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arXiv:1808.05089v1 [cs.IT] 15 Aug 2018
1
On Optimizing VLC Networks for Downlink
Multi-User Transmission: A Survey
Mohanad Obeed, Student Member, IEEE, Anas M. Salhab, Senior Member, IEEE,
Mohamed-Slim Alouini, Fellow, IEEE and Salam A. Zummo, Senior Member, IEEE,
Abstract—The evolving explosion in high data rate services
and applications will soon require the use of untapped, abundant
unregulated spectrum of the visible light for communications
to adequately meet the demands of the fifth-generation (5G)
mobile technologies. Radio-frequency (RF) networks are proving
to be scarce to cover the escalation in data rate services. Visible
light communication (VLC) has emerged as a great potential
solution, either in replacement of, or complement to, existing RF
networks, to support the projected traffic demands. Despite of
the prolific advantages of VLC networks, VLC faces many chal-
lenges that must be resolved in the near future to achieve a full
standardization and to be integrated to future wireless systems.
Here, we review the new, emerging research in the field of VLC
networks and lay out the challenges, technological solutions, and
future work predictions. Specifically, we first review the VLC
channel capacity derivation, discuss the performance metrics
and the associated variables; the optimization of VLC networks
are also discussed, including resources and power allocation
techniques, user-to-access point (AP) association and APs-to-
clustered-users-association, APs coordination techniques, non-
orthogonal multiple access (NOMA) VLC networks, simultane-
ous energy harvesting and information transmission using the
visible light, and the security issue in VLC networks. Finally, we
propose several open research problems to optimize the various
VLC networks by maximizing either the sum rate, fairness,
energy efficiency, secrecy rate, or harvested energy.
Index Terms—Visible light communication, hybrid VLC/RF
networks, load balancing, non-orthogonal multiple access, energy
harvesting, physical layer security.
I. INT RO DU CTI ON
With the dramatic increase in total data traffic (approxi-
mately 7.24 exabyte-per-month in 2016, predicted to be 48.95
exabyte-per-month in 2021 [1]), there is an urgent need to
develop a fifth-generation (5G) of networks with a higher
system-level spectral efficiency that will offer higher data
rates, massive device connectivity, higher energy efficiency
(EE), lower traffic fees, a more robust security, and ultra-
low latency [2]–[4]. With the advent of the internet-of-
things (IoT) era, the amount of the connected devices to
the internet is increasing dramatically [5], [6], resulting in a
significant increase in data traffic that, and hence, crowded
traditional radio-frequency (RF) or wireless-fidelity (WiFi)
networks [7]. Small cells or network densification have been
proposed as a solution for 5G technologies [8], [9] in or-
der to increase the system capacity and coverage, reduce
the power consumption of mobile devices, and enhance the
networks’ EE. The continuity of dramatic growing in data
traffic demand has motivated researchers to explore new
spectrum, new techniques, and new network architectures
to meet these demands. Visible light communication (VLC)
has been introduced as a promising solution for 5G and
beyond. The motivation behind emerging the VLC technology
is the great invention of the energy-efficient light emitting
diode (LED) [10]. White LEDs outperform the other light
sources with their modulation performance, high electrical-
to-optical conversion efficiency, long life span, small size and
light weight, low cost, and operational speed [11]–[13]. LED
lamps consume approximately 20% of the power consumed
by fluorescent bulbs and approximately 0.5% of the power
consumed by traditional light sources [14].
Visible light communication uses a portion of the elec-
tromagnetic spectrum that is entirely untapped, free, safe,
and provides a high potential bandwidth for wireless data
transmission with rejecting the present RF interference [15].
Hence, VLC is a communication technology that uses LEDs
as transmitters to emit both the light and information signals
to the users. We should note that the power of the infor-
mation signal must meet the illumination requirements, as
well as being within the range of the LED’s physical limits
[16]. However, the non-linearity of LEDs in electrical-to-
optical transfer can be efficiently avoided using pre-distortion
mechanisms [17]. The VLC receiver contains a photo-detector
(PD) component that has the ability to convert the received
light intensity to a current signal. Data are transmitted using
an intensity modulation (IM) technique at the transmitter,
and received using a direct detection (DD) technique at
the receiver (IM/DD) [18]. This means that the modulating
signal must be real non-negative, and the existing modulation
techniques in the RF networks adjusted to fit this property.
Compared to RF networks, VLC networks provide higher
data rates, larger EEs, lower battery consumption, and smaller
latency. In addition, VLC can be safely used in sensitive
environments such as chemical plants, aircraft, and hospitals
[19]. Because of the small coverage of the transmitters in
VLC systems, an exhaustive reuse of frequency can be
implemented. VLC is also power-saving since the consumed
power for communication is already used for illumination and
may also be used for energy harvesting. Because the light can
be blocked by opaque objects, VLC functions properly only
in line-of-sight (LoS) communications, which own a robust
security since the unauthorized users who are out of sight
cannot receive an information signal of good quality.
Despite all the aforementioned VLC advantages, VLC faces
many technical challenges that must be resolved in the near
future to achieve its full standardization and integration with
future wireless systems. Among the most important challenges
to be overcome are relatively small bandwidth of LEDs,
2
deriving the exact channel capacity, channel estimation and
shadowing effects, backhauling VLC traffic into a large-scale
networks, the rapid decrease in light intensity with distance,
and the noise or interference that may be generated by
nearby lighting systems. One common solution to partially
overcome these challenges is optimizing the parameters of
VLC networks. Another common solution is to supplement
the VLC network by RF networks.
Numerous studies have investigated the potential appli-
cations of VLC to outdoor communications; yet, VLC is
better suited for indoor communications. According to various
published statistics, users of wireless information spend 80%
and 20% of their time in indoor and outdoor environments, re-
spectively [20]. In general, this paper reviews the optimization
techniques studied in the literature to improve VLC systems’
performance with focusing on target research directions.
A. Related Work
Several review articles have been written in the past on
the topic of the VLC technology [21]–[31], but none of them
addressed how the new emerging technologies in RF networks
could be mapped and applied in VLC networks such as the
non-orthogonal multiple access (NOMA), energy harvesting
(EH), simultaneous wireless information and power transfer
(SWIPT), space division multiple access (SDMA), and phys-
ical layer security (PLS). Specifically, Kumar et al. reviewed
LED-based VLC systems and applications in their early stage
development [21]. In [22], authors focused on the dual func-
tion of LEDs (used in smart lighting and VLC), and explored
their potential for integration by introducing a new concept:
LIGHTNETs (LIGHTing and NETworking) that performs
both functions simultaneously. Authors of [23] highlighted
the benefits and disadvantages of VLC networks, compared
with RF networks. The benefits of LEDs for illumination and
communications, modulation schemes, dimming techniques,
and the methods used for improving the performance of VLC
were reviewed in [24], while in [25], authors focused on the
VLC link level transmission and shed some light on medium
access techniques and visible light sensing. A more recent
study by Li et al. reviewed system-level VLC networks, with
a focus on user-centric network design, and compared it with
the network-centric design with emphasizing on the interfer-
ence reduction techniques [26]. In [27], authors explored the
differences among optical wireless communications (OWC)
technologies such as infrared communications, VLC, light-
fidelity (LiFi), free space optical (FSO) communications, etc.
Some review articles focused on specific aspects of VLC
such as VLC channel modeling methods [28], noise optical
sources and noise mitigation mechanisms [29], VLC-based
positioning techniques for indoor and outdoor applications
[30], and the pertinent issues associated with the outdoor us-
age of VLC in vehicular communication [31]. They generally
identified emerging challenges and proposed future research
directions.
This paper explores all the optimization techniques, previ-
ously reported in the literature, that aim to improve the VLC
network performance. Emphasis is placed on how the new
technologies, emerged in RF networks, mapped or used in
TABLE I
LIS T OF ABB R EV IATI O NS
4G Fourth generation
5G Fifth generation
AC Alternative current
ACO-OFDM Asymmetrically clipped optical OFDM
AP Access point
APA Access point assignment
BER Bit error rate
CoMP Coordinated multi-point
CSI Channel-state-information
CSK Color shift keying
DD Direct detection
DC Direct current
DCO-OFDM Direct current optical OFDM
EE Energy efficiency
EGT Evolutionary game theory
EH Energy harvesting
FoV Field-of-view
FFR Fractional frequency reuse
FR Frequency reuse
GEE Global energy efficiency
IM Intensity modulation
IoT Internet of things
LB Load balancing
LED Light emitting diode
LiFi Light fidelity
LoS Line of sight
MIMO Multiple input multiple output
MINLP Mixed-integer nonlinear programming
MISO Multiple input single output
MRC Maximum ration combining
MPPM Multipulse pulse position modulation
NGDP Normalized gain difference power allocation
NOMA Non-orthogonal multiple access
OFDM Orthogonal frequency division multiplexing
OFDMA Orthogonal division multiple access
OMA Orthogonal multiple access
OOK On-off keying
OPPM Overlapping pulse width modulation
OWC Optical wireless communication
PD Photo-detector
PD-NOMA Power domain NOMA
PDMA Pattern division multiple access
PIN Positive-intrinsic-negative
PLC Power line communication
PLS Physical layer security
PPM Pulse position modulation
PWM pulse width modulation
QoS Quality-of-service
RA Resource allocation
RF Radio frequency
RGB Red, green, and blue
RLL Run length limited
SCMA Sparse code multiple access
SDMA Space-division-multiple-access
SIC Successive interference cancelation
SINR signal-to-noise and interference ratio
SLIPT Simultaneous lightwave for information and
power transfer
SNR Signal-to-noise-ratio
SWIPT Simultaneous wireless for information and
power transfer
TDMA Time division multiple access
VLC Visible light communication
WiFi Wireless-fidelity
3
VLC networks such as NOMA, SWIPT, cooperative trans-
mission, SDMA, and physical layer security.
Specifically,
•This paper provides, in Section II, an overview of VLC
technology, defines and discusses the objectives and con-
straints that must be taken into account when optimizing
VLC networks. Special emphasis is placed on channel
capacity derivations, and the unique properties of VLC.
We also discuss the variables, parameters, and constraints
having an impact on the performance of VLC networks.
•All optimization techniques are reviewed in Section III,
including power and resource allocation, users-to-APs
association, cell formation, and AP cooperation used
for mitigating the disadvantages of VLC networks to
improve performance. This important topic was pre-
viously investigated by Li et al. [26]. However, their
study was focused on the difference between user-centric
and network-centric cell formations, and the interference
reduction techniques, whereas in this paper, we place our
attention on the techniques, used in RF/VLC and in VLC
standalone networks, that are aimed at alleviating the
limitations in VLC networks. In other words, we show
how to formulate optimization problems, what are the
techniques used for solving these optimization problems,
how the different objectives, limitations, constraints are
evaluated, and how added RF APs can remove stand-
alone VLC network limitations.
•By reviewing all the work conducted on NOMA-VLC
systems in Section IV, we show how such systems are
different from NOMA-RF architectures.
•In Section V, we survey the various energy harvesting
techniques used in VLC networks and show how this
added function (energy harvesting) affects the illumina-
tion and communication functions that are implemented
simultaneously, using LEDs.
•The topic of physical layer security in VLC networks
is also reviewed in Section VI, including the different
techniques proposed to improve the secure VLC com-
munications.
•In Section VII, we outline some remaining challenges
and open research areas in NOMA-VLC networks, en-
ergy harvesting in VLC systems, and securing VLC
networks. We present several ideas, which have not
been previously investigated or proposed, to improve the
performance of the different types of VLC networks.
With this article, our goal is to present a clear, comprehen-
sive picture of what has been accomplished so far, in the field
of VLC networks, and to present future research directions.
A list of abbreviation used in this paper is presented in Table
I, and the different types of VLC networks that considered in
this paper are shown in Fig. 1.
II. FU NDAM E NTALS O F VLC I ND OOR S YS T EM S
Because of its unique properties, a VLC channel is dif-
ferent from a RF or any other communication technology;
its optical signal is modulated via the intensity of the signal,
without carrying any information in phase or in frequency;
the transmitted signal is positive and real, the optical power
VLC networks
Transmitters’
design
Adding RF AP(s)
APs’ Coordination
SDMA and angel
diversity
transmitters
Receiver’s type
Legitimate users +
eavesdroppers
Information users
+ energy
harvesting users
Multiple access
schemes
NOMA
OMA
Fig. 1. Different types of VLC networks
is proportional to the mean of the input power signal (not
to the mean square of the signal amplitude); the transmitted
peak power is constrained by the LEDs dynamic range and
the illumination requirements.
A. VLC Elements
Every communication system must consist of a transmitter,
channel, and receiver. Here, we discuss the characteristics of
a VLC’s transmitter and receiver.
1) VLC Transmitter: The LED lamp is the most appropri-
ate transmitter used for both illumination and communication
purposes (see Introduction for details). Each lamp usually
consists of one or multiple LEDs driven by a circuit that
controls the intensity of the brightness, using the the ’flowing-
in’ current. The function of the driver circuit is to transmit
the data by modifying the flowing-in current, which, in turn,
modifies the light intensity. The flowing-in current must be
within the LEDs dynamic range in order for the output (light
intensity) to be linearly proportional to the input current. Be-
cause it shows the objects as they are without changing their
real colors, the white color is commonly used for illumination
and communication. Two common schemes are generally used
in design white LEDs. One uses a blue LED with a yellow
Phosphor layer [32], the other uses a combination of three
LEDs (red, green, and blue) [33].
Because of its low cost and simplicity of implementation,
the first type of LEDs (the blue LED with a yellow phosphor
layer) is more popular than the RGB type for designing white
LEDs. However, it has a limited bandwidth, compared to
RGB, because of the slow absorption and emission of the
4
coating phosphor layer. Khalid et al. [32] showed that a 1
Gbps data rate could be achieved, using this type of LEDs.
The RGB technique is better for communication as it uses the
color shift keying (CSK) modulation technique that modulates
the signal, using the three different LEDs. By doing so, data
rates of 3.4 Gbps data can be achieved [33].
One important issue that should be considered, when de-
signing the VLC, is the illumination requirements, which is
the main purpose of the LED. In other words, the illumination
range that is required should not be violated by the VLC
system. This means that the performance of the VLC system
is related to the illumination design requirements (more details
are given in Section II-D5).
2) VLC Receiver: The PD is a diode device sensitive to the
light intensity that can convert the received light to a current
modulated by the intensity of the light received. The PDs
that are commercially available can easily take samples of
the received visible light at a rate of tens of MHz [25].
There are three types of devices that can be used as
VLC receivers of the optical signal coming from the LED
transmitter: 1) photo-detector (e.g. positive-intrinsic-negative
(PIN) and avalanche PD), 2) an imaging or camera sensor, 3)
and a solar panel.
One of the advantages of a camera sensor is its availability
on most mobile devices such as smart-phones used to capture
videos and images. The main advantage of a solar panel is
that it can directly convert the received light to an electrical
signal without the need for an external power supply [34].
B. Channel Model
The receiver receives the LoS optical signal ans many
copies of non-LoS, coming from reflections. According to
[35], the optical power received from signals reflected more
than once is negligible. Fig 2 shows a channel model of VLC
links, containing the LoS and first reflected links. The LoS
VLC link between the AP iand the user jcan be expressed
as follows [13], [36]:
hj,i =Ap(m+ 1)
2πd2
j,i
cosm(φ)gof cos(θ)f(θ),(1)
where Apis the physical area of the receiver PD, mis the
Lambertian index given by m=−1
log2(cos(θ1/2), with θ1/2the
half-intensity radiation angle, dj,i the distance between AP i
and user j,gof the gain of the optical filter, φthe angle of
irradiance at the AP, θthe angle of incidence at the PD, and
f(θ)the optical concentrator gain is given by
f(θ) = (n2
sin2(Θ) ,0≤θ≤Θ;
0, θ > Θ,(2)
where nis the refractive index and Θis the semi-angle of
the field-of-view (FoV) of PD. Komine and Nakagawa [35]
showed that the DC attenuation of the channel, from the first
reflected link is given by
dh1=(m+ 1)Ap
2πd2
k,id2
j,k
ρdAscosm(φr)cos(α1)cos(α2)gof f(θr) cos(θr),
(3)
Fig. 2. Channel model, including the LoS link and the first reflected link
where αrand θrare the angels of the irradiance and incidence
of the first reflection link, respectively, d2
k,i and d2
j,k are the
distance from the AP ito the reflecting point kand the
distance from the reflecting point kto the user j, respec-
tively, ρand dAsare the reflection factor and the reflective
area, respectively, α1and α2are the irradiance angles with
respect to the reflected point and with respect to the receiver,
respectively.
C. VLC Modulation Schemes
As mentioned previously, data cannot be transmitted by
encoding the phase or frequency, and the modulation in VLC
is implemented by varying the light intensity of the LED.
On the other hand, the demodulation can be implemented by
direct detection at the PD. Various IM/DD-based modulation
techniques have been proposed and published in the literature.
On-off keying (OOK) was proposed for VLC, as a simple
modulation scheme, where data are represented by two levels
of light intensity [37], [38]. In order to obtain higher data
rates, in comparison with what OOK offers, pulse width
modulation (PWM) and pulse position modulation (PPM)
schemes, in which data are represented by the pulse width
and the pulse position, respectively, have been proposed.
The data rate in PWM can be increased by combining it
with the discrete multitone technique (DMT) [39], while the
data rate can be increased in PPM by using overlapping
PPM (OPPM) [40], multipulse PPM (MPPM) [41], or the
overlapping MPPM [42].
Due to the non-linear VLC channel response, the aforemen-
tioned modulation schemes suffer from inter-symbol interfer-
ence. To combat this impairment, the orthogonal frequency
division multiplexing (OFDM) scheme, widely used in RF
systems, should be modified to be compatible with the IM/DD
technique. Because the light signal is a real non-negative
signal, the complex bipolar signals generated by OFDM must
be represented by real positive signals in VLC. The solution
can be implemented by relaxing the Hermitian symmetry
constraint and convert the bipolar signal to a unipolar signal.
5
Two types of optical-OFDMs are widely used as VLC mod-
ulation schemes: a DC-biased optical OFDM (DCO-OFDM)
and an asymmetrically-clipped optical OFDM (ACO-OFDM).
In DCO-OFDM [43], [44], a positive direct current is added
to make sure that the signal is non-negative, and all the
subcarriers are modulated to maximize the spectral efficiency.
On the other hand, in ACO-OFDM, only odd subcarriers are
used to modulate the data [45], resulting in a symmetric time
domain signal.
D. Objectives and Constraints in VLC Networks
In this section, we present the established objectives for the
design or optimization of the VLC networks and discuss the
associated constraints that must be achieved. Certainly, some
of the unique characteristics of VLC technology have gen-
erated new challenges, different from those in RF networks.
As a result, the techniques used in traditional RF networks
cannot directly be applied to VLC networks.
1) System Capacity or Sum Rate: Several issues (that do
not exist in the RF systems) must be considered, when deriv-
ing the VLC channel capacity. These are: 1) dimming require-
ments, 2) peak optical intensity constraint, 3) illumination
requirements and the LED dynamic range, 4) and necessity
for the input signal to be non-negative and real-valued. In
addition, the channel gain for VLC is modeled almost as the
Lambertian model [35], in which the channel gain for VLC
is time-invariant but affected by geometrical parameters such
as the locations of the transmitter and receiver. Because of
the differences between RF and VLC systems, the capacity-
achieving input distribution does not have to be Gaussian
[46]. This means that the commonly derived Shannon channel
capacity formula used for RF systems cannot be applied to
VLC ones. Consequently, many researchers have been inves-
tigating the VLC channel capacity under these constraints.
Several papers have focused on the optical intensity channel
capacity, where only two constraints are imposed: the non-
negative real-valued intensity signals, and the average light
intensity for eye safety standard [46]–[48]. However, for the
VLC channel capacity, the illumination requirements and the
LED dynamic range constraints must be considered when
deriving the channel capacity. Ahn and Kwon [49] proposed
a numerical approach to determine the channel capacity for
inverse source coding in VLC, without providing a closed-
form expression for the VLC channel capacity, whereas Wang
et al. derived closed-form expressions for the upper and lower
bounds of the dimmable VLC channel capacity [50]. The
lower bound was expressed as follows:
C≥1
2log21 + e
2π(ζP
σ)2,(4)
where ζis the dimming target ranging from 0 to 1, Pis
the nominal optical intensity of LEDs, σ2is the Gaussian
noise variance, and eis the Euler parameter. The channel
gain (losses and opto-electronic transformation factors) is
assumed to be equal to 1, in Equation 4. Expression (4)
is the common expression used in the literature to estimate
the system capacity. The same authors derived closed-form
expressions for the upper and lower bounds of the dimmable
VLC channel, when imposing the peak optical intensity
constraint of the LED [51]. This constraint resulted in a
loss of channel capacity, and was found negligible when the
maximum allowed optical intensity was twice the nominal
optical intensity of the LEDs. With a different approximation
method used for the intrinsic volumes of the simplex, Jiang
et al. [52] derived a tighter upper bound, compared to that
derived in [50], for the VLC dimmable channel capacity.
Chaaban et al. derived the capacity bounds of the IM/DD
optical broadcast channel under two constraints, which are
the average light intensity and peak power intensity [53]. In
[54], Xy et al. derived a lower bound for the ergodic point-
to-point channel capacity. Because the VLC channel is time-
invariant and only depends on geometrical parameters, the
authors derived the ergodic capacity over the communication
region in the spatial domain, instead of the time domain. In
addition, they derived lower bounds for the ergodic capacity
in the dynamic systems for which geometrical parameters
follow typical distributions. For multiple-input-single-output
(MISO) VLCs with two users and two transmitters, Agarwal
and Mohammed [55] proposed an achievable rate region of
the proposed system VLC channel when the zero-forcing pre-
coder was applied. They showed that the largest rate region
was achieved when the average power of LED is half the
maximum allowed peak power.
2) Throughput: This criterion is different from the system
capacity because it calculates the actual transmitted data rate.
Determining the bit error rate (BER) and the used coding and
modulation schemes is required in finding the actual system
throughput.
The throughput of the user jcan be expressed in OFDM
systems using the following expression:
Xj=B
βL
βL−1
X
i=1
ηi,(5)
where Bis the modulation bandwidth, Lthe number of
subcarriers, ηthe subcarrier spectrum efficiency obtained from
the modulation scheme, coding scheme, and the received
signal-to-noise ratio (SNR) [56], and βis a constant that
depends on the kind OFDM used (e.g. for DCO-OFDM
β=1
2). In TDMA systems, the achieved throughput, at the
user j, is expressed as follows:
Xj=B
NT,j
NT,j
X
i=1
ηi,(6)
where NT,j is the number of time slots assigned for user j,
and ηiis the spectrum efficiency of the time slot.
3) Energy Efficiency: VLC networks are more energy-
efficient than RF networks because LEDs, used as transmit-
ters, are energy-efficient devices, and the consumed power
used for communication is also used for illumination. How-
ever, the range of acceptable illumination values is defined
by maximum and minimum requirements, meaning that the
consumed power can be controlled, within this given range, to
maximize the EE. In addition, with the advent of 5G wireless
networks, the tremendous number of access points (APs),
and the billions of connected devices, the need for designing
6
energy-efficient systems is becoming even more compelling
for seeking to have green communication systems. This is
confirmed by what is shown in [57] that the EE in VLC
networks was greatly affected by an increase in the number
of active users.
The EE can be improved by efficient resources optimiza-
tion, power allocation, energy transfer and harvesting, and
hardware solutions [58].
The common approach to guarantee energy-efficient sys-
tems is to optimally allocate the resources to maximize the
EE function subject to QoS and maximum transmit power
constraints. The EE function can be defined as the system’s
benefit over the total consumed power. In other words, if the
system’s benefit is the sum rate, then the EE is
EE =RT
PT
,(7)
where RTis the sum rate and PTis the total consumed power
at the transmitters.
Another way for improving the EE is to formulate the
optimization problem as minimizing the total amount of
transmitted power, under a given set of QoS constraints.
This type of optimization problems is easier to tackle than
the problem of maximization of the EE function. This is
because the EE function is not concave, in terms of allocating
the transmit power. The common approach to tackle the EE
maximization problem is to convert the non-convex problem
into a sequence of convex optimization problems using the
Dinkelbach’s method. Another way to improve the EE in VLC
networks is to harvest the energy by converting the received
light intensity into a current used for transmissions. This can
be implemented by equipping the receivers with solar panels.
4) Fairness: Fairness is an important issue in VLC net-
works for many reasons: 1) the dramatic decrease in the VLC
channel value with the distance between the transmitter and
receiver makes many users unable to switch from crowded
cells to uncrowded ones; 2) the small coverage stimulates
designers to fully re-use the frequency in the cells, resulting
in severe interference with the signal received by some users.
Fairness is commonly measured using Jain’s formula [59]
for a single cell or for the whole cellular system. The cell
fairness is
Fi=(PNi
j=1 Rj,i)2
NiPNi
j=1 R2
j,i
,(8)
and the fairness of the whole cellular system is
Fs=(PNap
i=1 PNi
j=1 Rj,i)2
Nap PNap
i=1 PNi
j=1 R2
j,i
,(9)
where Ni, Nap are the number of users associated to the cell
iand the number of cells, respectively, and Rj,i is the jth
user data rate associated with the cell i.
Fairness can be achieved either by formulating the opti-
mization problem to maximize the utility with a guarantee to
achieve a proportional fairness [60], α-proportional fairness
[61], or by adding the QoS constraints to the formulated opti-
mization problem. The concept of the proportional fairness is
to modify the objective function to imply both the system
utility (e.g. sum-rate) and the fairness. If we denote xas
the utility function, the generalized objective function can be
written as follows:
Γ(x) = (log(x), α = 1;
x1−α
1−α, α ≥0, α 6= 1,(10)
where αis a proportion factor. α= 0 means the utility is
only considered and the fairness is ignored; α= 1 means
that the proportional fairness is achieved, and, if α→ ∞, the
max-min fairness is achieved.
5) Required Illumination Constraints: The two functions
of LED, illumination and communication, are related to each
other and must be studied and optimized jointly. In other
words, the illumination requirements should be considered
in designing the input current to the transmitter LED. This
requirement implies that different constraints must be consid-
ered when optimizing the communication in VLC networks.
The constraints are the peak optical power, dimming require-
ments, and flicker reduction.
For the peak power constraint, we should note that the input
signal to the LED contains two components: the alternative
signal (that contains the information), and the DC signal used
to guarantee non-negative signal. The total energy emitted by
the LED determines the transmitted optical power and the
subsequent received signal strength, whereas the brightness
is determined by the luminous intensity [35]. We denote
Φmax,Φmin , and Φavg , as the predefined minimum illumi-
nation, maximum illumination, and the average illumination
over the entire area, respectively. For the office work, an
illuminance between 300 to 2500 lux is required [35].
The relation between the radiated optical power at LED
and the luminous flux at the point i, which is distant from
LED by dim with incidence and radiance angles θand ψ,
respectively, can be given by [62], [63]
hiPopt =δΦi,(11)
where δis the optical to luminous flux conversion factor [63]
which its value depends on the LED type; Popt is the optical
power, Φiis the luminous flux at point i, and hiis given by:
hi=m+ 1
2πd2
i
cosm(θ)cos(ψ),(12)
where mis the Lambertian index given in Section II-B.
One additional constraint for communication is that the
input DC-biased current (DC and AC currents) to the LED
must be within the dynamic range of the LED to have
the radiated optical power linearly proportional to the input
current [64]. For instance, the practical dynamic range of the
LED Vishy TSHG8200 is within [5 mW, 50 mW].
To meet the illumination requirements at all points in the
floor area, the upper and lower bounds of the optical power
should be set accordingly. Considering both the bounds of the
LED dynamic range and the illumination limits, the optical
power at the transmitting LED must be confined by
max(Pmin,ill, Pmin,D )≤Popt ≤min(Pmax,ill , Pmax,D ),
(13)
7
where Pmin,ill and Pmax,ill are the minimum and maximum
optical power required for achieving the corresponding illumi-
nation requirements, respectively; Pmin,D and Pmax,D are the
maximum and minimum power limits for the LED dynamic
range, respectively.
The dimming control is a desirable process for the illumi-
nation purpose [65]. For power saving, LEDs can be dimmed
to desired levels, using appropriate modulation schemes [37],
such as multi-pulse position modulation (M-PPM) [66]; or
variable OOK [67].
Another purpose for the used modulation scheme is to
mitigate the light intensity fluctuation to be unnoticeable by
the human eyes. To guarantee the flickering is above the
human eyes’ fusion frequency, flickering frequency must be
at least greater than 200 Hz [68]; this can be avoided by using
the Run Length Limited (RLL) codes that are used to reduce
the long runs of 0s and 1s.
TABLE II
SIM UL ATI ON PA RA ME TE RS
Name of the Parameter Value of the Pa-
rameter
Maximum bandwidth of VLC AP, B20 MHz
The physical area of a PD for IUs, Ap0.1cm2
The physical area of a PD for EH users, Ap0.04 m2
Half-intensity radiation angle, θ1/260o
FoV semi-angle of PD, Θ 30o−60o
Gain of optical filter, gof 1
Refractive index, n1.5
Efficiency of converting optical to electric,
ρ
0.53 [A/W]
Maximum input bias current, IH12 mA
Minimum input bias current, IL0A
Fill factor, f0.75
LEDs’ power, Popt 10 W/A
Thermal voltage, Vt25 mV
Dark saturation current of the PD, I010−10 A
Noise power spectral density of LiFi, N010−21 A2/Hz
Room size, 8×8
Room height, 2.5m
User height 0.85
Number of VLC APs, 4×4
Number of users, 5-35
Monte-Carlo for user distribution, 100 different
user distributions
RF
Number of RF APs 1
Location of RF AP (0,0) in the ceil-
ing
Transmit power 10 Watt
The distance of breakpoint 5 m
Central carrier frequency 2.4 GHz
Bandwidth 20 MHz
Angle of arrival/departure of LoS 45o
Standard deviation of shadow fading (before
the breakpoint)
3 dB
Standard deviation of shadow fading (after
the breakpoint)
5 dB
Noise power spectral density -174 dBm/Hz
6) Coverage Probability: Since the LEDs in VLC can
cover only a small area, and the coverage probability de-
creases dramatically as the distance increases, the coverage
is an important issue in VLC networks and should be consid-
ered when designing the networks’ parameters. The coverage
probability can be defined as the probability that the received
data rate for typical user is greater than or equal to a certain
data rate threshold. All the geometrical parameters of the
VLC channel affect the coverage probability, but we focus our
discussion on those having major impacts such as the distance,
optical power intensity, and the user’s field-of-view (FoV).
If we consider a system model consisting of multiple VLC
APs and the considered user jis served only by one AP i,
increasing the optical power would surely enhance the channel
link from the AP ito the user j, but would increase the
interference from all other APs significantly. The user’s FoV
plays a significant role in affecting the coverage probability,
since decreasing the user’s FoV leads to enhancing the VLC
channel and decreasing the number of interfering APs, but
we should also note that an extensive decrease in the user’s
FoV leads to decrease of the coverage probability. On the
other hand, for a given FoV, increasing the height of the APs
leads to an increase in the number of APs in the user’s field
of view, meaning that the number of interfering APs would
increase, and the path loss from the AP ito the user would
also increase.
Fig. 3 represents the effect of a user’s FoV on the coverage
probability by showing the number of APs that can cover
the area with different user’s FoV. Fig. 3 shows that the
coverage probability increases as the user’s FoV increases.
On the other hand, the channel quality decreases as the user’s
FoV increases (Fig. 4). Both figures show that the user’s FoV
has a great impact on the channel quality and the coverage
probability, meaning that optimizing the FoV would have a
significant impact on the VLC systems. Table II contains the
simulation parameters considered in our study.
7) The Harvested Energy: An additional function to LEDs,
besides the illumination and communication, is the transfer of
power, using the light intensity. When the VLC network con-
sists of users that need to harvest the energy, the parameters
should be designed to find a compromise between the three
functions. The receiver can harvest the energy by equipping
it with a solar panel that can convert the received modulated
light signal into an electrical signal without an external power
supply. Because the received current signal at the receiver
contains both DC and AC currents, the DC current can be
blocked and forwarded to the energy harvesting circuit. Li et
al., in [69], derived the energy that can be harvested by a user
from one LED as:
E=fIDC Voc ,(14)
where fis a fill factor of approximately 0.75, IDC the
received DC current, and
Voc =Vtln(1 + IDC
I0
),(15)
where Vtis the thermal voltage, and I0the dark satura-
tion current of the PD. If we denote the transmitted DC
current by b, the received DC current can be expressed as
by IDC =ρhPopt. Hence, if we have multiple LEDs, the
harvested energy at the user jis given by:
Ej=fρPoptVthT
jbln(1 + ρhT
jPoptb
I0
),(16)
where hjis the channel vector between the LEDs and the
user j, and bis the DC Bias current vector at LEDs.
8
-3 -2 -1 0 1 2 3
-3
-2
-1
0
1
2
3
0 AP
1 APs
AP
(a) FoV = 30o
-3 -2 -1 0 1 2 3
-3
-2
-1
0
1
2
3
1 AP
2 APs
AP
(b) FoV = 40o
-3 -2 -1 0 1 2 3
-3
-2
-1
0
1
2
3
1 AP
2 APs
3 APs
4APs
AP
(c) FoV = 50o
-3 -2 -1 0 1 2 3
-3
-2
-1
0
1
2
3
1 AP
2 APs
3 APs
4 APs
5 AP
6 APs
7 APs
8 APs
AP
(d) FoV = 60o
Fig. 3. Number of APs that can cover the area based on the user’s FoV.
8) Secrecy Capacity: When VLC networks contain two
types of users, the authorized users that have the authority
to obtain and decode the data, and the eavesdroppers try-
ing to obtain confidential messages without permission, the
performance metric is changed to be the secrecy capacity.
The secrecy capacity is defined as the maximum information
rate that can be attained by the legitimate receiver minus the
maximum eavesdropper’s information rate [70]. If the average
power constraint is only considered in the Gaussian wiretap
channel, the optimal input distribution is Gaussian; however, if
the amplitude power constraint is considered, it is difficult to
find the optimal input distribution for capacity-achieving [71],
but the lower and upper bounds can be found. However, for
the uniform input distribution and with considering amplitude
constraint |x(t)| ≤ A∀t, the secrecy capacity of the single-
input-single-output (SISO)-VLC system is lower and upper
bounded, respectively, by [72]
C≥1
2log 6h2
DA2+ 3πeσ2
πeh2
EA2+ 3πeσ2,(17)
and
C≤1
2log h2
DA2+σ2
h2
EA2+σ2,(18)
where hDis the transmitter-legitimate receiver channel, hEis
the transmitter-eavesdropper channel, σis the noise variance,
eis the Euler parameter, and Ais the peak power constraint.
III. RES OU RCE A ND PO WE R CO NT RO L WI TH AP
ASS IG NME NT
In this section, we review the optimization techniques
previously reported in the literature to improve the VLC
network performance when the system consists of multi-users.
Four main issues are considered in this type of networks,
for maximizing the various objectives and achieving the
various constraints discussed in Section II. These are: the
user-to-network association (called ’access point assignment’
(APS)), resource management, power allocation, and APs
coordination. The joint of APA and resource allocation was
identified by load balancing (LB). LB has been extensively
investigated in RF networks [73], [74]. However, the unique
9
30 35 40 45 50 55 60 65 70
FoVo
10-6
10-5
10-4
10-3
LoS channel
d=1
d=2
d=3
d=4
Fig. 4. The effect of user’s FoV on the channel quality with different
transmitter-receiver distance, when the angels of radiance and incidence are
zero.
properties of VLC technology make the problem different,
and the techniques used in RF networks cannot be directly
applied to VLC networks.
Despite all the advantages of VLC systems mentioned in
the Introduction, they suffer from several limitations that
contribute to the degradation of the system’s performance
such as a small coverage area, non-LoS failure transmission,
frequent handover, and inter-cell interference. This leads to
unbalanced systems, with some users receiving a poor service,
while others may receive a high QoS. For instance, the
opaque placed in the indoor environment might block the
LoS light that carries data for some intended users, leading
to a degradation of the channel by up to 90 percent of
the LoS channel [75], and, as a consequence, a significant
deterioration of the data rates for the intended users. However,
these opaque objects can block the inter-cell interference
coming from the adjacent VLC APs for other users. This
means that the fluctuation of the received QoS at users is
high and that the blockages significantly affect the system
fairness and the balance of the systems. Another cause for
unbalanced VLC systems is the handover. For the reason that
the coverage area of LEDs is small, the mobile users would
suffer from wasting resources by sending and transmitting
the overhead of the required handover. Fig. 5 shows how the
handover is an important issue in VLC systems. As observed
in the figure, the small coverage area of the LEDs in VLC
networks leads to a decrease in the throughput of both the
system and the mobile users due to the overhead generated
by such handovers [76]–[78]. However, by dividing the time
into sufficiently short periods, we can have quasi-static periods
known as ’states’. The handover consumes time, on average
from 30 ms to 300 ms [79]. Another issue due to the small
coverage area is the fact that the crowded static users cannot
be distributed to the deployed cells, resulting all or most of
them will be connected to one cell. This causes some APs to
be overloaded, and consequently leads to a poor service for
the connected users, while the other APs are unloaded or have
Fig. 5. Handover in VLC network.
a lower number of users. The bright side of the VLC’s small
coverage area is the fact that the whole bandwidth can be fully
re-used in all cells, which improves the spectral efficiency of
the overall system [80]. However, re-using the full frequency
in cells generates inter-cell interference, to some extent. Inter-
cell interference can be accepted for the sake of improving the
system’s spectral efficiency. On the other hand, the services
received by the users located at the edges of the cells would be
affected by this inter-cell interference. To summarize, because
of these issues, the users located at the edges of cells, blocked
by objects, in motion, or connected to overloaded APs can not
receive a good QoS like the other users. This significantly
deteriorates both the performance and fairness of the VLC
systems.
A. Optimizing Hybrid VLC/RF Networks
One of the most common solutions to the aforementioned
VLC issues is to supplement the standalone VLC networks
with RF networks. Compared to VLC networks, RF networks
are known for their ubiquitous presence (high coverage area)
and proper operation in non-LoS environments. In addition,
the devices connected to RF networks do not suffer from VLC
interference and vice-versa [81]. Therefore, adding one or
more RF APs to VLC networks mitigates the LoS blockages,
handover overhead, and inter-cell interference. However, a
problem remains: finding a compromise between the high
coverage area RF networks and the high capacity VLC
networks. In other words, how to distribute the users among
the APs (either RF or VLC) to improve the overall system’s
performance with an acceptable fairness of the system. The
main idea is to associate the users who suffer from inter-
ference, handover overhead, and blockages to the RF AP(s)
and keep the other users connected to the VLC networks. As
shown in Fig. 3, when the users’ FoV is 30o, the problem in
VLC networks is the coverage, whereas, if the users’ FoV is
greater than, or equal to 40o, the problem is the interference.
In Figures 6 and 7, we show how adding one RF AP to the
VLC network can enhance the sum rate and system’s fairness,
respectively. In these figures, we associate the uncovered users
(when FoV = 30o) and the interfered users (when FoV = 40o)
to the RF AP, while keeping the other users connected to the
VLC network. The simulation parameters are shown in Table
II, and the RF channel is modeled as in [82].
Several techniques have been proposed to balance the
load and tackle these issues by an efficient user distribution
among VLC/RF APs [76]–[78], [82]–[95]. LB consists of
two missions: the APs’ assignment (APA) and allocating the
10
resources, whether this resource is a time slot in TDMA
schemes or a sub-carrier in OFDMA schemes. Specifically,
Stefan and Haas [83] started to study the APA by distributing
the users between one RF AP and one VLC AP. Some of
the users were associated to the VLC AP to alleviate the
load of the RF AP, and the infeasible VLC connections were
transferred to the RF AP. In [84], by having multiple VLC and
RF APs, the advantages of combining RF and VLC networks
were investigated, and it was proposing that users can be
distributed dynamically, on both the VLC and RF networks,
based on the users’ channel condition. Users can then migrate
to the AP offering higher data rates. The APA was imple-
mented in [84] under the assumption that the resources are
allocated fairly among users. It was concluded that the hybrid
VLC/RF networks improved the performance significantly,
compared to the VLC or RF standalone networks. Authors
of [78] proposed to first associate the users to the VLC
network, and then, to re-allocate the users receiving a lower
data rate than a predefined threshold to RF APs. In [85],
authors formulated a centralized and distributed optimization
problem for user association to the APs (whether this AP is
VLC or RF AP) with allocating the resources jointly among
users. The centralized optimization problem, with considering
the proportional fairness [96], was formulated as a mixed-
integer non-linear programming (MINLP), which is highly
complex. Hence, a distributed algorithm was also proposed
with lower complexity compared to the centralized algorithm.
To decrease the number of handovers, Wang and Haas
[76] proposed a dynamic LB scheme in which the quasi-
static users are connected to VLC APs, and the moving
users are connected to the RF AP. In [86], [87], authors
upgraded the formulated optimization problem in [85] to
consider the handover in the dynamic systems. With consid-
ering the handover overhead and α-proportional fairness, the
authors of [86] formulated and proposed two solutions for
two optimization problems, i.e. the joint APA and resource
allocation problem (JOA), and the separate APA and resource
allocation (SOA). They compared the two approaches in terms
of performance and complexity. The former approach was
found to achieve a better QoS for the users, but with a
significant higher complexity, up to 1000 times greater, than
the later. In a separate study [87], instead of assigning the
users to a specific AP, Wu et al. formulated the problem by
considering the handover as a hierarchal assignment to first
assign the network (either RF or VLC) to each user, and then
select the appropriate AP, in the assigned network, for each
user. Because the problem formulated in [85] is for static
systems, those presented in [86], [87] provide a significant
improvement in the system performance for dynamic systems.
Instead of considering the handover with LB, Wu and Haas
[88] considered the LoS VLC channel blockages in the for-
mulated optimization problem. They modified the formulated
optimization problem to accommodate the LoS VLC channel
blockages. The main idea is that, the users that suffer from
a high occurrence rate of channel blockages should travel to
the RF networks, whereas the users that do not suffer from
blockages, or the ones that suffer from a low rate of blockages
(to avoid the effect of handover overhead), should stay in the
5 10 15 20 25 30 35
Number of system users
0
0.5
1
1.5
2
2.5
3
Sum rate (bit/sec)
×109
VLC+RF, FoV=30o
VLC only, FoV=30o
VLC+RF, FoV=40o
VLC only, FoV=40o
Fig. 6. Comparison of VLC/RF system and VLC alone by plotting the sum
rate versus the number of system users with different users’ FoV.
LiFi networks.
To avoid the complexity of solving these optimization
problems, fuzzy logic-based approaches were proposed for
balancing the load in VLC networks [82], [89], and [90].
Authors of [89] and [82] proposed two-stage assignment
process for the users in one RF AP and multiple VLC APs.
They first decided which users should be connected to the RF
AP, then they distributed the remaining users to the VLC APs,
regardless of the presence of the RF AP and its connected
users. In the fuzzy logic approach, the user jscores the APs,
based on its offered throughput, SNR, inter-cell interference
from the adjacent APs, and activity of the adjacent VLC
APs, then decides whether to connect to the RF AP or to
the VLC network, based on the resulting score. Similarly,
authors of [90] used this approach to handle the handover in a
dynamic hybrid VLC/RF system model. In their scheme, they
considered several parameters as an input to the fuzzy logic
approach: the instantaneous and average CSI, user speed, and
the minimum required data rate at users.
In [91], authors used another approach called the ’evolu-
tionary game theory’ (EGT), to solve the joint LB and re-
source allocation problem. Some practical issues were consid-
ered in their study, including the receiver’s orientation angle,
LoS blockage in RF and VLC APs, and the diversity in the
users’ data requirements. In addition, the channel of LiFi was
characterized with considering these practical factors. Authors
in [92] studied and compared the common approaches used
for balancing the load in the hybrid VLC/RF networks which
are: 1) optimization based algorithms, 2) evolutional game
theory, 3) fuzzy logic based algorithms. They showed that, for
the dynamic systems when the handover is considered besides
the AP assignment and the resource allocation, the fuzzy-
logic-based algorithms outperformed the other approaches,
whereas for the static systems, the optimization-based algo-
rithms are the best, with a slight improvement over the simpler
EGT approach.
Authors of [93] used a different approach for assigning
the APs in the dynamic systems, using bandit theory with
11
5 10 15 20 25 30 35
Number of system users
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
System fairness
VLC+RF, FoV=30o
VLC only, FoV=30o
VLC+RF, FoV=40o
VLC only, FoV=40o
Fig. 7. Comparison of VLC/RF system and VLC standalone by plotting the
system fairness versus the number of system users with different users’ FoV.
considering the accumulated reward gap function as a per-
formance metric. Their idea was to consider the learning
aided AP assignment that enables the system to adjust the
AP selection probability depending on the learning historical
reward information and the environmental information. In
[77], authors distributed users to the APs by applying the
matching theory, as the users were mapped to be students
and the APs were mapped to be collages. Then, taking into
account the preferences (i.e. system throughput, users’ moving
directions, and fairness index), students (users) would decide
which collage (AP) is the best for them to maximize their
preferences, in return, collages accept the maximum number
of applicants to maximize their preferences, while rejecting
the others. The rejected students would go to their second
preferable collage (AP), and so on.
In a different way, we proposed new algorithms for joint
APA and power allocation aiming to improve both the system
capacity and fairness [94], [95]. Because the assignment
of APs, power allocation, and determination of the exact
interference information are interlinked problems, iterative
algorithms were proposed to efficiently jointly distribute the
users to APs, and to distribute the powers of the APs to the
users.
Some studies focused on allocating the resources, rather
than APA [97]–[101]. These methods are appropriate for the
quasi-static systems and when the LoS blockages are not
present. In [97], authors considered both the multi-homing
and multi-mode mechanisms and they formulated for each
mechanism an optimization problem to allocate the resources
for maximizing the effective capacity by satisfying the sta-
tistical delay target. In the multi-homing mechanism, users
can gather the information from the VLC and RF APs at the
same time, whereas in a multi-mode mechanism, users can
be connected to one type of networks only. Unlike the multi-
homing mechanism, the centralized formulated optimization
problem for multi-mode mechanism needs to select the AP for
each user; therefore, a computationally intractable approach
was considered in [97], and a distributed suboptimal method
was proposed. They showed that, by tightening delay require-
ments, the multi-homing mechanism provides a much better
performance. In [98], for multi-users with multiple VLC APs
and one RF AP, authors studied the problem of maximizing
the EE under maximum power constraints on both RF and
VLC APs, and under QoS constraints, when the multi-homing
mechanism was applied. In [99], authors expanded on the
work presented in [98] and [100], and jointly allocated the
power and bandwidth to the users, but in only one VLC and
one RF AP. Both [98] and [99] used Dinkelbach method to
convert the nonconvex problem to a sequence of convex prob-
lems, then used the sub-gradient method to solve those convex
problems. By assuming that a multi-homing mechanism is
available to users, there is no need to balance the load by
efficiently distributing the users between the RF and VLC
APs. In [101], a system consisting of a cascaded power-line-
communication (PLC)/VLC link, along with a RF link was
optimized, meaning that the total transmitted power under
QoS constraints was minimized. The formulated optimization
problem was shown to be a convex problem that could
be solved efficiently. In [102], authors formulated a power
and sub-channel allocation optimization problem for energy-
efficient software-defined VLC/RF network, when the users
have the multi-homing capability. The optimization problem
considered the backhaul constraints, QoS requirements, and
the inter-cell interference constraints. With the help of the
software-defined controller, the resource allocation strategy
can be requested as an application from the application layer,
then through the software-defined controller, the requested
strategy can be implemented in the APs in the physical
layer. Because the objective function is the nonconvex EE
function, the Dinckelbach approach was also used to convert
the problem into a serial of convex optimization problems.
In [103], a comparison between the performance of the
standalone VLC networks with that obtained from augmenting
RF APs to the VLC network (in terms of outage probability)
was provided. Specifically, authors quantified the minimum
required RF resources (bandwidth and power) for the VLC
networks to achieve a predefined (per user) rate outage per-
formance. In [104], Tabassum and Hossain used the stochastic
geometry to analyze the coverage and the rate of a typical user
and compared the results in four types of networks: RF-only,
VLC-only, opportunistic RF/VLC (either the user connected
to RF or VLC), and the hybrid RF/VLC (the user can gain
the resources from both the RF and VLC APs) networks.
Based on several parameters including the FoV receiver,
number of interfering LEDs, distribution of the interference,
association and coverage probability, and the average rate
of the typical users, they found closed-form solutions to
distribute the users among the VLC and RF APs. By imposing
the QoS constraints based on the data link metrics, i.e. the
limits on the buffer overflow and buffering delay probabilities,
Hammouda et al. [105] showed that the VLC links offered
queuing delays lower than RF links when the data arrival
rates at the transmitter buffer were low; however, the RF links
supported the higher data arrival rates.
12
B. Optimizing the Standalone VLC Networks
As previously shown in III-A, the most common solution
for handover, LoS blockages, coverage, and the inter-cell
interference is to support the VLC network by a RF network.
However, some studies reported in the literature focused on
the LB in standalone VLC networks.
In [106], with the help of a central controller, and by
considering the arbitrary receiver orientation, Soltani et al.
proposed an approach for APA to users, based on the strength
of the received signal and the traffic of the APs, aimed at
maximizing the system’s throughput. Briefly, when a com-
ing user wants to join an established network, the central
controller calculates all the offered data rates from all APs
and enables the user to select the best AP for him. In [107],
authors jointly allocated time resources to the users and
assigned APs to the users. They conceived the problem as
a bidirectional allocation game, since the aim of APs is to
select the only users that maximize the system throughput,
and the users want to select APs providing better QoS. By
considering mobile users in standalone VLC networks, Zhang
et al. [108] proposed a novel user-to-AP assignment based
on anticipating the future users locations and their traffic
dynamics, and find a trade-off between the delay and the
throughput in the dynamic VLC systems. In [109], authors
studied and formulated the joint power allocation and LB
problems. By considering a proportional fairness [96], the
formulated optimization problem was found an intractable
nonconvex. Thus, a suboptimal solution was proposed to
optimize both the power and the time fraction in an alternating
fashion.
Another factor that can be used to enhance the performance
of VLC networks is the arrangement of APs, in which APs are
placed and selected in the most appropriate way to improve
both the illumination and communication. In [110], authors
investigated the effects of the cell size and network deploy-
ment on the performance of VLC systems by measuring the
signal-to-noise and interference ratio (SINR) distributions,
outage probabilities, and data rates. They concluded that the
hexagonal cell deployment achieved the best performance,
whereas the random cell deployment exhibited the worst
performance. In addition, they demonstrated that the multipath
effect was much less prominent than the effect of the co-
channel interference because of the PD’s size compared to
the light wavelength. They also compared the performance
of the VLC with the RF and mmWave indoor networks and
showed the superiority, in general, of the VLC systems.
The aforementioned papers optimized the VLC networks
based on a TDMA scheme. In [111] and [112], the resources
in an OFDMA scheme were allocated to maximize the
throughput in the downlink LiFi networks. Ling et al. [112]
first showed that the problem of allocating the DC bias, the
power, and the subcarriers is a coupled problem, and then
proposed several algorithms, to compromise between the per-
formance and complexity, starting by proposing an algorithm
for allocating the DC bias only, two algorithms for allocating
the power and subcarrier jointly, and finally two algorithms
to jointly optimize the DC bias, power, and subcarrier. In
[111], unlike [112] which considered the subcarriers, authors
focused on allocating the time-frequency blocks to increase
the flexibility in resource allocation. When allocating the
subcarriers, channel responses should be considered, taking
into account the fact that the channel quality in the low
frequencies is better than that in channels at high frequencies
[110]. Because the channel quality depends on the frequency,
a careful allocation of the subcarriers (taking the channel
into account) leads to a more efficient resource allocation in
OFDMA more than that in TDMA.
TABLE III
PROP OSE D TE CHNI QUES T O A LLEV IATE TH E LI MI TATIO NS ASS OCI ATED
WI TH V LC NE TW OR KS
Issue Solution in hy-
brid VLC/RF
Solution in standalone VLC
Small cover-
age
Associate
uncovered
users to RF
network
•CoMP
•FoV alignment
•MIMO
•efficient APA
Blockages Associate the
blocked user to
RF network
•Efficient APA
•Serve each user with
multiple APs
Handover Associate the
unfixed users
to RF network
•Merge VLC APs to be
one cell
•distribute the APs based
on the anticipated loca-
tion of the user
Interference Associate the
edge-users to
RF network
•SDMA
•Frequency reuse
•Fractional frequency or
time reuse
•Joint transmission
•APs arrangement
•User-centric network de-
sign
•Efficient resource and
power allocation
Limited
LEDs
bandwidth
Equipping the
users with
multi-homing
capability
to gather
information
from RF
and VLC
simultaneously
•Efficient LED design
•extensive frequency reuse
•joint transmission
•Densify the APS and ap-
ply the user-centric de-
sign
•employ NOMA
•efficient resource alloca-
tion
C. Coordination between VLC APs
In this section, we review the references that utilized APs
cooperation techniques to improve the VLC networks. The
APs in VLC networks can work together to beamform the
transmitted signals, remove or mitigate interference, improve
the space diversity gain, increase coverage, decrease the han-
dover overhead, and decrease the received SNR fluctuations.
A coordinated multi-point (CoMP) transmission technique
can be implemented by connecting multiple APs through
backbone networks so that they can cooperate to design their
transmitted signals. Therefore, the joint transmission (JT) can
13
be implemented between the coordinated transmitters to form
one cell.
Li et al. [85] studied how the APs should cooperate to
mitigate the interference with balancing the load. For man-
aging interference in the NAPs and Nusers system model,
the APs in the proposed system in [113], were designed to
organize themselves into a cooperative coalition based on the
game theory coalition formation. In [114], authors adopted
the joint transmission scheme to alleviate the effect of the co-
channel interference and to improve the system throughput
and the quality of the received signal. In addition to the co-
channel interference, the impact of blockages on users can be
mitigated using the CoMP joint transmission scheme [115].
Authors of [115] proposed an approach that assigns multiple
transmitters to each user, with proportional fairness. Serving
a user by multiple LEDs transmitters significantly mitigates
the rate of blockages and the handover overhead.
To decrease the backbone traffic and decrease the amount
of the exchanged information, authors in [116] coordinated
the various transmitters to control interference by either par-
titioning the resources among transmitters, or by controlling
the transmitted power. Partitioning the resources between
transmitters decreases the spectral efficiency significantly,
even though the inter-cell interference is eliminated [116].
Hence, in [117] and [75], fractional frequency reuse (FFR)
was used to trade-off the spectral efficiency for the inter-cell
interference, whereas Sun et al. [118] designed the signal for
VLC system to trade-off between the interference and the
spectral efficiency by imposing time superposition reuse in
two neighboring cells, then they proposed an optimal power
allocation strategy for this signal design approach. Ma et
al. [119] exploited the spatial domain and coordinated the
transmission to mitigate interference in a multi-cell MU-
MISO VLC system, by considering the backbone limited
capacity.
Because only the non-negative real-valued signals can be
transmitted in VLC systems, precoding techniques proposed
in literature to CoMP VLC networks are different from
these investigated in RF networks. Zero-forcing and dirty
parity coding were investigated and compared in multi-
user multiple-input-single-output (MU-MISO) VLC systems
in [120] for maximizing the SINR, whereas zero-forcing-
based precoding scheme was proposed in [121]–[123] for
minimizing the mean square error. Authors in [124] also used
the zero-forcing a precoding approach for maximizing the
achievable data rate, whereas authors in [125] proposed a
generalized-inverse-based zero-forcing scheme to maximize
the max-min fairness and system sum rate.
For multi-user-multiple-input-multiple-output (MU-
MIMO) VLC systems, in which users are equipped with
multiple PDs, the block diagonalization approach was
proposed in [126] to remove interference. Pham et al.
[127] used the same precoding approach when considering
the non-negativity constraint on the input signal. The
Tomlinson-Harashima precoding approach was proposed by
Chen et al. in [128]; the authors showed it outperforms the
block diagonalization approach in terms of BER. A robust
linear precoding and receiver design for maximizing the
minimum SINR was proposed in [129]. Authors in [130]
showed that the dirty paper coding performed better than
the linear precoding approaches when the users’ CSI are
known, whereas the linear precoding approaches are better
when only an imperfect users’ CSI is available. To mitigate
the effects of the indoor VLC channel correlation, authors
in [131] calculated a precoding matrix for each subcarrier in
a MIMO-MU-OFDM VLC system by exploiting the phase
differences, after transforming them to a frequency domain
of different links. The precoding matrix was designed
to eliminate the inter-user interference. Cai et al. [132]
proposed algorithms of PD selection in imaging receivers
to mitigate the channel correlation and decrease the BER
in a MU-MIMO-OFDM VLC system. By exploiting the
knowledge of the transmitted symbols, authors of [133]
proposed an adaptive precoding scheme to only eliminate
the destructive interference and correlate the constructive
interference. Designing the precoding matrix to correlate the
constructive interference provides a significant improvement,
in terms of BER, compared to the zero-forcing precoding
approach [133].
Space division multiple access (SDMA) has been proposed
in VLC networks to mitigate effects of interference and to
improve the spectral efficiency [134]–[138]. In the SDMA
scheme, multiple LEDs are designed to generate spatially
separated beams that are directed to various users. Kin and
Lee [134] showed experimentally that the SDMA efficiently
can improve the amplitude of the received signal. In [135],
authors proposed a low complexity algorithm (compared
to the exhaustive search algorithm) named ’random pairing
algorithm’ for grouping the users into multiple SDMA groups
in order to obtain a better area spectral efficiency under users’
fairness constraints. Each user group is served by multiple
coordinating APs when applying the zero-forcing precoding
method to eliminate the inter-cell interference. In [136] and
[137], authors proposed the use of angle diversity transmitters
to increase the bandwidth and mitigate the interference. The
authors estimated the performance of a SDMA-VLC system
by deriving the analytical upper and lower bounds of the
average spectral efficiency. When the number of LEDs is
much larger than the number of users, where multiple LEDs
can serve one user, and using the angle diversity transmitters
proposed in [137], authors in [138] addressed the problem
of properly assigning multiple LEDs for each user. A power
allocation algorithm was also proposed to improve the sum
rate and the system’s fairness.
In a very dense VLC networks, especially when the number
of users is much lower than the number of APs, a user-
centric (UC) design is the most appropriate approach for cell
formation in VLC networks. In [139], Zhang et al. investi-
gated the user centric design for VLC, for which the cells’
structures do not have a specific shape. They first clustered the
users, then associated the APs to the grouped users. In [140],
Li et al. extended the work to improve the fairness among
users by proposing algorithms aimed at scheduling users and
maximizing the sum utility of the system. In [62], in addition
to forming the cells and associating the APs, they allocated the
powers to the clustered users aiming at maximizing the EE of
14
the distributed cells. In [141], authors used these techniques of
cell formation and power allocation to design energy-efficient
scalable video streaming with considering an adaptive mod-
ulation mode assignment. The common clustering approach
used in [62], [140], [141] is the edge distance clustering. After
the users are clustered, the APs are assigned to the clustered
users, using an anchoring AP association approach. Finally,
the power at the APs is allocated to the associated users to
maximize the EE.
Authors of [57] and [142] showed that the procedures user
clustering, AP association, and power allocation are joint
problems, when the EE maximization is the target. Hence,
they proposed a novel user clustering method to maximize the
separation between clusters and help in reduce the inter-cell
interference. They then proposed a joint power allocation and
AP association to maximize the EE. Inside the formed cells,
two common transmission schemes were used in these papers
that adopt the user-centric design: either use the combining
or the vectored transmission schemes.
IV. NOM A IN VLC
In this section, we introduce NOMA, a new technology
nominated for the fifth generation (5G) wireless networks
aimed at increase the throughput, decrease the latency, and
improve the fairness and connectivity. The rational behind
NOMA is the use of a single resource component by multiple
users, whether this component is a sub-carrier, a time slot, or
a spreading code. With this basic concept, different types of
NOMAs, such as the power domain NOMA (PD-NOMA),
pattern division multiple access (PDMA), sparse code multi-
ple access (SCMA), were presented as good candidates for
the 5G multiple access technique. More details on NOMA in
traditional RF networks are provided in [143], [144].
In VLC networks, researchers are interested only in power
domain NOMA (PD-NOMA). The goal of PD-NOMA is to
set different power levels for different users. For instance, for
two users served by the same base station (BS), and using
the same OFDM subcarriers, the BS assigns a high power
to the user with poor channel and a low power for the user
with a better channel. In other words, assuming that h1> h2,
where hiis the channel of the ith user, the BS transmits
the signal of User 2 with higher power. User 2 decodes the
received signal and treats User 1’s signal as noise, whereas
User 1 first decodes the signal of User 2, and then removes it
from the received signal, after that it decodes his own signal.
To generalize this idea, we assume that we have Nusers
served by the same BS, and first categorize them based on
their channel gains as h1≤h2≤.... ≤hN. When using
the NOMA technique, the BS transmits the signal of all users
using same carrier, and the received signal, at the kth user,
can be expressed as follows:
yk=hk
N
X
j=1
αj√P sj+nk,(19)
where αjis the power coefficient of the user j,sjis the
information signal of the user j, and nkis the additive white
Gaussian noise. According to NOMA, users with a lower
2 4 6 8 10 12 14 16
Weak user distance (m) (Strong user distance = 2 m)
6
8
10
12
14
16
18
20
Sum rate(bit/sec/Hz)
NOMA
OMA
Fig. 8. The impact of increasing the distance of the weak user with achieving
the fairness constraint that both users receive equal data rate, when FoV =
40, incidence angle = 0, and irradiance angle = 0.
0 1 2 3 4 5 6 7 8 9 10
X coordinat of the weak user (Y coordinat is 0)
2
4
6
8
10
12
14
16
18
Sum rate(bit/sec/Hz)
NOMA
OMA
Fig. 9. Shifting the weak user in the X coordinate where the incidence
and irradiance angles changes accordingly, the strong user located at (0,0)
coordinate, FoV = 40.
channel gain will have a higher power, meaning that α1≥
α2≥.... ≥αN. Then, the successive interference cancellation
is implemented to decode the signals received by the users.
In other words, User Nmust decode all the signals of all
users to have his own signal, and User N−ihas to decode
N−isignals to obtain its intended signal. It is clear that,
as the number of users increases, the complexity of decoding
the signal is increased. In addition, the residual interference
coming from inaccurate channel estimation increases with the
number of users.
Implementing the NOMA in VLC networks requires con-
sidering the unique properties of VLC networks such as the
limited bandwidth of LEDs, the maximum transmit power that
is restricted by the illumination requirements, the blockages
that make the channel between the transmitter and receiver
close to zero, and the dramatic deterioration in the channel,
as the distance increases. In addition, the channel value can
15
be controlled by changing the FoV of the receivers or the
semi-angles of the transmitters (if they are tunable), and these
two factors can be selected to improve the performance of
NOMA-VLC networks. Because the PD-NOMA scheme is
based on successive interference cancellation (SIC), NOMA-
VLC networks require all users’ CSIs to be available, which
is the case in VLC. It was also shown that the NOMA scheme
performance is enhanced as the SNR increases [145], which is
the case of VLC link. These features offered by NOMA-VLC
networks led many researchers to investigate these networks
and find out how the NOMA outperforms OMA schemes in
VLC systems. Figures 8 and 9 present simulation of how the
NOMA outperforms OMA in VLC networks, for two users
and one AP VLC system, when only the distance of the weak
user increases (Fig. 8) and when the distance, incidence and
irradiance angles are changed (Fig. 9). ’Strong’ and ’weak’
users mean the user with the best channel and the user with the
worst channel, respectively. In [146], Huang et al. proposed
a mathematical expression of the symbol error rate analysis.
In [147] and [148], authors showed the superiority of NOMA
over OFDMA, in VLC systems, with respect to sum rate and
BER performance, respectively. In order to allocate the power
that maximizes the sum rate, authors of [149] optimized the
NOMA-VLC downlink for a two-user system, with satisfying
certain QoS constraints. They also provided a semi-closed
form to the optimal power allocation.
In [150]–[154], authors evaluated the performance of the
NOMA-VLC for one VLC AP and multiple users. In [150],
[151], authors presented distribution functions for the uni-
formly distributed users, then evaluated the NOMA-VLC
system by comparing it to OMA-VLC system in two case
scenarios: 1) when each user has a data rate target, and 2)
when the data rates of all users are assigned opportunistically
according to their channels. By considering the proportional
fairness [96], authors of [152] showed that the formulated
problem was of non-convex type, but could be converted to
a convex problem that could be solved using a dual decom-
position method. Authors of [153] evaluated and compared
the NOMA and OMA schemes, when the users change their
locations and their vertical orientation. Instead of reporting
the full CSI that increases the computational complexity, they
used limited-feedback schemes to categorize users based on
their mean vertical angle and mean distance, and this might
be most appropriate to simplify the implementation.
For multiple APs, authors of [154] studied NOMA-VLC
networks when the network consisting of two VLC APs and
three users. They proposed a gain ration power allocation
(GRPA) approach to allocate power to the various users, and
compare it with the static power allocation approach; assum-
ing that the users’ movement is assumed to follow random
walk model. In the GRPA approach, the power for the user k
is assigned to be Pk= ( h1
hk)kPk−1. Assuming the users’ FoV
and the transmission angels of LEDs are tunable provides a
potential to improve the performance significantly. For multi-
cell VLC networks, under the assumption that the frequency
reuse FR = 2, the users in [155] were grouped based on the
received interference. If any user suffered from interference,
they were given a special resource blocks, and NOMA was
implemented for the remaining users. For the users sharing
the same resource block, the authors formulated optimization
problems to allocate the power, under QoS constraints, and
provided solutions to the formulated problems.
NOMA has been also used in MIMO VLC systems [156],
[157]. In [156], authors experimentally investigated a system
with single carrier mode of transmission, using the frequency
domain SIC, but without considering the power allocation
problem. In [157], Chen et al. proposed a power allocation
algorithm (called normalized gain difference power allocation
(NGDP) approach) aimed at reducing the complexity and
increasing the efficiency of 2x2 MIMO-NOMA-VLC systems
with multiple users. In their study, they classified the users
using the sum of the channel gains for each user, with respect
to each LED. In the proposed power allocation method, the
power allocated to the user kand user k+1 in the ith LED are
related: Pi,k = ( h1i,1+h2i,1−h1i,k=1 −h2i,k+1
h1i,1+h2i,1)kP2i,k+1, where
hji,k is the channel between the ith LED and the jth PD of
the kth user.
For the uplink VLC systems, authors of [158], [159]
introduced a phase pre-distortion method to decrease the
uplink error rate performance in NOMA-VLC systems. Since
in [158], authors used the SIC to decode the signals, whereas
in [159], a joint detection method was used to improve the
system performance.
V. EN ER GY HA RVE STI NG I N VLC S YS TEM S
Much attention has recently been paid to energy-harvesting
techniques at user-equipment devices, either from exploit-
ing the surrounding environment, or by transferring wireless
power. Energy harvesting is the capability of converting the
radio frequency (RF) signals or light intensity into electrical
voltage/current. With the advent of the era of the IoT, the
demand for transferring the power and enabling IoT devices
to harvest energy using light or RF transmission is increas-
ing, especially in indoor applications where smart buildings,
health monitoring, and sensors devices applications become
abundant. Extensive work has been done to design, evaluate,
and optimize simultaneous wireless information and power
transfer in RF networks [160], [161]. Work on harvesting
the energy and transmitting the information using the light
is scarce, as it is still in its early stage.
Different from harvesting the energy in the RF networks,
the energy can be harvested using the DC component that is
transmitted along with the information signal to ensure the
non-negativity of signals. This DC component can be easily
separated from the modulated signal using capacitor and
goes to the energy harvesting circuit. Since the recent solar
cell panels can provide more than 40% conversion efficiency
[162], a new trend has emerged in the research community for
using solar cells at the receivers to detect information signal
and harvest energy.
Investigating the harvesting of energy in VLC systems has
been a timely topic of interest [69], [163]–[169]. A few papers
recently published proposed to investigate systems that use the
light to jointly transfer power, meet illumination requirements,
and transmit data. Authors of [69] experimentally harvested
the solar energy with mobile phone by equipping it with
16
(a) FoV=30o(b) FoV=40o
(c) FoV=50o(d) FoV=60o
Fig. 10. The distribution of the possible harvested energy over the area, with diferent user’s FoV, where the system model consists of 16 VLC APs.
a commercial solar panel in an indoor environment. They
showed that the devices directly exposed to the indoor light
could be charged to a satisfactory level. Fig 10 shows the
amount of the possible energy, which can be harvested by a
user, over the surface of an 8×8room with 16 VLC APs.
As observed Fig.10, the user’s FoV has an impact on the
harvested energy.
Authors of [163] investigated the concept of indoor optical
wireless power transfer to solar cells during darkness hours.
By using laser diodes and a solar panel, they measured
the power efficiency and showed an improvement over the
inductive power transfer systems, of approximately 2.7 times.
By using 42 laser diodes, they claimed to deliver 7.2 W of
optical power to a solar panel 30 m distant from the diodes.
Authors of [170] studied how much artificial indoor light
could deliver an amount of energy, using different types of
receiving cells.
In [164] and [165], a dual-hop hybrid VLC/RF communica-
tion system was studied as a means to reach out to the out-of-
the-coverage user. The authors showed that visible light could
be used, in the first hop, to transfer both data information and
energy to the relay. The relay, could then forward the data to
the destination, using the harvested energy. In [166], [167],
authors maximized the sum-rate utility of a VLC system
consisting of one AP and Kusers, subject to individual QoS
constraints. Li et al. [166] assumed that a user kvan receive
the information in their assigned time slot, and the power
within the time slots assigned to other users. In [167], on the
other hand, Abdelhady e al. proposed solving the problem by
allocating the optical intensity and time slots, using an upper
bound on the individual required harvested energy. Authors in
[168] characterized the outage performance of a hybrid VLC-
RF system, where the visible light is used for the downlink
to transfer the energy and data to the users, who then use the
harvested energy to transmit a RF signal in the uplink.
All the studies mentioned above use the alternating current
(AC) component for harvesting the energy, where the DC
component of the transmitted light is fixed and readily used
to harvest energy [34]. In [34], authors designed an optical
wireless receiver using a solar panel and enabled it to receive
17
information and harvest energy simultaneously. Because the
received current signal contains both DC-current and the AC-
current components, authors in [34] suggested to attenuate
the AC current, using an inductor to remove the ripples from
the DC-current that is forwarded to energy harvesting branch,
and to block the DC-current, using a capacitor, to obtain
only an AC-current in the communication circuit. Sandalidis
et al. [171] investigated the three functions of the LED
lamp, i.e. the illumination, communication, and the energy
harvesting, on a system consisting of a desk LED close to the
receiver equipped with a solar cell. The authors divided the
received optical power between the information signal and the
harvested energy, using a splitter.
Diamantoulakis et al. [169] studied the lightwave infor-
mation and power transfer for a system consisting of one
transmitter and one receiver. They provided the two following
protocols to maximize the harvested energy at the receiver,
under data rate constraint: 1) Splitting the time into two
portions, one dedicated to maximize the user’s SINR, and
the second assigned purely to maximize the harvested energy
by maximizing the DC component, 2) Optimization of the
DC bias, in phase 1, to maximize the harvested energy under
QoS constraints, with phase 2 assigned only to harvesting
the energy. However, optimizing the DC bias for the whole
time is more general, and there is no need to split the
time between harvesting the energy and transmitting the
data. In addition, the formulated problem would be more
challenging if there were multiple receivers, since the fairness,
in terms of data rate and harvested energy, is required. Hence,
authors in [172] studied the simultaneous information and
power transfer in MISO multi-user VLC system, where some
users are interested only in gathering information and the
others users interested in harvesting energy. The problem of
maximizing the total harvested energy under QoS constraints
was formulated as a non-convex problem, and hence, a special
iterative algorithm was used to solve the formulated problem.
VI. SE CUR IN G VLC S YS T EM S
Traditionally, the mission of the physical layer researchers
and designers is to provide a reliable signal transmission
to the relevant receivers, while the mission of securing and
protecting the transmitted information is usually assigned to
the upper layers of the networks [173]. However, with the
increasing demand for high data rate and the spreading of the
broadcast-nature networks, researchers have found with new
mechanisms to build secure communication networks, using
the physical layer.
The physical layer security (PLS) deals with how to exploit
the randomness of noise, channels, and different resources,
such as multi-antenna and cooperative nodes, to minimize the
information that can be extracted by the eavesdropper [174],
[175]. The secrecy capacity was introduced by Wyner [176] as
a metric to measure the security performance; it was defined
as the highest information rate that can be acquired at the
legitimate receiver, with having the eavesdropper completely
unaware of the transmitted information. To have a precise
quantification of the security, the eavesdroppers are assumed
to have unlimited knowledge of the network parameters and
have a sufficient computational capability.
In this section, we review the work that has been performed
on the PLS, in VLC networks. For the PLS in RF networks,
readers can refer to [177] and [178].
As mentioned in the Introduction Section VLC networks
are more secure than RF networks and less susceptible to
signal interception because of the small coverage provided by
LEDs, and because they work properly only in the presence of
the LoS components. However, the security in VLC networks
is still a problematic issue, specifically when transmitted
information can be accessed by multiple users, for instance
in public areas, meeting rooms, laboratories, and libraries.
This means that potential eavesdroppers may be able to gather
confidential messages [179].
Many papers reported in the literature address the PLS
in VLC networks, and different techniques were proposed
to evaluate and improve the secure communications. The
proposed techniques generally depend on different network
parameters, such as the availability of the eavesdroppers’ CSI,
the number of LEDs equipped with transmitters, the number
of the legitimate users and eavesdroppers. These techniques
use a zero-forcing precoding approach that eliminates the
transmitted information to eavesdroppers; they may use ar-
tificial noise or jamming aimed at confusing eavesdroppers,
they build a protected zones using angle diversity transmitters,
optimizing the input distribution, characterizing the security
in VLC systems using the stochastic geometry. The artificial
noise and signal modification are possible in real-world VLC
applications, but the MAC layer cannot provide sufficient
protection against eavesdropping [180]. To our knowledge, to
this day, a closed-form expression of secrecy capacity in the
VLC networks has not been derived. All the studies reported
in the literature derive a lower and upper bounds for the
secrecy capacity and for the secrecy outage probability.
Unlike RF channels, the optical intensity must be consid-
ered for illumination requirements. Hence, in VLC channels,
the optical intensity is a constraint that is directly proportional
to the electrical signal amplitude, not to the squared signal as
in RF channels.
In [181], Ayman Mostafa and Lutz Lampe started investi-
gating the PLS in MISO-VLC channel with one eavesdropper
and one authorized user. When the CSI of the eavesdropper is
available, the zero-forcing precoding approach is applied, but
if the CSI is unknown, the transmitter divides its own optical
power into two portions, a one used for the information-
bearing signal and the other used for emitting jamming
signals to confuse eavesdroppers without affecting legitimate
receiver. It is important to note that the zero-forcing preceding
approach can be implemented when the number of LEDs
transmitters is larger than the number of eavesdroppers. Simi-
larly, the jamming signals can be eliminated, at the legitimate
users, when the number of users is lower than the number of
LEDs jammers.
Instead of dividing the power between information and
jamming signals, Ayman Mostafa and Lutz Lampe [182]
assigned one LED for transmitting data and assigned all the
others to transmit jamming signals. To eliminate the jamming
18
signal at the legitimate receiver, different LED jammers
coordinate their transmitted signals to be eliminated at the
legitimate receiver. In [183], authors devoted some LEDs to
transmit the information and keeping the others for emitting
an intrusion signal and shape a protected zone where potential
eavesdroppers receive a degraded SNR.
In [72], authors presented a formulation for the upper and
lower bounds of the secrecy rate, under amplitude constraint
for the SISO-VLC system; they then generalized the capacity
bounds to the MISO systems. They also solved two opti-
mization problems to find the optimal weighting vector at
the light source transmitters, when CSI of the eavesdropper
is known and when the transmitter has a limited informa-
tion about the location of the eavesdropper. For amplitude-
constrained wiretap channels, the secrecy rate maximization
problem was formulated as a non-convex optimization prob-
lem when the CSI of the eavesdropper is known [71]. The
authors transformed the nonconvex problem into a solvable
quasiconvex line search algorithm that provides a slightly
better performance than the simpler zero-forcing algorithm
proposed in [72]. When the CSI of the legitimate user is
limited, and the CSI of the eavesdropper is not available,
they estimated the channel of the eavesdropper by deriving
the uncertainty sets that reflect the inaccurate knowledge
of the eavesdropper location, orientation, LEDs half angle,
and non-LoS components. In [184], a joint beamforming and
jamming approach was proposed to improve the PLS for one
legitimate user with multiple eavesdroppers in the MISO-VLC
system. Two vectors were optimized jointly: the beamforming
vector that is multiplied by the legitimate information, and the
jamming precoding vector that is multiplied by the jamming
signal, in order to maximize the SNR of the legitimate user,
under SNR constraints for both perfect and imperfect CSIs at
the transmitter.
In [185] and [186], V. Pham and T. Pham investigated
ways of transmitting confidential messages to two different
legitimate users, in a MISO-VLC system, while keeping the
messages confidential from each other (as well as the eaves-
dropper). The zero-forcing precoding approach was applied
to guarantee the confidentiality among users. When the trans-
mitter wants to transmit Kconfidential messages to Kusers,
a new precoding scheme was proposed in [187] to maximize
the secrecy sum rate, in a multi-user MISO VLC system. This
precoding scheme is based on finding the beamforming matrix
from the eigenvectors associated with the largest eigenvalues
of the different KMISO-VLC channels. In [188], authors
studied the PLS in a system consisting of massive low-
intensity LEDs, distributed uniformly in the ceiling, multiple
legitimate receivers, and multiple eavesdroppers with limited
CSI. After defining the insecurity zone around the legitimate
receivers, they designed the beamformer so that it can direct
its main lobes towards the defined zones and minimize the
information rate outside the defined insecurity zone.
Because of the peak amplitude constraint on the input
distribution, the Gaussian input distribution is not the optimal
option. Therefore, different input distributions, under intensity
constraints, were proposed to improve the secrecy perfor-
mance in VLC networks [182], [188]–[191]. Specifically,
authors of [182] used the uniform input distribution. Authors
of [189] improved the work of [188] by using the truncated
Gaussian inputs instead of the uniform input distributions for
both the data and the artificial noise signal. In [190], authors
used the a truncated generalized normal distribution for the
MISO-VLC Gaussian channel. It was shown that the truncated
generalized normal distribution input performs better than the
uniform and the Gaussian distribution input [190]. For the
same system model and same input distribution as in [190],
Aefaoui et al. [191] found a closed-form for the optimal
beamforming, for a known location of the eavesdropper.
Both the truncated Gaussian distribution and the truncated
generalized normal distribution provide potential to improve
the secure communications by optimizing the parameters that
cannot be optimized in the uniform distribution.
When the VLC system contains multiple eavesdroppers
distributed randomly in the considered area, the stochastic ge-
ometry can be used to characterize the system and to provide
analytical expressions of the secrecy outage probability and
of the average secrecy rate. In [192], authors studied the PLS
in one VLC cell consisting of group of LED lamps located
in the center of the ceiling, with one receiver and multiple
eavesdroppers. The eavesdroppers were randomly distributed
based on the Poisson point process. They provided closed-
form analytical expressions for the secrecy outage probability
and the average secrecy rate, using the stochastic geometry
method under the assumption that the floor area is a circle.
In [193], Cho et al. proposed a LED selection scheme to
improve the secrecy outage probability, when the eavesdrop-
pers are randomly located in the selected area, and their CSI
are unknown to the transmitters. Similarly to what was done
in [192], they used the Poisson point process to model the
randomness of the location of the eavesdroppers. The same
authors used the proposed eavesdropper location modeling to
analyze the performance of the MISO-VLC system model
and proposed a beamforming solution [194]. To find the
optimal beamforming vector, they formulated the following
optimization problems: minimizing the average eavesdrop-
per SNR under a given SNR constraint to the legitimate
receiver, maximizing the authorized user SNR under the
average eavesdropper SNR constraint, and they optimized
the same problems for the rate, instead of the SNR. In all
the formulated problems, closed-form expression were pro-
vided for the beamforming vector solution. Because the VLC
LEDs provide a very limited coverage area, the beamforming
solution for the secrecy maximization can be approximated
to be a LED selection, suggesting the selection of the AP
closest to the legitimate user; secrecy rate would then be
improved, as the distance between the eavesdropper and the
legitimate user increased [194]. The same authors studied the
PLS in a VLC system when multiple eavesdroppers combine
their observations using maximum ratio combining (MRC)
approach, to maximize their information rate and degrade the
secrecy performance [195]. The authors used the stochastic
geometry to anticipate the secure communication under a pre-
defined eavesdroppers’ density.
In [196], Yin and Haas considered the unique properties of
the VLC channel and the VLC network’s layout to fully char-
19
acterize the secrecy outage probability and the ergodic secrecy
rate in multiuser (multiple legitimate users and multiple eaves-
droppers), multi-cell VLC systems. The APs in the ceiling
were modeled using a two-dimensional homogeneous Poisson
point process, under the assumption that some of the LEDs are
not working as VLC APs (they provide only the illumination),
whereas both users and the eavesdroppers are modeled using
another independent two-dimensional homogenous Poisson
point process at their plane. They investigated the secrecy
outage probability and the average secrecy capacity for three
scenarios: 1) the legitimate user is served by the nearest AP,
2) the legitimate user is served by cooperating APs, and 3)
the legitimate user is located in the protected zone around the
AP, where the eavesdropper is not allowed to be.
Because all the aforementioned work ignored the fact that
an eavesdropper might exploit the reflected light to obtain
unauthorized information, authors of [197] considered the
effect of the reflected path and the channel correlation in
a MISO-VLC network to propose an eavesdropping-resilient
framework for VLC security. Authors of [198] showed that a
small gap under the door, kay holes, or the window could be
sufficient sources for eavesdropping. They also showed that
eavesdroppers could gain information from reflected lights
from the walls. Cho et al. [199] showed how the non-LOS or
the reflected light would affect the secrecy outage probability
in a system model consisting of multiple LED transmitters,
one legitimate user, and multiple randomly distributed eaves-
droppers. They showed that the secrecy outage probability
depends on the position of the legitimate user, the design of
the LED transmitters, and the location of the eavesdroppers
with respect to the reflecting points.
For MIMO-VLC systems, in [200], a MIMO system was
used to establish a secure communication zone by minimizing
the BER in the protected zone and maximize it every-
where else. In [201], authors studied the PLS in a MIMO-
VLC system model consisting of one transmitter equipped
with multiple LEDs, one multiple-PD eavesdropper, and one
multiple-PD authorized user. In both cases (the CSI of the
eavesdropper is known or unknown), they derived the opti-
mal covariance matrix and the optimal signaling scheme for
achievable secrecy rate maximization, then derived an upper
bound for the proposed system secrecy capacity. Authors of
[202] improved the PLS in VLC systems by applying angle
diversity transmitters that are capable of transmitting data
in narrow beams, effectively minimizing the leakage of the
information. By comparing different types of optical network
deployments, they concluded that the hexagonal deployment
is the best in terms of secure communications, whereas the
Poisson point process deployment is the worst. Wang et al.
[203] proposed LED pattern selection scheme to improve the
secrecy performance of the generalized space-shift keying
VLC systems.
For the hybrid VLC/RF networks, authors of [204] studied
the PLS when the network consisted of one RF AP, one
VLC AP, one legitimate receiver, and one eavesdropper. Both
the eavesdropper and the receiver have the multi-homing
capability (i.e. they can aggregate the information from both
networks). The RF AP and the VLC AP are equipped with
multiple antennas and multiple LEDs, respectively. By opti-
mizing the beamforming vectors and the transmit powers at
both the VLC and RF APs, they formulated their problem as
minimization of the total consumed power under having the
aggregated information rate at the eavesdropper nulled and
having the information rate at the receiver above a predefined
threshold. In [205] and [206], authors derived the exact and
the symptomatic secrecy outage probability for the uplink
transmission in a system consisting of one legitimate receiver,
one eavesdropper and two RF VLC APs. The downlink
was implemented by the VLC AP, where the receiver and
the eavesdropper harvest the energy from the light intensity.
Then, during the receiver transmission of the information in
the RF link with a finite energy storage, the eavesdropper
tried to acquire the transmitted information. They concluded
that increasing the circle area or decreasing the LED height
improves the secrecy outage probability.
In [207], Mukherjee investigated the lower and upper
bounds of the secret-key capacities in SISO VLC system,
and analyzed the secret-key transmission scenario in MISO
VLC system. Al-Moliki et al. proposed a security protocol
that generates confidential keys dynamically from the bipolar
real OFDM samples to encode each signal frame by using
the cyclic prefix samples placed in the small channel impact
area [208], [209]. The same authors upgraded their proposed
protocol in [208] to combat the known-plain text attacks and
chosen-plaintext attacks by applying logistic chaotic maps to
the system [210].
A chaotic channel determined subcarrier shifting (CDSS)
scheme with pre-equalization were presented in [211] to im-
prove the PLS in DCO-OFDM VLC system. For secure image
transmitting in VLC channel, chaos scrambling schemes were
proposed in [212] for discrete-Foruire transform precoded
OFDM-based, and in [213] for discrete cosine transform
precoded OFDM-based systems.
VII. S UMM ARY A ND OPE N RESE AR CH PROB LEM S
In this paper, we reviewed the optimization techniques
that proposed to improve the performance of VLC networks
and minimize the effects of the VLC limitations. The review
covered the different types of VLC networks: hybrid VLC/RF
networks, VLC standalone networks with APs’ coordination,
NOMA-VLC networks, VLC networks that contain energy
harvesting users, and VLC networks that contain eavesdrop-
pers.
Based on the existing work in the literature, in this section,
we outline different challenges and open research problems
that need to be considered and investigated in the future work.
A. NOMA-VLC Networks
Despite all the aforementioned work on NOMA-VLC sys-
tems, numerous challenges remain, and important topics in
this area of research are still to be investigated. Below is a
list of some key open problems in NOMA-VLC networks:
•Hybrid NOMA-VLC systems: the hybrid NOMA is to
group the users into multiple clusters, and assign to
each cluster a designated resource block, following the
20
TABLE IV
TEC HN IQ UE S US E D FO R P LS
State Appropriate techniques
Full CSI is avail-
able •Zero-Forcing precoding;
•design the beamforming matrix from
the channel matrix eigenvectors;
•LED selection
Location of the
eavesdropper is
available
•build a protected zone where eaves-
dropper cannot be located;
•jam a defined zone where the eaves-
dropper can be located;
•estimate the eavesdroppers’ channel
and use the same techniques when
CSI is available;
•use the angle diversity transmitters;
LED selection; APs arrangement
No information
available about
eavesdroppers
•characterization of the secrecy perfor-
mance using the stochastic geometry
tool;
•divide the power between jamming
and beamforming vectors;
•devote some LEDs for jamming;
•LEDs selection;
•APs arrangement
NOMA principle in each cluster. To our knowledge,
the hybrid NOMA has not been studied yet in VLC
systems. The rational for using the a hybrid NOMA is
its ability to reduce the system’s complexity. Indeed,
having a large number of users in the VLC system,
and assigning them to the same resource block can be
problematic, since the user with the best channel must
decode all the signals of all the users before decoding
his/her own signal, creating delays the decoding and
resulting in high complexity. Hybrid NOMA systems
have been proposed in RF networks to take into account
both the system performance and complexity. Therefore,
we propose to study the hybrid NOMA-VLC system
by finding the optimal user grouping, allocating the
power to each group, the power inside each group, or
grouping the users and allocating the power jointly, for
sum-rate maximization purposes. This system can be
extended to be a multi-cell system, in which the user-
to-AP association problem also exists and should be
considered. Hence, the problem would be then a two
layer user grouping with power allocation.
•NOMA with different QoS requirements: In real life,
not all users require the same amount of data rate. For
example, some of them may stream videos, whereas
others are texting or exploring websites. Also some
receivers can be IoT devices that need low data rates.
Allocating power, in the most effective way, to users with
different needs still remain a challenge, and obtaining the
required data rate for each user, even when some weak
users (users with poor channels) require higher data.
•Cooperative NOMA-VLC: cooperative NOMA has been
proposed in RF networks to exploit the redundant infor-
mation in NOMA systems, and to compensate the weak
user suffering from co-channel interference by increasing
his data rate. The cooperative NOMA can be used among
VLC users or by using relays. We are interested in the
cooperation among users, where the strong users that
encode the signals of the weak users can forward these
coded signals to the intended users. When assuming a
VLC system with two users, under the assumption that
all users are equipped with a multi-homing mechanism
(i.e. they can gather information from VLC and RF
networks simultaneously), the strong user first decodes
the signal of the weak user, then forwards it to the weak
user using WiFi or Bluetooth techniques. Weak user can
then combine the RF and VLC signals, using combining
techniques.
•Modulation and coding for NOMA-VLC system: several
papers studied the modulation and coding schemes in
NOMA RF networks [214], [215]. As the modulation and
coding in VLC networks is different (based on IM/DD),
investigating the modulation and coding schemes in
NOMA-VLC systems would be worthy for practical
implementation.
•NOMA in coordinated multi-point (CoMP) VLC net-
works: CoMP VLC system means that multiple APs
are cooperating to transmit the data for the users. The
cooperation is for mitigating the inter-cell interference
and enhancing the received data rate by optimizing the
precoding matrix. Assume a VLC system consisting of N
APs and Musers, where M > N , the questions should
be raised is that how the users should be sorted from
the strongest user to the weakest user?, how should the
users be grouped to be served by the cooperating APs?,
and how should the power be allocated. Combining the
two techniques NOMA and CoMP surly leads to having
a significant performance improvement in VLC systems.
•Hybrid SDMA and NOMA: SDMA in VLC can be
implemented using angle diversity transmitters that can
generate several parallel narrow light beams directed to
different directions using different LEDs. The goal of
using SDMA is to mitigate inter-cell interference in VLC
networks by directing the light to intended users and
decreasing the overlap areas. However, some LEDs can
be directed to non users, some to one user, and others to
multiple users. The LEDs that are assigned or directed
to serve multiple users can use the NOMA as a multiple
access and to maximize the data rate. SDAM is used to
mitigate or eliminate inter-cell interference, and NOMA
is used to mitigate the intra-cell interference using SIC.
By combining both of them, the system performance is
significantly improved, in terms of data rate and system’s
fairness. Fig. 11 shows a system model in which SDMA
and NOMA can coexist in VLC systems, where the
NOMA can be used in LEDs that serve more than one
user.
B. Harvesting the Energy in VLC Systems
Despite all the aforementioned work in Section V, there are
several remaining challenges associated with the transfer of
information and power, using a light wave. Here are below a
21
Fig. 11. The proposed hybrid SDMA/NOMA system.
few key issues that need to be investigated and optimized for
obtaining the most efficient power and information transfer
systems.
•Simultaneous light-wave for information illumination
and power transfer: Several studies investigated VLC
systems in which both energy and information could be
transferred to users. However, achieving both functions
in VLC networks might violate the illumination require-
ments. We therefore propose to study the three functions
of the light simultaneously by formulating optimization
problems that allocate the DC bias, the available power,
and the available resources.
•Joint DC-bias and resource allocation for sum rate with
the presence of energy-harvesting users: allocating both
the DC bias and the available resources at the VLC
APs leads to a significant improvement of the VLC
performance under simultaneous lightwave information
and power transfer (SLIPT). An effective allocation of
resources (to the users) provides opportunities to preserve
high energy that can be harvested by users.
•As proposed in the NOMA-VLC Section, a cooperative
NOMA can be implemented in VLC systems; however,
the strong user may do not want to consume some of
his/her power by forwarding the signal to the weak user.
We therefore suggest investigating ways for the strong
user to harvest the energy from the light intensity, in the
first phase, and then use it to forward the weak user’s
signal. This means that the transmitter should optimize
the DC bias and the information power to maximize the
sum rate and guarantee acceptable fairness.
•Optimizing the MISO-VLC network with NOMA: when
the system consists of multiple VLC APs cooperating to
transmit the information and power for multiple users,
if the number of users is larger than the number of
APs, the key issue that should be addressed is whether
OMA or NOMA is the best system for scheduling
users and harvesting the energy. As previously reported
in the literature, NOMA can provide better data rates
than OMA. In other words, NOMA can achieve the
required users’ data rate with a small amount of transmit
power (information power), which allow the DC bias to
increase, resulting in increasing the harvested energy.
•Placing the energy harvesting users: suppose that a
VLC system consisting of multiple information users
(users interested only in gathering the information), and
IoT devices that work only in uplink (like sensors)
and interested only in harvesting the energy (energy
harvesting (EH) users). Optimizing the positions of the
EH users in order to maximize the harvested energy
and to achieve the required QoS at the information
users is crucial in VLC SLIPT systems. Yet, it remains
challenging. Therefore, there is needed to investigate
ways of implementing and simplifying this task.
C. Securing VLC Networks
Despite the significant number of studies already per-
formed, there are still some important issues to tackle and still
many challenges for researchers to overcome in the future. A
few of them are highlighted below, together with potential
solutions that may improve the PLS in VLC systems:
•How to optimize the beamforming vector in MISO-VLS
systems when an active and passive eavesdropper exists.
The common approach for the active eavesdropper is the
zero-forcing preacoding approach, the common approach
for the passive eavesdroppers is the design of protected
zones, using an artificial noise or by steering the beam-
forming lobes. This raises an important question: what
would the appropriate method be to improve the security,
if the transmitters know the CSI of some eavesdroppers
and they do not know the CSI of the others, or have a
limited information about the eavesdropper (e.g. location
only).
•PLS in NOMA-VLC system: Several recent papers in-
vestigated the PLS in NOMA RF networks for different
system models [216], [217]. To this day, no paper has
studied the PLS in NOMA-VLC systems. Because of the
unique properties of VLC systems, the PLS in NOMA-
VLC systems is required to be investigated, evaluated,
and optimized.
•User-centric cell formation based in the presence of
eavesdroppers: As shown above, the user-centric cell
formation is an appropriate scenario when the number
of users is much smaller than the APs. Suppose that
the network contains some eavesdroppers (whether their
CSI are available or not), the questions raised are: 1)
how should the users be clustered? 2) how should the
APs be associated to the clustered users? 3) which
APs should participate in communication, and which
should be switched off? 4) could the switched off APs
help enhance the secrecy sum-rate in emitting jamming
signals?
All the above questions indicate that the joint PLS and
user-centric design should be investigated and optimized
together.
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Mohanad Obeed (S’17) received the B.Eng. degree
in computer and communication engineering from
Taiz University, Taiz, Yemen, in 2008, the M.Sc.
degree in electrical engineering from King Fahd
University of Petroleum and Minerals (KFUPM),
Dhahran, Saudi Arabia, in 2016.
He is currently pursuing the Ph.D. degree at
KFUPM, Dhahran, Saudi Arabia. His research in-
terests include visible light communications, coop-
erative communication, resource allocation, convex
optimization, physical layer security, and energy
harvesting.
Anas M. Salhab (S’11-M’14-SM’17) received the
B.Sc. degree in electrical engineering from Pales-
tine Polytechnic University, Hebron, Palestine, in
2004, the M.Sc. degree in electrical engineering
from Jordan University of Science and Technology,
Irbid, Jordan, in 2007, and the Ph.D. degree from
King Fahd University of Petroleum and Minerals
(KFUPM), Dhahran, Saudi Arabia, in 2013. From
2013 to 2014, he was a Postdoctoral Fellow with the
Electrical Engineering Department, KFUPM. He is
currently an Assistant Professor and the Assistant
Director of the Science and Technology Unit with the Deanship of Scientific
Research, KFUPM. His research interest spans special topics in modeling
and performance analysis of wireless communication systems, including
cooperative relay networks, cognitive radio relay networks, free space optical
networks, visible light communications, and co-channel interference. He was
selected as an Exemplary Reviewer by the IEEE WIRELESS COMMUNICA-
TIONS LETTERS for his reviewing service in 2014. Recently, he received
the KFUPM Best Research Project Award as a Co-investigator among the
projects in 2013/2014 and 2014/2015.
27
Salam A. Zummo (M’00-SM’08) received the
B.Sc. and M.Sc. degrees in electrical engineering
from the King Fahd University of Petroleum and
Minerals (KFUPM), Dhahran, Saudi Arabia, in
1998 and 1999, respectively, and the Ph.D. de-
gree from the University of Michigan, Ann Arbor,
USA, in 2003. He is currently a Professor with the
Electrical Engineering Department, KFUPM. Prof.
Zummo has six issued U.S. patents and authored
over 100 papers in reputable journals and confer-
ence proceedings. His research interests are in the
area of wireless communications, including cooperative diversity, cognitive
radio, multiuser diversity, scheduling, MIMO systems, error control coding,
multihop networks, and interference modeling and analysis in wireless sys-
tems. He received the Saudi Ambassador Award for early Ph.D. completion
in 2003, and the British Council/BAE Research Fellowship Awards in 2004
and 2006. He also received the KFUPM Excellence in Research Award from
2011 to 2012.
Mohamed-Slim Alouini (S’94, M’98, SM’03,
F’09) was born in Tunis, Tunisia. He received the
Ph.D. degree in Electrical Engineering from the Cal-
ifornia Institute of Technology (Caltech), Pasadena,
CA, USA, in 1998. He served as a faculty member
in the University of Minnesota, Minneapolis, MN,
USA, then in the Texas A&M University at Qatar,
Education City, Doha, Qatar before joining King
Abdullah University of Science and Technology
(KAUST), Thuwal, Makkah Province, Saudi Arabia
as a Professor of Electrical Engineering in 2009.
His current research interests include the modeling, design, and performance
analysis of wireless communication systems.
