# Retrofitting FSO Systems in Existing RF Infrastructure: A Non-Zero Sum Game
Technology

Abderrahmen Trichili, Member IEEE, Amr Ragheb, Member, IEEE, Dmitrii
Briantcev, Student Member, IEEE, Maged A. Esmail, Member, IEEE, Majid
Altamimi, Member, IEEE, Islam Ashry, Senior Member, IEEE, Boon S. Ooi, Senior
Member, IEEE, Saleh Alshebeili, Mohamed-Slim Alouini, Fellow, IEEE A.
Trichili, D. Briantcev, I. Ashry, B. S. Ooi, and M.-S Alouini are with the
Computer, Electrical and Mathematical Sciences $\&$ Engineering in King
Abdullah University of Science and Technology. Email:
{abderrahmen.trichili,dmitrii.briantcev,islam.ashry,boon.ooi,slim.alouini}@
kaust.edu.sa.
A. Ragheb, M. Altamimi, S. Alshebeili are with King Saud University. Email:
<EMAIL_ADDRESS>
M. A. Esmail is with Prince Sultan University. Email<EMAIL_ADDRESS>
###### Abstract

Progress in optical wireless communication (OWC) has unleashed the potential
to transmit data in an ultra-fast manner without incurring large investments
and bulk infrastructure. OWC includes wireless data transmissions in three
optical sub-bands; ultraviolet, visible, and infrared. This paper discusses
installing infrared OWC, known as free space optics (FSO), systems on top of
installed radio frequency (RF) networks for outdoor applications to benefit
from the reliability of RF links and the unlicensed broad optical spectrum,
and the large data rates carried by laser beams propagating in free space. We
equally review commercially available solutions and the hardware requirements
for RF and FSO technology co-existence. The potential of hybrid RF/FSO for
space communication is further discussed. Finally, open problems and future
research directions are presented.

###### Index Terms:

Free space optics, RF systems, heterogeneous links, switching, diversity,
atmospheric turbulence, propagation effects, digital divide, 6G and beyond,
satellite and deep space communication

##  I Introduction

Internet and data traffic drastically increased over the last few years with
the emergence of new online applications such as virtual reality and ultra-
high-definition video streaming. Satisfying the demand of the bandwidth-hungry
world requires reliable connectivity. Free space optics (FSO) is a license-
free technology that connects two communicating terminals using narrow
infrared (IR) light beams and has received massive attention over the last few
years. FSO can be a solution to the so-called ‘last mile’ and ‘last meter’
connectivity problems and can be used when optical fiber installation is
scarce (See Fig. 1). FSO has also been proposed for 5G backhauling [1, 2] and
expected to play a significant role to build next-generation 6G networks [3,
4]. It has been shown that FSO can benefit from spatial mode multiplexing to
push the communication capacity by using the spatial structure of the light
[5] and through other various degrees of freedom of light such as the
frequency [6] and polarization [7]. Due to the spectrum scarcity of radio
frequency (RF) technology, FSO has been widely proposed as an alternative to
existing RF links. Such an idea attracted several negative arguments in
particular because of FSO signals’ sensitivity to propagation effects. But
what if FSO is used as a complementary technology to RF? For instance, RF and
FSO links are affected differently with weather conditions [8]. FSO links, for
example, are sensitive to fog but not to rain, while RF links are severally
degraded by rain but resilient to fog. Therefore, RF can be used when the FSO
is not available, and FSO can be used when the RF is not available.
Furthermore, FSO systems are easily integrable and can be up and running over
a short period [9]. More importantly, installing FSO systems does not incur
additional civil engineering costs and can be installed on the well-
established RF infrastructure. Indeed, RF and FSO technologies’ complementary
behavior has led to various proposals of hybrid RF/FSO implementations [10].
In this context, we focus on the various hybrid RF/FSO links. In particular,
we present the different RF/FSO link switching mechanisms, such as soft
switching and hard switching. The scenario when the RF and FSO systems
transmit simultaneously is also reviewed. The practicality of each of these
approaches and the hardware challenges of building heterogeneous RF/FSO
systems are discussed. Commercially available RF/FSO solutions are equally
reviewed. The potentials of the co-existence of RF and FSO technologies for
near-Earth and deep space applications are also presented.

###  I-A Related Reviews

Free space optics has been a topic of interest of many published reviews [11,
12, 13, 14]. From a communication theory perspective, authors of [11] reviewed
FSO communication and covered the various aspects of FSO links, including
channel modeling, modulation techniques, and transceivers’ structures. Hybrid
RF/FSO systems were briefly discussed, illustrating their potential in
combating propagation effects. Ghassemlooy et al. highlighted the potential of
optical wireless communication systems to complement existing RF networks
[12]. Authors of [13] conducted an extensive survey on optical communication
in space and the various challenges and corresponding mitigation strategies.
In particular, RF/FSO was presented as a potential technique to mitigate
atmospheric turbulence effects. Authors of [15] discussed hybrid optical
networks; in particular, they overviewed RF/FSO links and their potential to
achieve high data rate reliable wireless transmissions. A broad overview of
many of the essential topics required to design and develop next-generation
FSO systems was provided in [14]. Retrofitting FSO in existing RF installation
was proposed to increase the data rates, and communication reliability of
wireless backhauls [14]. Integrating wireless fidelity (WiFi) and visible
light communication (VLC), also known as light fidelity (LiFi), for indoor
environments was addressed in [16].

###  I-B Contributions

Here, we provide a comprehensive review on integrating IR FSO systems on
existing RF infrastructures. We start by giving a brief comparison between RF
and FSO to highlight the complementarity of both technologies. We shed light
on the various switching techniques between FSO and RF in a hybrid system.
Among these system configurations, we review the contributions in the
following approaches:

  * •

Soft switching

  * •

Hard switching

  * •

Machine-learning-based switching

  * •

Diversity scheme

We also compare them in terms of hardware complexity. The specifications of
RF/FSO systems available in the market, field trials, and seminal deployments
are covered. Furthermore, the contribution of hybrid RF/FSO for space and
near-Earth applications is presented. Issues mainly related to the cost are
also discussed. A set of insightful future research directions is finally
proposed.

###  I-C Paper Organization

The remainder of this paper is organized as follows. Section II provides a
comparison between FSO and RF technologies mainly in terms of licensing,
safety, system foot-print, and possible propagation effects. Section III is
dedicated to the mixed RF/FSO links. Section IV is devoted to the various
configurations of hybrid RF/FSO links. Section V describes commercially
available RF/FSO solutions and the main field demonstrations. The potentials
of hybrid RF/FSO systems for satellite and deep space applications are
discussed in Section VI. Open issues and potentials research directions from
the authors’ perspective are provided on VII. Section VIII concludes the
paper.

Figure 1: Illustration of potential outdoor FSO use cases ranging from point-
to-point terrestrial communication to satellite-to satellite and satellite-to
ground connections. ©King Abdullah University of Science and Technology.

##  II FSO vs RF

FSO and RF communications, each of which has many advantages and constraints.
For example, dust and fog drastically affect FSO, while rain severely affects
RF. RF beams tend to diverge higher than FSO ones; however, FSO signals are
more sensitive to pointing errors. This section discusses the advantages and
disadvantages of FSO and RF systems in terms of bandwidth, footprint, safety,
secrecy, and resilience to channel propagation effects. Such discussion will
motivate the integration of both technologies to create robust hybrid systems.

###  II-A Unlicensed Spectrum and Available Bandwidth

Currently, RF is the technology of choice for wireless communication. However,
radio communication requires paying for licenses to use a few bands of the
strictly regulated spectrum. FSO, on the other hand, does not suffer from such
a problem since the spectrum of light is unlicensed. In terms of bandwidth,
FSO has a vast bandwidth in the range of a few hundred THz, while RF has a
much smaller available bandwidth. RF frequencies below 10 GHz are almost
exhausted because of their favorable communication properties, while moving to
higher frequencies comes with a higher cost, more complexity, and propagation
challenges. Current RF technology supports data rates in the range of
Mbps/Gbps. However, state-of-the-art FSO intensity modulation/direct detection
(IM/DD) technology can support Gbps data rates and reach beyond Tbps when
coherent optical systems are used [14]. We note that in an IM/DD system, the
intensity of a laser is modulated using an RF signal. The modulated optical
signal is detected using a photodetector at the receiver. In contrast, a
coherent system involves using the intensity and phase of an optical carrier,
which requires continuous phase tracking utilizing a device known as a local
oscillator. This drive the system complexity and cost higher.
High-speed FSO systems are possible using all-optical networks as light
signals coming from an optical fiber can be directed to an FSO channel and
vice versa without the need for intermediate electrical to optical and optical
to electrical conversion devices that limit the bandwidth. Moreover, this
arrangement contributes to reducing the end-to-end system latency.

###  II-B System Footprint and Geometrical Loss

The desired beamwidth of the received signal after the propagation over a
wireless channel primarily defines the receiving terminal size. A narrow
beamwidth reduces the amount of power loss and terminal size. The beamwidth,
at a position of the receiver $z_{R{X}}$ along the propagation is proportional
to the wavelength, $\lambda$, and is inversely proportional to the transmitter
aperture diameter $D_{T}$, that is:

$\omega(z_{RX})\sim\frac{\lambda}{D_{T}}.$ (1)

With a fixed $D_{T}$, a transition from RF to FSO will significantly reduce
the beamwidth $\omega$. For the sake of comparison, let’s assume an RF
frequency of 50 GHz for a possible 5G system with a corresponding
$\lambda_{1}\approx 6\cdot 10^{-3}\text{ [m]}$. Also, consider an infrared
wavelength used for an FSO system with $\lambda_{2}=1550\text{ [nm]}=1.55\cdot
10^{-6}\text{ [m]}$. Even in this, favorable for the RF system comparison
scenario, a relative reduction of a spot size coming from RF to FSO will be
equal to $\frac{\lambda_{1}}{\lambda_{2}}\approx 4\cdot 10^{3}$. This
improvement in the beam waist of more than 3 orders of magnitude reduces the
transmitter aperture diameter $D_{T}$ for a reduced footprint of the FSO
system compared to RF. The reduction in the transmitter aperture diameter
reduces the signal’s power loss at the receiver due to the geometric path
loss. The small beam sizes make FSO preferable for backhaul applications,
while RF is preferred for access networks.

###  II-C Safety and Secrecy

FSO has fewer restrictions than the RF technology in terms of power levels and
EMF (electromagnetic field) radiation risks because of its point-to-point
topology and narrow beam nature [17]. Similarly, for the same reasons, FSO’s
physical layer security (PLS) is higher as it is not easy to intercept
collimated IR signals using power meters and spectrum analyzers. In addition
to being invisible to the naked eye, some infrared FSO signals are also
invisible to standard photography, or state-of-the-art video cameras [18]. FSO
signals cannot penetrate opaque objects along the propagation path, such as
walls; therefore, they are secure from hidden adversaries. On the contrary, RF
is susceptible to eavesdropping issues. It has also been shown that FSO links
can contribute to RF’s physical security enhancement when installed parallel
to an RF link [19]. The advanced security of wireless IR optical beams comes
with a cost that FSO, when compared with RF, is restricted to a point-to-point
network configuration, limiting the coverage and reach of such a technology.
Note that in some situations, FSO signals can be intercepted, notably when an
eavesdropper is placed close to the legitimate transmitter [20]. In practice,
this requires some intruder prevention practices, such as installing a shield
behind the FSO receiver to block the undetected light in situations when the
incident beam area is larger than the receiving aperture, as proposed in [18]
(for a commercial FSO product).

###  II-D Channel Propagation Effects

Even though the fundamental principle of both FSO and RF technologies is based
on the transmission of electromagnetic waves through the atmosphere, the
wavelength and the wave interaction with the outdoor environment vary
drastically between the two technologies. Overall, FSO is more sensitive to
propagation effects, as will be discussed in this section. The possible
propagation effects that may encounter FSO signals are illustrated in Fig. 2.

Figure 2: Possible propagation effects on FSO signals transmitted through the
atmosphere.

While propagating through the atmosphere, optical signals are subject to
attenuation. Attenuation originates from two main effects; absorption and
scattering. Absorption is caused by the interaction of waves with molecular
and aerosol particles in the atmosphere. However, IR FSO wavelengths are
chosen to match atmospheric transmission windows where the molecular and
aerosol absorption is minimum. Therefore, scattering, experienced by IR light
waves in the atmosphere, is the major factor for attenuating the received
signal. There are two main scattering types when propagating through the
atmosphere; Rayleigh scattering [21] and Mie scattering. As illustrated in
Fig. 3, Rayleigh scattering is a diffused all-directions scattering, while Mie
scattering is a forward scattering.

Figure 3: An illustration of Rayleigh and Mie scattering types. Rayleigh is an
all-direction scattering, while Mie scattering tends to be in the forward
direction.

Rayleigh scattering occurs when the particles in the atmosphere are much
smaller than the wavelength. Mie scattering is, conversely, the scattering of
an EM wave on particles of comparable or larger size than the wavelength. RF
waves with wavelengths of $\sim 10^{-2}$ m and larger experiences almost
exclusively Rayleigh scattering, whereas FSO with typical wavelengths of $\sim
10^{-6}$ m experiences mainly Mie scattering. Fog is the primary source of Mie
scattering. Other weather conditions such as rain, snow, and dust cause a
third type of scattering for FSO signals with particle sizes larger than the
optical wavelength.
The effect of fog on FSO systems is significantly detrimental, and the
attenuation could reach 200 dB/km and even 350 dB/km in low visibility regimes
[22]. Attenuation under dusty channels at low visibility could be higher than
fog as demonstrated in [23] using an FSO experiment with a laboratory-emulated
dust storm. Attenuation due to snow can also reach 150 dB/km [8]. Compared to
fog and snow, the effect of attenuation is less drastic during the rain, with
a 45 dB/km attenuation loss recorded for 1550 nm signals under a heavy rain
regime [8]. In this view, the combination of FSO and RF in one communication
system is even more appealing, as the RF is affected the worst by the rain of
all atmospheric conditions, whereas the fog has little to no effect on the RF
propagation.

TABLE I:  Comparison between FSO and RF technologies. Technology | RF | FSO
---|---|---
Available Spectrum |  $\sim$ 300 GHz |  $\sim$ 100s THz
Licensing | Licensed | Unlicensed
Terminal Foot-prints | Bulk | Small
Energy Consumption | Tens of [W] | Tens of [mW]
Data Rates | Mbits/Gbits | Tbits
Configuration | LoS/NLoS | LoS
Latency | Moderate | Low
Noise sources | Interference with other users | Background ambient light
Safety | Subject to EMF radiations | Eye and skin safe
Security | Susceptible to Eavesdropping | Secure
Sensitivity to Pointing Errors | Low | High
Propagation Effects | Attenuation, fading | Attenuation, turbulence

FSO channels are also subject to turbulence resulting from random variations
of the refractive index due to fluctuations of temperature and pressure in the
atmosphere. Atmospheric turbulence affects FSO almost exclusively due to the
wavelength compared to RF. Atmospheric turbulence can be modeled using
numerical models based on Kolomogrov theory and statistical models [24].
Different statistical models have been widely used to model turbulent FSO
channels in the literature, such as the negative exponential, log-normal,
Gamma-Gamma, and the Malaga models [11].
Dynamic wind loads causing sway of buildings, weak earthquakes, and small
vibrations due to road traffic cause the beam to deviate from its path
randomly [25]. These effects are known as pointing errors and impose
additional challenges for FSO links and severally affect the transmissions’
reliability if not compensated. Pointing errors are commonly modeled using a
Rayleigh distribution [26]. In terms of noise, FSO is subject to ambient noise
from the sun, while RF is subject to thermal noise.
For a full budget link calculation of FSO links, taking into account
attenuation, turbulence, beam divergence, and pointing errors, we direct the
reader to the detailed study in [14]. As takeaway messages of this section,
the full comparison between the FSO and RF technologies is summarized in Table
I. Moreover, the most common line of sight (LoS) models for the FSO and RF
channels under different channel conditions are reported in Table II.

TABLE II:  Most common LoS models for FSO and RF channels. | Atmospheric Condition | Model | Description and Parameters
---|---|---|---
FSO | Fog | Mie scattering model: $\displaystyle A=\frac{13}{V}\left(\frac{\lambda}{0.55}\right)^{-q}$ [dB/km] |  $\cdot$ Empirical model for scattering due to fog. $\cdot$ Model parameters [27]: $V$ [km]: Visibility range $\lambda$ [$\mu$m]: Operating wavelength $q$: Size distribution of the scattering particles
Dust storm | Dust attenuation model: $\displaystyle A_{d}=-52V^{-1.05}$ [dB/km] |  $\cdot$ Empirical model for dust scattering. $\cdot$ Model parameters [28]: $V$ [km]: visibility range $\lambda$=1550 nm
Snow | Snow attenuation model: $\displaystyle A_{s}=k/V$ [dB/km] |  $\cdot$ Empirical model for snow. $\cdot$ Model parameters: $V$ [km]: Visibility range $k$: Constant defined in [29]
Rain |  Rain attenuation model: $\displaystyle A_{r}=KR^{\alpha}$ [dB/km] |  $\cdot$ Model describing scattering due to rain. $\cdot$ Empirical model for rain scattering. $\cdot$ Model parameters: $R$ [mm/hr]: Precipitation intensity $(K,\alpha)$: Model parameters [30]
Weak turbulence |  Log-normal turbulence model: $\displaystyle f(I)=\frac{1}{2I\sqrt{2\pi\sigma_{I}^{2}}}\exp\left(-\left(\ln\frac{I}{I_{o}}+\frac{\sigma_{I}^{2}}{2}\right)^{2}\bigg{/}2\sigma_{I}^{2}\right)$ |  $\cdot$ Statistical model suitable for weak fluctuations regime. $\cdot$ Model parameters: $E[I]=I_{0}$: Mean irradiance. $\sigma_{I}^{2}$: Scintillation index (SI) [31]
Strong turbulence |  Negative exponential model: $\displaystyle f(I)=\frac{1}{I_{0}}\exp\left(-\frac{I}{I_{0}}\right),~{}I_{0}>0$ |  $\cdot$ Statistical model suitable for strong fluctuations regime. $\cdot$ Model parameters: $E[I]=I_{0}$: Mean irradiance
Moderate to strong turbulence |  Gamma-Gamma turbulence model: $\displaystyle f_{I}(I)=\frac{2(\alpha\beta)^{(\alpha+\beta)/2}}{\Gamma(\alpha)\Gamma(\beta)}I^{(\alpha+\beta)/2-1}K_{\alpha-\beta}\left(2\sqrt{\alpha\beta}I\right)$ |  $\cdot$ Statistical model suitable for moderate to strong turbulence conditions. $\cdot$ Model parameters: $(\alpha,\beta)$: Turbulence related parameters $\cdot$$\Gamma(.)$: Gamma function $\cdot$$K_{v}(.)$: Modified Bessel function of the second kind and order $v$
All turbulence conditions |  Málaga turbulence model: $\displaystyle f_{I}(I)=A\sum_{k=1}^{\beta}\alpha_{k}I^{\frac{\alpha+k}{2}-1}K_{\alpha-k}\left(2\sqrt{\frac{\alpha\beta I}{\gamma\beta+\Omega}}\right)$ $\displaystyle\begin{cases}A=\frac{2\alpha^{\alpha/2}}{\gamma^{1+\alpha/2}\Gamma(\alpha)}\left(\frac{\gamma\beta}{\gamma\beta+\Omega}\right)^{\beta+\frac{\alpha}{2}}\\\ \alpha_{k}=\left(\begin{array}[]{c}\beta-1\\\ k-1\\\ \end{array}\right)\frac{(\gamma\beta+\Omega^{{}^{\prime}})^{1-\frac{k}{2}}}{(k-1)!}\left(\frac{\Omega^{{}^{\prime}}}{\gamma}\right)^{k-1}\left(\frac{\alpha}{\beta}\right)^{\frac{k}{2}}\end{cases}$ |  $\cdot$ Statistical model suitable for all turbulence regimes and can be simplified to Log-normal, negative exponential, and Gamma-Gamma models $\cdot$ Model parameters [32] $\beta$: Amount of fading parameters $\Omega:$ Average power of the LoS term
RF | Fading |  Nakagami-m model $\displaystyle f(x)=\frac{2m^{m}x^{2m-1}}{\Omega^{m}\Gamma(m)}\mbox{exp}\left(-\frac{mx^{2}}{\Omega}\right)$ |  $\cdot$Suitable to model a wide range of fading. $\cdot$ Model parameters: $x$: Channel fading amplitude, $m\geq\frac{1}{2}$: Shape factor (fading parameter) $\Omega>0$: Mean-square value of $x$ [33] $\cdot$$\Gamma(.)$: Gamma function
Multipath fading |  Rician model: $\displaystyle f(x)=\frac{2(K+1)x}{\Omega}\exp\left(-K-\frac{(K+1)}{x^{2}}\right)I_{0}\left(2\sqrt{\frac{K(K+1)}{\Omega}}x\right)$ |  $\cdot$ Stochastic model to model multipath propagation with the line of sight path being stronger than others. $\cdot$ Model parameters: $K$ direct path to other scattered paths power ratio [34] $\cdot$$I_{0}(.)$: Modified Bessel function of the first kind and order 0

##  III Mixed RF/FSO Multihop Links

Figure 4: A schematic illustration mixed serial dual-hop RF/FSO configuration.
RF signals at the relay node are converted to optical signals and forwarded to
the destination on the FSO link.

A possible scenario for the deployment of FSO is when it is combined with RF
transmission systems to fill the connectivity gap between the RF access
network and the fiber backbone network [35, 36]. A schematic illustration of a
dual-hop mixed RF/FSO configuration is shown in Fig. 4. The dual-hop has two
primary designs: Amplify and Forward (AF) and Decode and Forward (DF).

  * •

In an AF system, the data initially encoded on an RF channel is received by an
antenna at a relay node. The received electrical signals are converted to
optical signals and amplified and forwarded to the FSO transmitter at the
relay.

  * •

In the case of DF relaying, the signal is decoded, regenerated, and then
retransmitted to the FSO node.

The AF approach is preferable and less complex than DF, as it does not require
any decoding at the relay node.
Dual-hop heterogeneous systems, with both AF and DF relays, have been well
studied considering a wide range of RF and FSO channels [35, 36, 37, 38, 39].
In a seminal study, Lee et al. studied the outage performance of a dual-hop
heterogeneous RF/FSO system with a fixed gain AF relay [35]. The RF link is
assumed to be subject to a Rayleigh fading, and the FSO is subject to Gamma-
Gamma turbulence. A sub-intensity modulation (SIM) scheme was considered for
the AF relay to convert the incoming RF signal to optical signals before being
forwarded to the destination. We note that SIM is a technique that consists of
modulating a pre-modulated RF signal on the intensity of optical signals,
which lowers the system’s complexity [40]. The primary outcome of the study
reported in [35] is that RF/FSO systems have slightly worse performance (in
terms of outage probability) than conventional dual-hop RF/RF links. The work
was followed by the outage performance analysis of a dual-hop system subject
to a Rayleigh fading for the RF hop and an M-fading generalized model for the
FSO hop [36]. The authors also assumed a SIM scheme to convert the RF signals
to optical signals at the fixed-gain AF relay node and further considered the
effect of pointing errors that could occur on the FSO link. The capacity and
error performances of a dual-hop RF/FSO system with a Nakagami-$m$ RF channel
and a Gamma-Gamma distributed FSO link were studied in [37]. Authors of [38]
considered the same RF and FSO channel conditions as [35] but with a DF
relaying scheme. Both fixed gain and channel state information (CSI) relaying
scenarios are considered in a dual-hop RF/FSO study reported in [39], where
the RF link is subject to a Nakagami-$m$ fading, and the FSO is subject to
Gamma-Gamma turbulence. Note that the CSI-based relaying, also known as
variable gain, assumes feedback sent from the receiver to the transmitter. The
effect of outdated CSI on the outage BER performances of RF/FSO mixed system
was investigated in [41]. The authors assumed that the RF link is subject to
Rayleigh fading, and the FSO is modeled by a Gamma-Gamma distribution.
A less conventional relaying scheme known as Quantize and Encode (QE) was
considered in an RF/FSO dual-hop system [42]. In a QE relaying scheme, the RF
source uses a quadrature amplitude modulation (QAM) format, and the relay
estimates and quantizes the log-likelihood ratio of each received bit in a QAM
symbol and then transmits it through the FSO channel. Overall, with many
relaying schemes, mixed RF/FSO systems have been well studied in the
literature.

##  IV Hybrid RF/FSO system: Operation and Switching Mechanisms

Figure 5: A schematic illustration of a hybrid RF/FSO configuration. Data can
be transferred on the RF or the FSO link, or both.

Besides being used in a dual-hop fashion, as discussed in section III, RF/FSO
technologies can be installed in parallel, forming a hybrid communication
system. An illustration of a hybrid RF/FSO system that supports the
simultaneous transmission of data using RF and FSO signals is depicted in Fig.
5. This section discusses the various operation modes of hybrid RF/FSO systems
from what has been proposed in the literature. We start by presenting two
switching mechanisms between the RF and FSO links, known as the hard and soft
switching schemes. A third scheme based on the use of machine learning
algorithms is then presented. We further cover the case when both the RF and
FSO transmitters operate simultaneously, known as the diversity scheme.

###  IV-A Hard Switching

Figure 6: An illustration of a hard switching system diagram. Continuous
feedback from the receiver to the transmitter is needed.

In a system based on hard switching, either the RF link or the FSO link is
operational at any given time. Feedback from the receiver to the transmitter
is used to coordinate between the two communicating terminals to perform the
switching.
Usman et al. proposed in [43] a hard switching mechanism for hybrid FSO/RF
systems. The authors assumed the use of the FSO link when it is above a
certain threshold, and when the link becomes unacceptable, the RF is used
instead. A dual FSO threshold system design was also considered, where the FSO
has two different thresholds for transitioning between “on” and “off” states.
The dual threshold system showed to be similar in performance to a simple hard
switching while reducing the number of switches and preserving the FSO
subsystem. The performance of the hard-switching approach was further
investigated in numerous manuscripts [44, 45]. Authors of [44] studied the
performance of a hard-switch-based RF/FSO system over generalized fading
models. Time Hysteresis (TH) and Power Hysteresis (PH) modifications to the
hard-switching approach were studied in [45], where the switching threshold
may be variable based on the channel conditions and history.
A multi-user FSO/RF hybrid network scheme was proposed in [46], where a
primary FSO link services every user. When the FSO link fails, a central node
allocates a backup RF link with non-equal priority to different users.
Finally, the performance of a selective dual-hop RF/FSO DF relay network based
on hard switching was studied in [47]. The authors assumed two RF/FSO
subsystems with a relay node and maximum ratio combining (MRC) scheme at the
receiver [47]. The proposed scheme was found to outperform FSO cooperative
system and single hope RF/FSO system.

###  IV-B Soft Switching

Figure 7: An illustration of a soft switching system diagram based on joint
encoding and decoding and with an optional (that is limited if used) feedback
from the receiver to the transmitter.

Within the soft-switching approach, channel coding can be used to coordinate
between the FSO and the RF links. The main advantage of the soft-switching
compared to the hard-switching is that the rate of the FSO link is not wasted
if the RF link is selected. Zhang et al. proposed a soft switching approach
based on short length Raptor codes [48]. In Raptor codes, each message sent
from the RF and FSO subsystems is different from the previous one. The decoder
decides to accept the entire block as soon as a sufficient number of messages
have been collected, whether they come from RF or the FSO transmitter. This
approach allows utilizing an otherwise unused FSO data rate for long-distance
transmission scenarios when the received FSO power would be considered below
the threshold for the hard switching-based mechanism. Authors of [48] showed a
rate gain by 4 folds (and more) compared to the hard switching approach for 1
and 2 km transmission length scenarios. However, both hard- and soft switching
approaches showed similar average data rate performance at a half-km
transmission length due to the sufficient optical power at the receiver.
Alternatively, authors of [49] proposed to adapt the transmitted symbol rate
and the constellations on the RF and FSO links depending on the channel
conditions. The authors pointed that such an approach could be particularly of
interest for grid-connected systems, where power conservation is not crucial.

###  IV-C Machine Learning Based Switching

Figure 8: An illustration of an ML-powered system diagram where hard switching
is performed based on the ML prediction. The feedback in the ML scheme is
optional.

Machine learning is a versatile tool that has found uses in almost all the
various fields of communication. Machine learning has been used in RF and
optical communication systems for applications such as performance monitoring,
modulation format identification, channel modeling, and digital signal
processing [50, 51, 52]. However, for the hybrid FSO/RF systems, only a few
studies have been so far reported. In [53] and [54], several machine learning
algorithms, including random forest, decision tree, and others, are exploited
to predict the received signal strength indicator (RSSI) in a hybrid FSO/RF
hard switching system. Accurate prediction of RSSI parameter helps in
fastening the switching between FSO link and RF link where for low RSSI, low-
speed RF link is used and for high RSSI, high-speed FSO link is used. The
obtained results show high accuracy for predicting the RSSI parameter with
superiority for the decision tree algorithm. Proactive switching for hybrid
FSO/RF links that ensure energy efficiency is studied in [55]. In hybrid
FSO/RF links, energy wastage happens because of the need to continuously keep
the FSO link “on” when the RF link is operational. The reason is to monitor
the channel, so when the channel conditions improve, the system switches to
the FSO link. To cope with this problem, the authors of [55] proposed that
when the RF link is “on”, the FSO link is kept in sleep mode with the
capability to activate it periodically to sample the FSO signal power by
transmitting beacon signals. These samples are used to train a Long Short Term
Memory (LSTM) algorithm to predict the link switching time (the time when the
FSO signal is expected to be above a predetermined threshold). The reported
simulation results have shown that the proposed technique can significantly
improve the energy efficiency of the RF/FSO system [55].

###  IV-D Diversity Scheme

Figure 9: An illustration of a diversity system diagram where both systems
simultaneously and the received data from the RF and FSO link are combined in
a combiner unit. The feedback in the diversity scheme is optional.

The diversity scheme consists of simultaneously transmitting the same
information on FSO and RF co-existing links. Under the assumption that
millimeter waves at 6 GHz support the same data rates as optical links,
authors of [56] proposed encoding the same data signals on an FSO and an RF
link. At the receiver, selective combining (SC) and MRC schemes are
considered. This diversity approach is challenging mainly when a complex
modulation format, such as phase shift keying (PSK), is used with the optical
links requiring coherent systems.
Authors of [57] proposed the use of receive diversity in a hybrid setup by
introducing multiple receivers for both FSO and RF subsystems. The FSO link is
assumed to have an equal gain combining (EGC) scheme, while the RF had an MRC
scheme to collect received signals. An IM/DD configuration was considered for
the FSO, making the implementation of such a system possible in practice. The
proposed hybrid RF/FSO system design demonstrated reduced power consumption
for a similar performance compared with RF or FSO only solutions and the case
when only a single receiver RF/FSO system is used. The primary motivation of
the proposed technique is to be used in scenarios where one of two links
experiences a frequent outage due to the weather conditions.
Rakia et al. proposed a power adaptation scheme based on truncated channel
inversion for an FSO/RF system employing adaptive combining to ensure a
constant signal-to-noise ratio (SNR) [58]. The FSO transmitting power was
considered to be constant, and two policies of power allocation to the RF
subsystem, based on RF only and joined SNR, were considered. Unlike other
diversity schemes presented, the feedback channel between receiver and
transmitter is once again needed in this scheme.
Finally, a complex hybrid RF/FSO backhaul network was considered in [59]. The
authors proposed the use of buffer-aided and quality-of-service (QoS) aware
relays in conjunction with novel adaptive single-carrier and multiple carrier
transmission schemes to reduce delay for latency-sensitive applications such
as virtual reality and smart grid control. Given a fixed QoS, numerical
simulations showed an increase in the maximum supported arrival rate.
A detailed summary of the studies on the various RF/FSO switching mechanisms
in the literature is given in Table III.

TABLE III: Summary of switching mechanisms for hybrid RF/FSO systems studied and demonstrated in the literature.  Ref. |  Study Type |  Scope |  Hardware Configuration |  Investigated Metrics |  Main Conclusions
---|---|---|---|---|---
[43] |  Analytical, with numerical examples |  Hard switching with single and double threshold policy |  RF/FSO switching with feedback control |  – Outage probability
– Average BER for non-outage time periods
– Ergodic capacity |  The dual threshold achieves performance similar to that of single threshold policy but increases the expected lifetime of the FSO link.
[44] |  Analytical / numerical |  Hard switching with single threshold policy over generalized fading models |  RF/FSO switching with feedback control |  – Outage probability
– Average symbol error rate (SER)
– Ergodic capacity |  The range of optimum FSO beam waists and optimum switching thresholds are provided. RF/FSO links are found to perform better than FSO only systems under strong atmospheric turbulence and high pointing errors.
[45] |  Algorithmic/ numerical |  Hard switching with TH and PH switching schemes |  RF/FSO switching with feedback control |  – Average hybrid data rate
– Link availability |  The high data rate of individual links does not directly correlate with the high data rate of the hybrid link.
[47] |  Analytical, with numerical examples |  Hard switching with a single threshold for selective DF relay network |  RF/FSO switching with feedback control |  – Outage probability
– Average SER |  The proposed system increases the performance when compared to the single-hop hybrid system and cooperative FSO system with MRC combining scheme.
[46] |  Analytical, with numerical examples |  Hard switching with a single threshold for multi-user network scenario under non-equal priority |  RF/FSO switching with feedback control |  – Average buffer size
– Average buffer queuing delay
– Frame loss probability
– Efficiency of the queue
– RF link utilization
– Throughput |  The proposed switching algorithm ensures higher performance for prioritized nodes, while still serving the low-priority nodes. The common backup RF link also improves the performance of all the nodes in the network.
[48] |  Algorithmic / experimental / numerical |  Soft-switching with Raptor codes |  RF/FSO joint encoding and decoding |  – Daily average data rate
Data rate probability densities for an experimental scenario based on meteorological data |  Short-length Raptor code based encoders nearly quadruples the average data rate on the studied dataset, compared to the hard switching.
[49] |  Analytical with numerical examples |  Soft-switching with link adaptation |  RF/FSO joint encoding and decoding |  – Throughput in relation to channel conditions |  A gain of about 10% on the considered dataset is reported, when compared to fixed a modulation scenario.
[53] |  Algorithmic / experimental / numerical |  RSSI for ML-powered hard switching |  RF/FSO switching based on RSSI |  – Comparison of 3 ML models performance for RSSI prediction. |  The appropriate values for the ML model parameters were studied.
[54] |  Algorithmic / experimental / numerical |  RSSI for ML-powered hard switching |  RF/FSO switching based on RSSI |  –Comparison of 3 ML models performance for the RSSI prediction in binary and multi-class implementation. |  Accurate prediction of RSSI can enhance the efficiency of hard FSO/RF switching.
[55] |  Algorithmic / experimental / numerical |  Predictive link switching |  RF/FSO predictive hard switching |  – Energy consumption
– Received optical signal power
– Energy efficiency |  The predictive switching improved the energy efficiency of the system compared to the reactive link switching
[56] |  Analytical, with numerical examples |  Transmit diversity with the SC and MRC combining schemes for PSK modulation |  RF/FSO joint decoding with no receiver feedback |  – BER performance |  MRC is the most optimal combining method for the proposed RF/FSO scenario.
[57] |  Analytical, with numerical examples |  Receive diversity with EGC scheme for the FSO link and MRC scheme for the RF |  SC-based RF/FSO receiver with no feedback |  – Outage probability |  The proposed system is recommended for use in Mediterranean climate due to heavy rain/fog.
[58] |  Analytical with numerical examples |  Adaptive RF switching and power adaptation based on FSO link quality with MRC receiver |  RF/FSO MSC with limited feedback for RF on/off |  – Outage probability
– Outage capacity |  The system has shown improvement in performance in terms of outage probability and RF subsystem power conservation compared to baseline.
[59] |  Analytical with numerical examples |  Adaptive transmission for single-carrier, and multiple-carrier hybrid RF/FSO with relaying |  Receiver only with single-carrier or multiple-carrier with no feedback |  – Maximum supported arrival rate
– Average queuing-delay
– RF and FSO data rate contribution |  The system has shown to improve the QoS aware maximum supportable arrival rate of the hybrid RF/FSO network.
TABLE IV: Configuration of the current commercial hybrid FSO/RF systems

Company name |  Product name |  Country of origin | Data rate [Gbps] |  Reach |  Laser |  RF band |  Latency |  Ap. cost |  Ref.
---|---|---|---|---|---|---|---|---|---
FSO |  RF |  distance [km] |  wavelength [nm] |  (GHz) |  (msec) |  (k USD)
Communication by light (CBL) |  AirLaser IP1000plus |  Germany |  1 |  0.1 |  Up to 1 |  830 – 870 |  5 |  0.052 |  $\sim$18 |  [60]
JV-Labs.EU |  iRedStar |  Czech Republic |  1 |  0.8 |  0.7 |  850 |  5 |  0.5 |  $\sim$5 |  [61]
LightPointe |  FlightStrata 100 XA |  USA |  0.1 |  0.072 |  5 |  850 |  5.8 |  $\leq$0.00002 |  NA |  [62]
HyBridge SXR-5 |  1 |  0.15 |  5 |  850 |  5.4/5.8 |  $\leq$0.00002 |  $\sim$16 |  [63]
Mostcom (ARTOLINK) |  Artolink M1-30GE |  Russia |  Up to 30 |  N/A |  1.3 |  1550 |  E-band |  0.005 |  10-15 |  [64]
Collinear |  HybridCNX-520 |  Australia |  10 |  Up to 9.8 |  Up to 5 |  1550 |  71-76/ 81-86 |  ULow |  NA |  [65]
EC Systems |  EL-10Gex |  Czech Republic |  Up to 30 |  N/A |  1.3 |  1550 |  E-band |  $\leq$0.005 |  NA |  [66]
Trimble |  PXW3500GT |  Hungary |  1 |  N/A |  3.5 |  785 |  WiFi |  0.00005 |  $\sim$10 |  [67]
fSONA |  SONAbeam 10G-E+ |  Canada |  10 |  0.1 |  Up to 5 |  1550 |  WiFi |  Low |  $\sim$25 |  [68]
Hyperion Technologies |  Small Cell Backhaul |  Turkey |  10 |  N/A |  0.3 |  1550 |  2.4 |  0.1 |  NA |  [69]
ANOVA Financial Networks |  Celeras LTS |  USA |  4 |  N/A |  0.3 |  1550 |  MMW |  UL |  NA |  [70]

  * *

N/A: Information not available.

  * **

Low/ULow: No precise value was provided for the latency but described as
Low/Ultra-Low.

  * ***

E-band (WiFi): Only information available is that the link operates in the
E-band (WiFi).

  * ****

MMW: Exact MMW frequency/band not provided.

##  V RF/FSO Systems Hardware Configuration

In this section, we discuss the hardware configuration for practical hybrid
RF/FSO systems. In particular, we review the specification of commercially
available RF/FSO solutions. Then, we present some of the recent field trials
aiming to set reliable RF/FSO systems.

###  V-A Commercially Available RF/FSO Solutions

Recent market statistics have shown that the expected investments in FSO
equipment will exceed $300 million in 2029 [71]. There are many commercially
available FSO products, and some of these systems offer the possibility to
also transmit data over RF channels [64]. In this section, we highlight the
main features of some of the currently available FSO/RF solutions. Table IV
summarizes the main configurations of commercially available products in terms
of data rate, reach distance, operating wavelength, backup RF band, latency,
and the approximate cost (whenever the information is available). Note that
the system’s approximate cost varies with the customization and how big the
equipment order is.

Some hybrid commercial products offer FSO links that can support up to 30 Gbps
in ideal weather conditions, such as EC Systems (EL-10Gex) and Mostcom
(Artolink M1-30GE). The maximum transmission distance can also reach up to 5
km with Collinear (HybridCNX-520) and fSONA (SONAbeam 10G-E+) solutions.
However, in harsh environments (under heavy fog, dust, or snow), the
communication link is often switched to the RF backup channel. The data rates
are reduced by more than an order of magnitude, as specified by Communication
by Light (CBL-AirLaserIP1000plus), LightPointe (HyBridge SXR-5), and fSONA
(SONAbeam 10G-E+) systems. Note that most companies have used unlicensed RF
bands for the radio backup links to reduce interference and cost. These bands
include both lower frequency sub-bands (typically 2.4 and 5 GHz) and higher
frequency millimeter-wave (MMW) sub-bands beyond 60 GHz.

Latency is a crucial parameter in emerging and next-generation wireless
networks. For instance, the 5G New Radio (NR) global standard is targeting 1
msec as air-interface latency. In this regard, current commercial products
have shown FSO links latency varying from 0.1 msec (Hyperion Technologies) to
50 nsec (Trimble) with transmission distances ranging from 0.3 to 3.5 km,
respectively. This motivates the deployment of these systems in advanced
wireless communication networks. Furthermore, the current commercial solutions
operate in the 850 nm and 1550 nm bands. Both bands are characterized by low
atmospheric attenuation. Besides being “eye-safe”, one of the advantages of
the 1550 nm band is the relatively low cost of FSO transmitting and receiving
devices. Advanced vertical-cavity surface-emitting laser (VCSEL) transmitters
and high sensitive avalanche photodiodes (APD) are widely used in this band.
The proliferation of high-speed transmitters, amplifiers, wavelength division
multiplexing (WDM) components, and receivers optimize the FSO transmission in
the 1550 nm band. It is worth noting that the maximum commercial speed in the
850 nm band is 1 Gbps using VCSELs and on-off keying (OOK) modulation, whereas
beyond 10 Gbps (OOK) can be transmitted using the enhanced small form-factor
pluggable (SFP+) network interface module, 1550 nm.

###  V-B Field Trials of Hybrid RF/FSO Systems

The outcome of a two-year RF/FSO experiment, conducted between two campuses in
the University of Ankara, was reported in [72]. For a link distance of 2.9 km,
the maximum achieved data rates by the FSO and RF links were 155 and 11 Mbps,
respectively. Based on the detected received power of the FSO channel, a hard
switching mechanism was set to switch between the two parallel links. Over the
experiment period, the RF/FSO links were subject to various natural
atmospheric conditions, including snow, haze, cloud, and fog. The author
showed snowstorms and fog are the most detrimental conditions that affect the
laser link’s availability. It is worth noting that the overall FSO link
availability exceeded 99.98% over an observation period. Besides, in [73], a
hybrid outdoor RF/FSO system was tested in Rome, by the Air Force Research
Laboratory (AFRL), for a duration of one week. The hybrid system is
demonstrated over a 30 km distance between two 100-foot height towers. The
data throughput was up to 10 Gbps and 1 Mbps for the FSO and RF channels,
respectively. For a reporting duration of 30 minutes, the communication was
shifted 5 times ($\sim$ 7 minutes) to the RF link owing to the FSO link
outages in foggy weather. Authors of [74] demonstrated a hybrid RF/FSO setup
that mimics the communication for airborne. The field trial experiment was
demonstrated on the German Aerospace Center (DLR) campus near Munich over a
300-meter distance between static objects. The reported data rates were 600
Mbps and 6 Mbps for the FSO and RF link, respectively. A hard switching
algorithm is employed such that only one link is used for data transmission if
the other is not available. The interruption in the FSO link is demonstrated
by applying deterministic fades using an optical attenuator. Another field
trial of FSO communication with an RF backup link has been demonstrated in
Qatar University [75]. Contrary to the other field trials where the effect of
fog and snow highly disturb the FSO link, the humidity effect has been
considered in this experiment owing to the atmospheric condition in this Gulf
area. A communication link of 600 meters was established between two
buildings. The authors conducted the outdoor experiment over a period of two
months from December to January, where the average humidity and temperature
were 66% and 25 ∘C, respectively. The field trial shows the effect of humidity
on the FSO throughput performance. The same authors repeated their
investigation in [76]. However, the experiments were conducted in the hot
summer for the period between June and September, where the average
temperature reaches 45 ∘C. From both studies, it has been shown that the FSO
link throughput is affected more by temperature rather than humidity.

###  V-C Lessons Learned

In this section, we reviewed the specifications of commercial products and
field trials testing hybrid RF/FSO communication systems. The following
lessons can be drawn:

  * •

Commercial systems with VCSEL-based FSO transceivers are limited to data rates
in the level of $\sim$1 Gbps. However, SPF+-based transceivers can provide up
to 30 Gbps and enable higher transmission distances compared to VCSEL-based
ones.

  * •

Link throughput versus weather conditions was the main focus in most field
trials where hard switching mechanism was mainly used, owing to its
simplicity. However, considering other switching strategies requires further
studies and investigations.

  * •

Snowstorm, fog, humidity, and high temperature (i.e., above 40 ∘C) are the
significant weather conditions that deteriorate the performance of FSO links.
However, further field trials under other extreme weather conditions, such as
rain and dust storms, are required before large-scale technology deployment.

##  VI RF/FSO for Space Communications

Here, we discuss the potentials of the co-existence of RF and FSO technologies
for near-Earth and deep space applications.

###  VI-A Overview on Satellites and Space Communication

Satellites have a wide range of applications, including remote sensing,
climate change control, deep space exploration, tackling the digital divide,
and providing connectivity to rural areas [77]. There are three main types of
Earth orbits satellites:

  * •

Low Earth Orbit (LEO) Satellites: which operate in close proximity of Earth
over distances between 160 to 2000 km. LEO satellites are mainly used for
imaging and are known for the low latency due to the relatively short
propagation distance in space. Recently, LEO satellite constellations (a group
of satellites working together) are receiving considerable attention and being
used to provide connectivity in rural areas.

  * •

Medium Earth Orbit (MEO) Satellites: which operate in the region above 2000 km
and below the static geostationary orbit. MEO satellites are mainly used for
navigation, communication, and space environment science.

  * •

Geosynchronous Earth Orbit (GEO) satellites: which are fixed with Earth in the
geostationary orbit (35,786 km) above the Earth’s equator and rotate in the
same direction with the Earth’s rotation. GEO satellites are typically used
for TV broadcasting and used by some satellite communication companies to
provide world coverage with a minimum number of satellites.

In satellite communication, the link connecting the network to the satellite
is known as a feeder link. The satellite sends signals to ground users through
multi-beams, known as the user links.
Traditional satellite communication has been historically based on microwave
bands, in particular, the L (1-2 GHz), Ku-band (12-18 GHz), and the Ka-band
(26.4-40 GHz). Compared to the Ku and Ka bands, the L band is less susceptible
to fading caused by rain. Ka and Ku have wider bandwidths and smaller
components. In the Ku band, only 1 GHz of bandwidth is allocated for satellite
services: half of it for uplink and the other half for the downlink. 6 GHz of
bandwidth is dedicated in the Ka-band for satellite communication [78].

###  VI-B Optical Near-Earth Space Communication

Optical communication in space has made tremendous progress over the years
[79]. An early inter-satellite demonstration has reported a successful error-
free 5.6 Gbps transmission between two Low Earth Orbit (LEO) satellites (NFIRE
and TerraSar-X) over several seconds [80, 81]. Ground-to-satellite (uplink)
and satellite-to-ground (downlink) FSO links have also been demonstrated [82,
83]. The first uplink and downlink demonstrations date back to 1994 with a
1.024 Mbps two-way communication between the Japanese Engineering Test
Satellite-VI (ETS-VI) and a ground station [82]. In 2016, the SOTA (Small
Optical TrAnsponder) system, developed by the National Institute of
Information and Communications Technology (NICT) in Japan, was used to
establish an optical communication link between a LEO satellite (SOCRATES) to
ground connection with a ground station affiliated to the German aerospace
center [83]. NASA, in collaboration with MIT Lincoln Laboratory, is currently
developing a 200 Gbps optical communication system to be installed on an LEO
Cubesat (small satellite at an altitude of 740 km) with a downlink that could
reach 200 Gbps to deliver more than 50 Terabytes of information per day to a
ground station, as a part of the TeraByte InfraRed Delivery (TBIRD) program
[84]. In addition to the vast bandwidth, optical satellite link require small
footprints devices that consume less energy compared to those operating in the
microwave bands typically used for Earth-satellite communications.
As the satellite communication race gears up, multiple companies are
developing optical free space feeder links and inter-satellite links to bring
fiber-like throughput to space. For example, Lightspeed-Telesat, and Starlink-
SpaceX projects aim to establish FSO satellite crosslinks in their satellite
constellations installed to provide broadband internet access all over the
globe [85, 86].
Optical links are preferable compared to RF links for space applications
because of the lower divergence of optical waves than the RF ones. However,
ground-space optical links are subject to turbulence and weather conditions,
particularly in the lower layers of the atmosphere, as discussed in section
II-D.

###  VI-C Mixing Optical and RF Links For Satellite Communication

Mixing optical communications and RF can be highly advantageous in
applications related to satellite, and deep-space communications [13]. As we
pointed out earlier, optical links are subject to atmospheric turbulence
affecting earth-to-space and space-to-earth links. Even though RF and optical
beams may propagate through the same geometrical path through the atmosphere,
the channel effects, in most cases, are more severe on optical signals. These
effects are caused by the various air densities on different heights above the
ground and the difference in the air’s turbulent behavior closer to the
ground. The distortions of the beam attributed to the atmospheric turbulence
are far greater close to the ground due to more substantial turbulence and
higher air density. This means that the downlink beam will encounter most of
the disturbances closer to the receiver, resulting in fewer distortions on the
beams’ intensity profiles than in the uplink case, where most of the
atmospheric disturbances are encountered immediately after leaving the
transmitter, and its adverse diffractive effects can accumulate over longer
propagation distances.
Therefore, it may be beneficial for the hybrid RF/FSO system to use FSO for
downlink and RF for the uplink. This is also beneficial, as RF downlink
signals may contribute to the spectrum congestion on the ground due to its
large spot size. We note that RF signals can result in interference for the
uplink but not as prominent as the downlink case. FSO can be further
beneficial for the downlink from the energy efficiency standpoint due to the
reduced energy consumption [87, 88]. However, more efforts are required to
develop advanced pointing, acquisition, and tracking mechanisms (PAT) for FSO
systems for near-Earth application [89, 90, 91, 92].
We note that many satellite and aerial network configurations based on hybrid
RF/FSO links have been proposed in the literature, such as the following:

  1. 1.

Satellite-aerial-terrestrial network, where a high-altitude platform (HAP)
acts as a relay between a satellite and terrestrial terminals [93, 94, 95,
96].

  2. 2.

Spatial networks, where the communications links such as satellite-to-
satellite (in the same or different orbits), HAP-to-HAP. The links in these
layers can be established using both RF or FSO [97].

  3. 3.

Hybrid networks as the RF link is for the ground-to-air channel, and the FSO
link is for the air-to-air path, and a hybrid RF/FSO system for the air-to-
ground channel. Such a setup utilizes the frequency spectrum efficiently,
enhances data rates, and provides inherent security [98].

  4. 4.

Multibeam high-throughput satellite systems where the feeder link operates in
the FSO band and the user link, between the satellite and the user terminal,
is in the RF Ka-band [99].

Another potential application of using FSO together with RF systems that worth
mentioning in this section is achieving satellite-based quantum key
distribution (QKD). Satellite-based QKD consists of distributing secret
encryption keys to enhance the security of long-range communication systems.
Earth-Satellite QKD demonstrations over distances beyond 1000 km have been
reported [100, 101]. The field of satellite-based QKD is continuously growing
[102, 103], and these research and development efforts will result in a global
QKD network that may enhance the encryption of conventional near-Earth
communication.

###  VI-D RF/FSO for Deep Space Operations

For deep space communication, RF can benefit from the well-established
infrastructure of the current systems. FSO can be used as a complementary
technology to push the data rates for this infrastructure, opening the door to
various applications such as outer-space real-time video streaming and the
transfer of high-resolution images. Indeed, recent demonstrations have shown
that optical wireless communication can potentially bring fiber-like
connectivity to the space [104, 105]. In Fall 2013, Nasa’s Lunar laser
communication demonstration (LLCD), which was part of the LADEE (Lunar
Atmosphere and Dust Environment Explorer) mission, reported a series of full-
duplex communications between a satellite in lunar orbit (400.000 from the
Earth) and multiple ground stations (in Spain and US) with a maximum uplink
throughput of 20 Mbits and downlink throughput of 622 Mbits [104, 105]. In
collaboration with SpaceX company, NASA is also currently working to install
an FSO system for the Psyche mission to explore a metal asteroid orbiting
between March and Jupiter [106]. The idea is to improve communication
performance by 10 to 100 times over the current RF technology without
incurring increases in mass, volume, or power. The FSO link is expected to be
operational in 2026.

##  VII Open Issues and Future Research Directions

In the following, we discuss the open issues associated with the RF/FSO co-
existence, related mainly to the cost of technology deployment. We then
provide a set of future and insightful research directions that we believe can
potentially lead to the wide-scale deployment of parallel RF/FSO links.

###  VII-A Economic Challenges

The main limiting factor of the wide-scale deployment of RF/FSO is the cost.
The cost of building the optical wireless infrastructure by network operators
is a significant challenge, in particular when coherent detection is used or
sophisticated PAT systems are involved for the FSO links. However, the return
of investment in terrestrial applications can be quick, mainly if IM/DD
systems are installed, and the FSO system is the primary link to preserve the
power consumption. The cost may also vary depending on the installation’s
geographical location. For example, suppose the hybrid system is installed in
a site where fog is a dominant weather condition. In that case, it will mostly
rely on radio technology, which derives higher Operating expenses (OPEX).
Programming the devices to perform the switching mechanisms can also generate
extra costs. To build confidence in such a technology, it should be installed
in pilot locations such as cities with clear weather conditions throughout the
year.

###  VII-B Boosting the Role of Machine Learning

Using machine learning algorithms for efficient switching between FSO and RF
links has not yet been fully exploited. Efficient switching ML-based
algorithms can be built based on several parameters like channel impairments.
Such parameters could be predicted using various ML tools with high accuracy,
as reported in [107, 108, 109]. A recent study reported in [109], has shown
that turbulence, pointing errors, and optical SNR can be predicted accurately
at different FSO transfer rates. ML-based switching can also be set on power
consumption or other non-channel-related parameters such as the EMF radiation.
This scenario can be suitable for cases when the RF is the primary source of
communication. The FSO system, in this case, can be turned “on” to reduce the
amount (or duration) of EMF radiations in a particular location.
We should note that the adoption of ML algorithms in parallel links requires
channel measurements on various RF and FSO channel conditions to build the
learning models. The relatively newly introduced Generative Adversarial
Networks (GAN) ML framework can be used for data augmentation in such cases.
We note that GAN is a deep neural network that learns to generate new data
with the same statistics of the learning set [110]. Using GAN can minimize the
amount of outdoor collected data required to train the learning models for the
RF/FSO ML-based switching method; in particular, that measurement collection
can be a time-consuming process. A recent study revealed that GAN-based
modeling is promising in wireless RF communication [111].

###  VII-C Connecting the Unconnected

As of January 2021, more than 35% of the world population does not have access
to the internet [112]. A large percentage of the connected population is also
under-connected with limited access to the internet, even in developed
countries. RF/FSO hybrid backhauling can significantly contribute to
connecting the unconnected and under-connected world regions. Setting new
optical fiber networks can be costly, mainly in terms of Capital Expenditure
(CAPEX), which involves the initial installation cost [113]. OPEX of RF/FSO
systems is comparable to those of RF-only systems, especially if the FSO link
is operational over long hours, which reduces the overall energy consumption.
Using only RF links may also not be enough to fulfill the continuously
increasing capacity demand. Therefore, co-installing RF and FSO technologies
can be a practical solution yet economically profitable to connect far-flung
areas with higher resistance to natural disasters. In particular, commercially
available plug-and-play hybrid systems can cover distances up to 10 km and can
be installed quickly without incurring civil engineering costs to lay optical
fibers underground [14]. RF/FSO system can equally contribute to enhancing the
internet throughput for those living in densely populated areas and suffering
from low internet penetration. Providing reliable connectivity to these
locations can enable new technologies for smart agriculture and also climate
change monitoring and internet of things (IoT) devices [114].

###  VII-D Massive MIMO Hybrid RF/FSO

Massive MIMO configuration can significantly contribute to increasing the data
rates of radio links [115]. A massive MIMO configuration can enable to match
the throughput of RF links to what could be provided by a single FSO link.
Progress in VCSEL technology has also led to the development of many FSO
sources that could be modulated independently on a single chip. There are also
various designs of multi-aperture detectors in direct and coherent detection
configurations. Newly developed antennas can be incorporated to extend the
field of view of high-speed optical detectors [116]. MIMO RF/FSO can equally
improve the reliability of both links.

###  VII-E Non-Conventional RF/FSO hybrid systems

There has been considerable interest in using the orbital angular momentum
(OAM) degree of freedom of the electromagnetic wave to push the transmission
capacity [117]. OAM is associated with a helical phase- front of
$\exp(i\ell\phi)$ [118], with $\ell$ being the topological charge and $\phi$
is the azimuth. The orthogonality between OAM beams enabled an extra
multiplexing scheme in optical communication [119]. OAM multiplexing is
possible in FSO, as well as in radio communication [120]. Beyond Tbps
transmissions were reported using OAM multiplexing using optical signals
propagating in free space [121, 122] and Multi-Gbps transmissions have also
been demonstrated in the RF domain [123]. OAM multiplexing is a particular
case of spatial mode multiplexing, which also involves using orthogonal mode
families to carry independent data streams, such as the Laguerre Gaussian
(LG), Hermite Gaussian (HG), and Ince Gaussian (IG) mode bases. Another
promising aspect of using spatial mode multiplexing is fulfilling diversity
without any requirements on the separation between the transmitting or
receiving apertures [124]. Diversity is not restricted to OAM-only modes
derived from LG mode basis but can cover modes from different mode bases, such
as LG and HG modes.
Djordjevic proposed in [125] using OAM FSO/RF to increase the spectral
efficiency and PLS of the optical and RF wireless systems [125].
This non-conventional RF/FSO spatial-mode based is indeed promising. However,
there are still some issues mainly associated with the design of compact mode
generation and detection techniques that need to be addressed before deploying
such a method beyond laboratory-test benches either in the optical or RF
bands.

###  VII-F Toward Multiband Transmission

The THz band has recently attracted considerable attention and seems to offer
plenty of opportunities for wireless communication [126]. Progress in devices
and modeling may bring THz communication to life sooner than we thought [127,
128]. Incorporating this frequency band, ranging from 100 GHz to 10 THz, fills
the gap between the RF and optical bands and leads to creating multiband
systems. Multiband systems can provide further resilience to a wide range of
channel conditions [129]. For example, as we discussed in section II-D, FSO
signals are severely affected by dust storms. However, experimental
investigations, reported in [129], showed that THz signals are barely affected
by dust signals. Multiband can equally open up new applications. Although
water vapor in the atmosphere severely absorbs THz signals, they can be used
with RF/FSO systems to provide high-throughput connectivity in non-line-of-
sight scenarios or short-range transmissions.
Multiband transmission can be further of interest for near-Earth and deep
space applications. THz beams have lower divergence compared to RF ones, which
can provide a good compromise between pointing sensitivity and geometrical
loss. It has been pointed out that THz communication systems can offer a
comparable performance to FSO systems for Earth-to-satellite links in dry
regions [130].
Another advantage of parallel multiband transmissions is strengthening the
secrecy of the system. If an intruder is detected in one band, switching the
communication on one of the other two technologies makes signal interception
or jamming difficult. It is also possible to divide the same information on
the various communication bands, restricting any eavesdropper from revealing
any useful information by eavesdropping on a single band. This can provide
extra security to RF/FSO networks.

###  VII-G Toward Self-Powered RF/FSO Networks

Solar-powered RF base stations are being deployed in various areas of the
world [131]. Powering RF sites using solar panels can ensure power delivery to
radio base stations in remote locations or regions without reliable grid
connectivity [131]. A future idea to explore is to build hybrid RF/FSO self-
powered networks. A particular scenario of interest is to use FSO systems to
lower power consumption in battery-powered sites to avoid or reduce the power
outage period, mainly because FSO systems typically consume less energy than
the RF ones, and therefore ensuring longer battery lives.
Using solar power as an energy source can reduce the carbon footprints of
cellular base stations compared to fuel-powered ones. It has also been
demonstrated that off-the-shelf solar panels can be used to decode information
signals while harvesting energy [132]. Indeed, high data rates in the order of
1 Gbps can be reached when using solar cells operating as photodetectors
[133]. MIMO configuration using solar cells has been shown to be also possible
in [134]. Using solar cells initially used to power base station batteries to
decode optical information signals without using any dedicated photodetectors
is another idea to explore, mainly in scenarios when no large amount of data
is transmitted. Using large area solar detectors can equally ease the PAT
requirements for FSO systems even in the presence of atmospheric turbulence or
slight pointing errors.

##  VIII Conclusion

FSO communication is paving the way toward high-speed wireless backhauls.
However, the sensitivity of optical signals to atmospheric turbulence may
limit the potential of large-scale deployment of such a technology. By
retrofitting FSO systems to existing RF infrastructure, it is possible to
benefit from the high data rates of FSO systems and the resilience of RF links
to atmospheric turbulence. Throughout this paper, we identified the motivation
of using RF and FSO communication links together. We presented the different
operation and switching mechanisms adopted in RF/FSO parallel links. The
characteristics of various commercially available RF/FSO solutions as well as
reported field trials are reviewed. The potential of using FSO on top of RF
systems for near-Earth and deep space applications is highlighted. Open issues
associated with hybrid RF/FSO systems’ hardware and deployment cost are
discussed. We finally identified future research directions that could be of
interest to academics and industrials working on the design of RF/FSO parallel
links. Among such directions, using RF/FSO communication can contribute to the
efforts willing to connect the unconnected and enhance internet throughput in
under-connected regions. Building multiband systems covering the THz band can
create a wide range of new opportunities and further resilience to atmospheric
conditions for terrestrial and satellite communications. RF/FSO networks can
lower power consumption and, therefore, decrease outage risks in battery-
powered base stations in difficult-access locations.

## List of Abbreviations

5G: Fifth Generation
6G: Sixth Generation
AF: Amplify and Forward
APD: Avalanche Photodetector
BER: Bit Error Rate
CAPEX: Capital Expenditure
CSI: Channel State Information
DF: Decode and Forward
DSP: Digital Signal Processing
EGC: Equal Gain Combining
EMF: Electromagnetic Field
FSO: Free Space Optics
GAN: Generative Adversarial Network
GEO: Geosynchronous Earth Orbit
HAP: High Altitude Platform
HG: Hermite Gaussian
HTS: High Throughput Satellite
IoT: Internet of Things
IM/DD: Intensity Modulation/Direct Detection
IR: Infrared
LEO: Low Earth Satellite
LG: Laguerre Gaussian
LiFi: Light Fidelity
LoS: Line of Sight
LSTM: Long Short Term Memory
MEO: Medium Earth Orbit
MIMO: Multiple-Input Multiple-Output
ML: Machine Learning
MMW: Millimeter Wave
MRC: Maximum Ratio Combining
NLoS: Non-line-of sight
NR: New Radio
OAM: Orbital Angular Momentum
OOK: On Off Keying
OPEX: Operating Expenses
PAT: Pointing, Acquisition, and Tracking
PH: Power Hysteresis
PLS: Physical Layer Security
PSK: Phase Shift Keying
QAM: Quadrature Amplitude Modulation
QE: Quantize and Encode
QKD: Quantum Key Distribution
QoS: Quality of Service
RF: Radio Frequency
Rx: Receiver
RSSI: Received Signal Strength Indicator
SATN: Satellite-Aerial-Terrestrial Network
SC: Selective Combining
SER: Symbol Error Rate
SFP: Small Form-factor Pluggable
SI: Scintillation Index
SIM: Sub-intensity Modulation
SISO: Single-Input Single Output
SNR: Signal to Noise Ratio
TH: Time Hysteresis
Tx: Transmitter
UAV: Unmanned Aerial Vehicle
VCSEL: Vertical Cavity Surface Emitting Laser
VLC: Visible Light Communication
WDM: Wavelength Division Multiplexing
WiFi: Wireless Fidelity
WOC: Wireless Optical Communication

## Funding

KAUST-KSU special initiative. KAUST office of sponsored research (OSR).

## Acknowledgment

Figure 1 was produced by Heno Hwang, a scientific illustrator at King Abdullah
University of Science and Technology (KAUST).

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