al. developed 1-10 mm2silicon photovoltaic (PV)
cells and achieved a power conversion efficiency of more than
17% for 660-nW/mm2illumination at 850 nm. They further
extended this work in [368], where PV cells were able to
harvest energy from both VL and IR resources in the range
of 650-950 nm wavelengths. Although these prototypes show
the feasibility of energy harvesting of implanted devices from
external light sources, they do not consider the information
and power transfer together.
For applications that require real-time and interactive com-
munications with the in-body IoBT devices, a more practical
approach is realizing bidirectional transdermal OWC by means
of SLIPT technology [371]. In the SLIPT [c.f. Fig. 11],
the transmitted lightwave has both AC and DC components.
At the receiver side, AC and DC components are split in
parallel by using an inductor and a capacitor at the energy
harvester and decoder branches, respectively [372]. Unlike its
RF counterpart (i.e., simultaneous wireless information and
power transfer), the SLIPT does not require switching between
modes since the DC bias is always necessary for IM/DD.
However, the literature on transdermal SLIPT is limited to
[344], where Goto et al. extended their previous IR-LPT
systems in [369], [370] to an IR-SLIPT system where two
implanted PDs receive IR-LD irradiation. The carrier wave
generated by the first PD is phase modulated and fed into
the transmitter implanted NIR-LED, which is powered by the
second PD. The size and the weight of the implanted OWC-
IoBT were 14 x 12 x 4 mm and 1.1 g, respectively.
E. Summary and Insights
The IoBT devices are expected to play an important role in
the post-COVID-19 world to make health-care more affordable
and reachable for everyone. However, commercially available
IoBT devices mostly operate on RF bands and share common
disadvantages such as i) limited operational lifetime due to
complex and power-hungry radio front ends, ii) reliability and
latency issues due to interference from co-existing devices on
the same band, iii) vulnerability to security threats as a result
of highly radiative nature of RF propagation, iv) and being
restricted by stringent safety regulations on electromagnetic ra-
diation in and on the human body. As noted above, OWC-IoBT
devices can be a viable alternative since they are not affected
from such drawbacks. Accordingly, this section provided a
taxonomy of OWC-IoBT devices based on node locations and
present theoretical, numerical, and experimental advances in
various aspects. The state-of-the-art is also tabulated in Table
VII which categorizes literature based on study and application
type, spectrum, topology, Tx/Rx types, achieved rates, link
distance, modulation type, complementary technology, and
protocols used in higher layers. Indeed, Table VII helped us to
gain deep insights into the open research challenges and future
research directions, which are discussed in detail below.
1) The Need for an IoBT Protocol Stack: It is obvious from
Table VII that most of the existing works merely focus on
PHY aspects without accounting for its impacts on higher layer
functionalities. Considering the ultra-low-power and URLCC
requirements of IoBT applications, there is a dire need for
a protocol stack that integrates OWC to higher layers. For
example, the majority of works reported above employed OOK
modulation for its simplicity at the expense of higher power
consumption. Although commercial modules that follow IrDA
standards employ return-to-zero modulation with shorter pulse
duration, they still fail to satisfy µW power consumption
levels. Alternatively, the pulse interval modulation (PIM) was
shown to consume much less transmission power since it uses
a single short pulse to encode a symbol while OOK roughly
generates pulses as many as the 50% of the transmitted bits
[354].
Even though some of the works in Table VII report very
high data rates, these may not be practical for physiological
data which is small in size but sensitive to delay by its nature.
Therefore, more emphasis should be on tradeoff between
throughput, BER, delay, and overall reliability. In this regard,
Sohn et al. also developed an OWC protocol to address both
energy efficiency and delay sensitivity based on asynchronous
PIM. The experimental results on developed prototype showed
that their cross-layer protocol can deliver a significantly lower

29
power consumption (392 µW) than IrDA and Bluetooth Low
Energy (BLE).
Another important but unexplored area is investigating ef-
fective and simple multiple access schemes. This is especially
necessary for several on/off-body OWC-IoBT devices operat-
ing within the same environment. Excluding OCDMA in [339]
and WDM in [352], existing implementations mostly deal
with broadcast topology without paying attention on potential
access schemes for MAI. We believe more comprehensive
theoretical and experimental work is needed for the sake
of standardization of PHY and MAC layer functionalities of
OWC-IoBT.
2) Standardization and Commercialization Efforts: Al-
though IEEE 802.15.4 standard specifies PHY and MAC layer
aspects of generic wireless personal area networks, it has
been realized that it is not adequate to fulfill the requirements
of WBAN. Therefore, the IEEE 802.15.6 standard has been
developed as a PHY and MAC layer standard for ultra-low-
power and secure communications and networking for RF-
IoBT devices. Unfortunately, the IEEE 802.15.6 standard does
not recognize OWC as one of its PHY techniques.
As discussed in Section ??, IEEE 802.15.7 has been de-
veloped to embrace many OWC technologies (VLC, IR, UV,
OCC, etc.) by defining different device classes (infrastructure,
mobile, vehicle) with five different PHY types for different
QoS requirements. Unfortunately, IEEE 802.15.7 does not
recognize IoBT devices as well as their specific PHY and
MAC layer distinctions. In its current form, it is similar
to IEEE 802.15.4 and a new standard is needed for OWC-
IoBT similar to IEEE 802.15.6. We believe an OWC-IoBT
standard can be developed based on lessons learned from IEEE
802.15.6 and IEEE 802.15.7 standards. This new standard will
eventually pave the way for commercialization of OWC-IoBT
devices, which is mostly within the interest of academy.
3) Conflation of RR and SLIPT concepts: Even though the
LPT is studied well in the literature, the potential of SLIPT
concept for OWC-IoBT devices is waiting to be unleashed.
Since the LPT is nothing but the foundation of the SLIPT, we
believe there are many open research problems in developing
prototypes and algorithms to coordinate energy harvesting
and communications for energy self-sustainable OWC-IoBT
devices. To the best of author’s vision, conflation of RR
communication and SLIPT is a promising and interesting
direction. As shown in Fig. 11, the RR-OWC consists of
skin-surface light source and an implanted reflector. Similar
to backscatter communication RF systems, the reflector mod-
ulates the continuous light beam emitted from the source and
reflect it back to the receiver [349]. Since the modulation
power is negligible, the energy harvested by SLIPT would
be sufficient to design energy self-sufficient design.
VI. IN TE RN ET O F UNDERGRO UN D THINGS (IOGT)
The IoGT has recently been recognized to revolutionize the
mining industry to overcome daunting challenges posed by
extreme underground mine conditions. Indeed, large mining
companies have already started to embrace IoGT solutions for
the digitalization of daily management of mining operations,
which can be exemplified as follows:
•Monitoring the mining machinery through IoGT devices
can substantially reduce the operational cost and en-
hance productivity. For example, the Canadian mining
company Dundee Precious Metals installed sensors to
lighting/conveyor belts and RFID tags to miner helmets
for better asset tracking, which yielded an overall 400%
production increase in 20147.
•The strict mining regulations of governmental bodies
have made miners’ occupational health and safety a key
business priority. In this regard, the constant monitoring
of the underground environment for toxicity and venti-
lation levels can ensure people and equipment’s safety
by enabling timely first aids and efficient evacuations in
case of emergencies. By equipping miners’ vests with
physiological sensors, IoBT devices can also constantly
monitor the vital signs and identify a need for rest or
medical support to avoid accidents.
•Another crucial need in the underground mine is the
localization of miners. Indeed, tracking miners’ position
is of utmost importance for first aid as well as search and
rescue operations after explosions and collapses.
•Indeed, analyzing collecting such big data may lead
to discoveries of more cost and time-efficient ways of
running underground mines. Instead of deadly and costly
reactive decisions, IoT-based data analytics can enable
proactive measures through preventive and predictive
maintenance.
In order to reap these benefits, IoGT devices and network
infrastructure must overcome many real-life challenges. For
example, the underground mine environment is hot, humid,
dusty, and full of vibration, which reduces IoGT devices’
lifetime. Moreover, they are complex in structure and dark with
poor visibility, have constrained space availability, and offer
limited accessibility. Unlike its regular indoor counterparts, the
interior layouts dynamically change as new ore bodies are ex-
ploited, and old ones are exhausted. These peculiar conditions
translate into different challenges (e.g., signal propagation,
reliability, latency, coverage, etc.) and require a different mod-
eling and design approach than indoor terrestrial IoT devices
in terms of hardware, communication, and networking aspects.
From this point of view, there is no unique communication
solution to meet the need for effective and reliable connectivity
among IoGT nodes.
Wired communication was an early system used to facilitate
connectivity in the underground mines, including magneto
(crank ringer) phones, voice-powered phones, paging phones,
and dial&page phones. On the other hand, data communication
was implemented through PLC Ethernet and carrier current
systems (e.g., trolley railways and hoist-ropes) at low rates.
Even though the wired communication systems do not suffer
from harsh channel impediments, they are prone to line breaks,
cannot offer mobile communication and localization, and
not suitable for IoT concepts. Therefore, RF communication
techniques have been recognized as a modern alternative and
7https://www.i-scoop.eu/internet-of- things-guide/
industrial-internet- things-iiot- saving-costs-innovation/
industrial-internet- mining-case/

30
Fig. 13: Illustration of OWC-IoGT infrastructures with conceptual use cases.
adapted widely for in-mine network infrastructure. However,
in-mine RF communication is known to suffer from poor BER,
low data rates, and high delay spread [373]. This is mainly
because of the highly attenuating and irregular electromagnetic
propagation characteristics as a result of uneven and rough
walls, different size and shape of galleries, tunnels with
various form of turns (u-turn, wide/narrow, angle turn), and
the presence of pillars to support ceilings [374]. In-mine
RF communication is also affected by EMI due to metal
substances and running electrical machinery in the surrounding
environment.
Thanks to its inherent attributes, OWC can be a promising
complement technology to existing RF-based in-mine commu-
nication infrastructure. In particular, VLC technology is quite
suitable since there is already a dire need for sufficient illu-
mination to meet regulatory bodies’ occupational health and
safety standards. Therefore, an IoGT network infrastructure
can be built, as shown in Fig. 13, where the backbone network
is formed by hybridizing wired and wireless technologies.
While the former is constructed by laying down coaxial/fiber
cables power lines together, the latter is possible through P2P
OWC links (illustrated with red-colored light beams) between
APs, which are used for both illumination and communication
purposes. On the other hand, the access network consists
of OWC-IoGT devices installed on machinery, vehicles, and
miners. Similarly, the access network can be realized by
hybridizing infrastructure and ad-hoc topologies. OWC-IoGT
devices located on miners, machinery, and vehicles directly
communicate with a nearby AP in the former. However,
mines’ dynamic interior layout may eventually cause some
coverage gaps as new ore bodies are exploited, and old ones
are exhausted. In such a case, the coverage can be extended
through a wide variety of link combinations, e.g., V2V, body-
to-body, body-to-machine, and vehicle-to-machine, etc. Inte-
grating the envisioned OWC-IoGT network with existing in-
mine communication systems can yield a more reliable and
well-connected environment. Based on this hybrid network
architecture, OWC-IoGT devices can increase redundancy and
ensure reliable connectivity by complementing existing in-
mine communication systems.
Another potential use of OWC is in the oil and gas industry,
where the connectivity between surface and down-hole equip-
ment plays a major role in optimizing the well performance
and enhancing production efficiency. Although using armored
cables and wirelines is common today, installing and maintain-
ing wired solutions is technically challenging and expensive
as it requires a costly halt of production. Therefore, various
wireless technologies (mud-pulse telemetry, low-frequency RF,
and acoustic systems) have been developed. However, their
performance has not been found satisfactory for down-hole
monitoring systems. Down-hole OWC is also substantially
different from regular indoor OWC due to the presence of
different types of gases/liquids and the pipes’ shape and inner
coating material.
Since channel characteristics play a major role in the overall
performance of OWC systems, this section first provides a
general overview of OWC channel modeling in underground
environments by emphasizing its main distinctions from reg-
ular indoor OWC channels, which are summarized in Table
IX. Then, we provide recent advances in OWC-IoGT in terms
of various application scenarios, localization, and tracking
techniques, as well as its potential use in mines and gas
pipelines, which are summarized in Table VIII.
A. OWC-IoGT Channel Modeling
Although there are many models that precisely characterize
indoor OWC channels, they are not readily applicable for in-
mine OWC channels due to the following real-life factors:
1) signal degradation due to the dust particles on the air and
transceivers,

31
TABLE VIII: The major OWC-IoGT studies based on environment.
Env.
Type
Study
Type Application Ref. Year IoT
MWL Band OWC Comp.
Tech.
Higher
Layers
Topology Tx
Type
Rx
Type
Data
Rate Distance Mod.
Underground Mine
Implement.
Alarm/
Positioning [375] 2016 N/A VL
IR
Broadcast (DL)
P2P (UL) LED PD N/A 3-5 m OOK PLC N/A
PMU/
Positioning [376] 2020 N/A VL
UHF
Broadcast (DL)
P2P (UL)
LED
RF
PD
RF
N/A
100 K
5-10 m
10-20 m
OOK
GFSK RF N/A
Mine Cage
Safety [377] 2020 Custom VL
IR Broadcast LED PD N/A 3-5 m PWM N/A N/A
Simulation
Alarm [378] 2017 N/A VL Broadcast LED PD N/A 30 m OOK PLC N/A
Intf. Mang. [379] 2020 N/A VL Broadcast LED ADR 120-250 M 5-10 m OOK N/A N/A
Localization
[380] 2016 N/A VL Broadcast LED PD N/A 3-5 m OOK N/A N/A
[381] 2019 N/A VL Broadcast LED PD N/A 5-7 m IM/DD N/A N/A
[382] 2019 N/A VL Broadcast LED PD N/A 3-5 m N/A N/A N/A
Pipeline
Simulation Perf. Anal. [383] 2014 N/A VL P2P LED SPAD 1-5 K 400 m OOK N/A N/A
[384] 2018 N/A VL P2P LED PD 8 M 22 m M-PAM N/A N/A
Implement. Image Trans. [385] 2019 N/A VL P2P LED PD 50 K 3.5 m PWM N/A N/A
Robot Relay [386] 2019 N/A VL P2P LED PD 10 K 3.6 m PWM N/A N/A
Legend PLC: Power Line Communication, ADR: Angle Diversity Receiver, SPAD: Single-Photon Avalanche Diode,
M-PAM: M-ary Pulse Amplitude Mod, PWM: Pulse Width Mod.
TABLE IX: Channel models for OWC-IoGT applications.
Channel Impairment Factors
Ref. Model Year Tilt &
Rotation
Dust
Particles
Non-Flat
Walls Shadowing Scattering
[387]
Lambertian
2015 7 3 7 7 3
[388] 2018 7 7 7 3 3
[389] 2019 3 7 7 7 7
[390] 2020 7 7 7 7 3
[391] 2020 3 3 3 3 3
2) channel variations caused by shadowing and scattering
caused by irregular tunnel shapes and non-flat tunnel
surfaces,
3) impact of location and angular orientation of transceivers
as APs may not always be installed on the ceiling and
OWC modules installed on the miners’ helmet may
randomly tilt and rotate.
In Table IX, we categorize the in-mine OWC channel modeling
efforts in terms of counting in such factors. The impact of
tilt/rotation is considered in [389], [391], the dust particle
effects are studied in [387], [391], the light propagation though
non-flat walls are modeled in [391], and shadowing/scattering
are modeled in [387], [388], [390], [391]. Notice that all these
factors are comprehensively modeled and analyzed only in
[391].
To the best of the authors’ knowledge, the only OWC
channel model for gas pipelines was presented in [384]
where Miramirkhani et al. use ray tracing to investigate the
propagation characteristics of the down-hole VLC channels.
The authors used Zemax to create the simulation environ-
ment, which accounts for computer-aided design models of
pipeline/transceivers, the interior coating, and gas specifica-
tions to construct the channel impulse response (CIR) at
white/blue/red colors and FoV angles. Based on CIRs, they
also present the maximum communication range to ensure a
given BER.
B. OWC-IoGT Applications
In [375], an alarm and positioning system are demonstrated
by hybridizing PLC Ethernet and OWC technologies. In case
of an emergency, a central unit sends a warning/alarm to
APs (e.g., LED lamps) through a PLC network, which is
then broadcast to the receivers located at miners’ helmets.
Once the warning is received, the helmet sounds an alarm
and returns a beacon, which may include the miner’s ID,
through the IR system that operates on IrDA standard. Based
on the ID and location of AP receiving this beacon, the central
unit determines the location of the miner. By periodically
transmitting alarm signals, the central unit can constantly
monitor the miner’s location and identity. As this system is not
designed for data communication, the authors do not provide
any information regarding BER and data rate performance.
In [378], Farahneh et al. also proposed an alarm system by
hybridizing PLC Ethernet and OWC technologies. Noting that
authors did not specify any data rate values and did not validate
results with experiments, they presented the BER performance
under different levels of shadowing.
In [376], Soto et al. implement a hybrid VLC-RF scheme to
communicate with a portable phasor measurement unit (PMU),
which digitizes voltage, current, and phasors synchronously to
the coordinated universal time (UTC). In the DL, VLC-APs
broadcast UTC information to PMUs, which returns measured
electrical power system parameters through UHF-RF modules
in the UL. The VLC was also used for positioning based on
AP locations. The developed system has been shown to deliver
low error rates for both phase and position estimation tasks.
Unfortunately, the authors do not provide any information
regarding BER and data rate performance.
Mine cages [c.f. elevator in Fig. 13] has safety several safety
problems such as overloading with people/trolleys or accidents
caused by the outreach of human limbs. In [377], Yang et
al. proposed a solution using existing lighting equipment and
equipping the mine cage and miners’ helmets with cheap
LEDs/PDs. Each transceiver broadcasts its PWM modulated
information over a dedicated frequency that also represents
the transceiver’s identity. The developed system reaches more
than 95% accuracy in overloading judgment and detection
of limb outreach. As this system is not designed for data
communication, the authors do not provide any information
regarding BER and data rate performance.
In [379], Jativa et al. proposed a solution to mitigate inter-

32
cell interference in underground mining VLC system, where
LED lamps to communicate with miners’ helmet equipped
with angle diversity receiver. Authors evaluate the solution
by reporting various performance metrics such as RMS delay
spread in the order of 10−4−10−6, data rate between 120 and
250 Mbps, BER as lows as 10−5, and distribution of signal-
to-interference-plus-noise ratio (SINR) values.
In [383], Li et al. demonstrate the continuous downhole
monitoring for the first time. The light emitted from a LED
is received by a 4 km away SPAD that counts photons
efficiently thanks to the absence of ambient light within the
pipeline. For 1, 2, and 5 Kbps of data rates, the analytical and
simulation results showed that 10−6BER at transmitting SNRs
of 12, 15, and 18 dBm, respectively. Since the channel model
in [383] did not consider real-life pipeline characteristics,
Miramirkhani et al. evaluate the performance considering a
more realistic environment such as the presence of methane
gas, interior coating, and different LED color and FoV angles
in [384]. Authors evaluated the BER performance under these
scenarios with M-PAM modulation and determined maximum
transmission for 10−6BER.
Two interesting downhole monitoring systems are imple-
mented by Zhao et al. in [385], [386]. In [385] authors
implement an image transfer system over a pipeline (with
and without water) of length 3.5 m. Since the pipeline has
two 90ocorners, two relay nodes are placed to amplify and
forward the previous node’s signal. Numerical results show
that the developed system was able to reconstruct transmitted
images with sufficiently high quality. In their follow-up work,
authors extend this system to a mobile scenario where pipeline
inspection robots form a multi-hop relay to convey information
to a source node.
C. OWC-IoGT Localization
Similar to the positioning system developed in [375], [376],
an AP-ID positioning system is also proposed in [380] where
authors controlled the number of light sources (i.e., APs)
by turning them on and off through OOK to increase the
positioning accuracy by manipulating the overlapping AP
coverages. The numerical results showed that the maximum
position error in each cell may be fixed to obtain a positioning
system with constant accuracy.
In [381], Firoozabadi et al. proposed a VLC localization
based on three-dimensional trilateration methods. Unlike the
AP-ID positioning approaches above, the proposed system
estimates the location based on range estimation from multiple
APs and their known location. The localization error was
shown to be 3.5 for nodes closer to the APs and up to 16.4 as
nodes go far way from APs. A similar approach is considered
in [382] where location obtained by triangulation of three
light sources is put into GPS format. Notice in [375], [376],
[380]–[382] that authors do not report in any BER or data rate
information as these work were aiming at localization rather
than data communications.
D. Summary and Insights
The underground mines, pipelines, and tunnels pose more
complicated and peculiar problems than regular indoor envi-
ronments. For instance, underground mines are hot, humid,
dusty, and full of vibration. Moreover, they are complex in
structure and dark with poor visibility, have constrained space
availability, and offer limited accessibility. In addition, unlike
its regular indoor counterparts, the interior layouts dynamically
change as new ore bodies are exploited and old ones are
exhausted. Likewise, the OWC channel within pipelines is
different from its regular indoor counterpart due to varying
types of gases/liquids and the pipes’ shape and inner coating
material. Such peculiarities translate into different challenges
(e.g., signal propagation, reliability, latency, coverage, etc.)
and demand an alternative modeling and design approach in
terms of hardware, communication, and networking aspects.
For example, the commercial products available for indoor
environments can be used for IoGT applications if they are
put into a heavy-duty form with increased node lifetime and
durability.
Similar to the integration of the OWC-IoTT ecosystem with
existing terrestrial wired/wireless infrastructure, the OWC-
IoGT networks can also be integrated with enterprise under-
ground networks. If there is no available network infrastruc-
ture, the IoGT network infrastructure can be built merely based
on OWC technology [c.f. Fig] or in a hybridized manner with
the support of RF and wired networks. However, we should
note that existing indoor OWC standards do not account for
channel impediments of underground environments. Therefore,
these standards are required to be extended through channel
characterization campaigns to enable the OWC-IoGT ecosys-
tem.
VII. CONCLUSIONS
This survey paper provides readers with a top-down ap-
proach to an IoT ecosystem assisted by the OWC commu-
nication and networking technologies. Considering the ever-
increasing number of IoT devices and the limited electromag-
netic spectrum, the OWC can complement existing wired and
wireless technologies by granting abundant unlicensed light
spectrum access. In this way, the OWC can overcome spectrum
scarcity, mitigate interference limitations, and support IoT
applications with high QoS demands.
This complementary approach requires integrating existing
network infrastructure with the OWC technology, which be-
haves distinctly from existing wireless technologies at different
transmission mediums. Therefore, our survey started with con-
cepts and preliminaries on IoT network architecture and OWC
technologies, which is especially necessary to build a solid
discussion about how OWC technologies can be combined
with available IoT infrastructure in different domains. That
is, the first part of this work helps lay the background and
explains how and where the OWC technology fits in the IoT
architecture. On the other hand, the second part focused on
the challenges and advances of using the OWC in different
domains such as IoTT, IoWT, IoBT, and IoGT. In each section,
we first explain the opportunities opened up by the OWC,
the challenges in hybridizing OWC with currently available
technologies, and recent advances dealing with mentioned
challenges. Although each section is concluded with its own

33
summary and insights, we believe it is better to provide inter-
ested readers with notable take aways, which are summarized
below:
Regardless of the IoT domains, it is found that most of the
research done that includes the use of OWC in IoT applications
does not consider the IoT’s full-stack to observe the effects of
OWC on the full system performance. Instead, an OWC link is
used in a specific application, and the higher layers of the stack
are theorized. However, observing how OWC may enable new
types of IoT applications necessitates the creation of full-stack
systems because the limitations of OWC may affect the IoT
solution under consideration. For instance, IoTT devices can
be integrated with the available wired and wireless network-
ing infrastructure. Therefore, current OWC standards mainly
focus on PHY and MAC layer specifications without paying
sufficient attention to how higher layers should be revised
to reap the full benefits of OWC technologies. For example,
higher layers can be redesigned with specific protocols and
middleware concepts to better assist underlying applications
with enhanced end-to-end network performance by reaping the
full benefits of OWC integration. Moreover, these standards
do not account for environment-specific challenges even if
the OWC channels and related difficulties are non-trivial and
distinct in IoWT, IoBT, and IoGT domains. Although IoBT
can be integrated with existing infrastructure similar to IoTT,
there might not be a readily available infrastructure for IoWT
and IoGT domains. Therefore, a full-stack protocol might be
necessary to realize IoT in such extreme conditions. It is also
important to note that this protocols should be tailored to the
SWaP-C constraints of IoT devices, which are quite distinct
at different IoT domains and applications.
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