A Review on Communications Perspective of Flying Ad-Hoc Networks: Key Enabling Wireless Technologies, Applications, Challenges and Open Research Topics

Abstract

Unmanned aerial vehicles (UAVs), also known as drones, once centric to military applications, are presently finding their way in many civilian and commercial applications. If national legislations permit UAVs to operate autonomously, one will see the skies become populated with many small UAVs, each one performing various tasks such as mail and package delivery, traffic monitoring, event filming, surveillance, search and rescue, and other applications. Thus, advancing to multiple small UAVs from a single large UAV has resulted in a new clan of networks known as flying ad-hoc networks (FANETs). Such networks provide reliability, ease of deployment, and relatively low operating costs by offering a robust communication network among the UAVs and base stations (BS). Although FANETs offer many benefits, there also exist a number of challenges that need to be addressed; the most significant of these being the communication one. Therefore, the article aims to provide insights into the key enabling communication technologies through the investigation of data rate, spectrum type, coverage, and latency. Moreover, application scenarios along with the feasibility of key enabling technologies are also examined. Finally, challenges and open research topics are discussed to further hone the research work.

Full text

drones
Review
A Review on Communications Perspective of Flying
Ad-Hoc Networks: Key Enabling Wireless
Technologies, Applications, Challenges and Open
Research Topics
Fazal Noor 1, Muhammad Asghar Khan 2, * , Ali Al-Zahrani 1, Insaf Ullah 2and
Kawther A. Al-Dhlan 3
1Faculty of Computer Science and Information Systems, Islamic University of Madinah,
Madinah 400411, Saudi Arabia; mfnoor@iu.edu.sa (F.N.); a.alzahrani@iu.edu.sa (A.A.-Z.)
2Department of Electrical Engineering, Hamdard University, Islamabad 44000, Pakistan;
insaf.ullah@hamdard.edu.pk
3Department of Computer Science and Information, University of Hail, Ha’il 55425, Saudi Arabia;
k.aldhlan@uoh.edu.sa
*Correspondence: m.asghar@hamdard.edu.pk; Tel.: +92-336-5276465
Received: 6 September 2020; Accepted: 28 September 2020; Published: 30 September 2020


Abstract:
Unmanned aerial vehicles (UAVs), also known as drones, once centric to military
applications, are presently finding their way in many civilian and commercial applications. If national
legislations permit UAVs to operate autonomously, one will see the skies become populated with many
small UAVs, each one performing various tasks such as mail and package delivery, traffic monitoring,
event filming, surveillance, search and rescue, and other applications. Thus, advancing to multiple
small UAVs from a single large UAV has resulted in a new clan of networks known as flying ad-hoc
networks (FANETs). Such networks provide reliability, ease of deployment, and relatively low
operating costs by offering a robust communication network among the UAVs and base stations
(BS). Although FANETs offer many benefits, there also exist a number of challenges that need to be
addressed; the most significant of these being the communication one. Therefore, the article aims to
provide insights into the key enabling communication technologies through the investigation of data
rate, spectrum type, coverage, and latency. Moreover, application scenarios along with the feasibility
of key enabling technologies are also examined. Finally, challenges and open research topics are
discussed to further hone the research work.
Keywords: UAVs; FANETs; Bluetooth; ZigBee; 5G; 6G; security; privacy; blockchain; energy harvesting
1. Introduction
Unmanned aerial vehicles (UAVs) have gained recognition for their variety of applications in
different domains such as surveillance, agriculture, health care, traffic control, inspections, and public
safety [
1
]. Moreover, in comparison to a stand-alone UAV, multiple small UAVs can be effectively
combined to execute assigned tasks in autonomous ways [
2
]. Thus, advancing from a single UAV
to multi-UAVs results in the emergence of a new clan of networks named flying ad-hoc networks
(FANETs) [
3
]. Smaller interconnected UAVs can exchange data with each other and with base stations
(BS) in a FANET system [
4
]. FANETs possess advanced features such as high mobility, fast deployment,
self-configurations, low cost, scalability, and others. However, such specific features demand a set of
guidelines that need to be addressed for effective implementation. Particularly, when selecting a FANET
system for real-time communication, Quality of Service (QoS) should be guaranteed [
5
]. In addition,
Drones 2020,4, 65; doi:10.3390/drones4040065 www.mdpi.com/journal/drones

Drones 2020,4, 65 2 of 14
for the exchange of information between UAVs and a BS, the network must have incorporated an
efficient and secure wireless connection.
FANETs can be deployed either individually or incorporated into traditional cellular infrastructures.
The subject has attracted the interest of both industry and academic experts. Most related research
studies seek to integrate FANETs with or without traditional networks in a manner that upholds
the QoS, security, and reliability requirements of small UAVs [
6
]. Therefore, the detection and
identification of vulnerabilities in the current systems are important for developing solutions that
enable high-throughputs and reliable data communications. The popular short-range wireless
networking technologies such as Wi-Fi (IEEE 802.11), ZigBee (IEEE 802.15.4), Bluetooth (IEEE 802.15.1),
and others can be utilized to incorporate a FANET system independently. Such technologies not only
provide wireless networking in the immediate vicinity, but also provide spectrum-free bands [
7
]. In the
following two scenarios, they are a good choice: in the event of failure due to the deterioration of
existing communication networks, and in remote areas, where problems do not enable installation
and deployment immediately. Additionally, they can step up rescue operations by maintaining
effective UAV communications. In addition, the low altitude of UAVs due to short-distance wireless
communication significantly improves the performance of networks in terms of QoS.
The Fifth-Generation (5G) technologies are projected to offer improved services in terms of data
rates and coverages in linking FANETs to existing cellular networks [
8
]. Moreover, 5G provides
multi-access edge computing (MEC), incorporating cloud computing capabilities. MEC prevents
resource-affected UAVs from performing compute-intensive tasks in a UAV environment and provides
offloading facilities to the edge of the network. Hence, 5G has many benefits for high-altitude
UAVs equipped with cameras, sensors, and GPS receivers. In addition, 5G has made it possible to
envision cellular networks beyond 5G (B5G) and sixth-generation (6G) is capable of incorporating
autonomous services as well as emerging developments to be envisioned [
9
]. The main issues are the
safe usage of these technologies and the provision of privacy in small UAVs in future wireless networks.
The design considerations of small UAVs rarely address the security concerns [
10
]. Small UAVs
also suffer from security vulnerabilities due to limited and insufficient onboard computing and
energy capabilities [
11
,
12
]. Such constraints prevent UAV deployment for longer periods of time
and for safer operations. Significant attempts have been made to resolve the underlying technical
problems in order to take advantage of the wider benefits of the multi-UAV networks [
13
]. Figure 1
shows a diagram summarizing the communication scope in FANETs, their involvement with recent
technological advances, and their combined applications. Therefore, it is essential to have adequate
wireless technologies and lightweight security schemes that can significantly stabilize battery life,
have minimal computational costs, and encourage better connectivity. In comparison, in this review,
key enabling technologies are addressed that manifest themselves as the paradigms needed to effectively
deploy FANETs in the future. It also highlights the main challenges and provides guidance for future
research work.
Drones 2020, 4, x FOR PEER REVIEW 2 of 14
selecting a FANET system for real-time communication, Quality of Service (QoS) should be
guaranteed [5]. In addition, for the exchange of information between UAVs and a BS, the network
must have incorporated an efficient and secure wireless connection.
FANETs can be deployed either individually or incorporated into traditional cellular
infrastructures. The subject has attracted the interest of both industry and academic experts. Most
related research studies seek to integrate FANETs with or without traditional networks in a manner
that upholds the QoS, security, and reliability requirements of small UAVs [6]. Therefore, the detection
and identification of vulnerabilities in the current systems are important for developing solutions that
enable high-throughputs and reliable data communications. The popular short-range wireless
networking technologies such as Wi-Fi (IEEE 802.11), ZigBee (IEEE 802.15.4), Bluetooth (IEEE 802.15.1),
and others can be utilized to incorporate a FANET system independently. Such technologies not only
provide wireless networking in the immediate vicinity, but also provide spectrum-free bands [7]. In the
following two scenarios, they are a good choice: in the event of failure due to the deterioration of
existing communication networks, and in remote areas, where problems do not enable installation and
deployment immediately. Additionally, they can step up rescue operations by maintaining effective
UAV communications. In addition, the low altitude of UAVs due to short-distance wireless
communication significantly improves the performance of networks in terms of QoS.
The Fifth-Generation (5G) technologies are projected to offer improved services in terms of data
rates and coverages in linking FANETs to existing cellular networks [8]. Moreover, 5G provides
multi-access edge computing (MEC), incorporating cloud computing capabilities. MEC prevents
resource-affected UAVs from performing compute-intensive tasks in a UAV environment and
provides offloading facilities to the edge of the network. Hence, 5G has many benefits for high-
altitude UAVs equipped with cameras, sensors, and GPS receivers. In addition, 5G has made it
possible to envision cellular networks beyond 5G (B5G) and sixth-generation (6G) is capable of
incorporating autonomous services as well as emerging developments to be envisioned [9]. The main
issues are the safe usage of these technologies and the provision of privacy in small UAVs in future
wireless networks. The design considerations of small UAVs rarely address the security concerns
[10]. Small UAVs also suffer from security vulnerabilities due to limited and insufficient onboard
computing and energy capabilities [11,12]. Such constraints prevent UAV deployment for longer
periods of time and for safer operations. Significant attempts have been made to resolve the
underlying technical problems in order to take advantage of the wider benefits of the multi-UAV
networks [13]. Figure 1 shows a diagram summarizing the communication scope in FANETs, their
involvement with recent technological advances, and their combined applications. Therefore, it is
essential to have adequate wireless technologies and lightweight security schemes that can
significantly stabilize battery life, have minimal computational costs, and encourage better
connectivity. In comparison, in this review, key enabling technologies are addressed that manifest
themselves as the paradigms needed to effectively deploy FANETs in the future. It also highlights
the main challenges and provides guidance for future research work.
Figure 1. Scope of communication with technological advancements for various applications in
FANETs.
Figure 1.
Scope of communication with technological advancements for various applications in FANETs.

Drones 2020,4, 65 3 of 14
The rest of the paper is organized as follows. Section 2describes the key enabling wireless
technologies; Section 3elaborates on applications; in Section 4, the challenges are discussed; Section 5
highlights the future work, and finally Section 6contains the conclusions.
2. Key Enabling Wireless Technologies
The choice of appropriate wireless communication technologies for FANETs depends on the
type of an application and the nature of the mission involved. Unlicensed wireless technologies such
as Wi-Fi, ZigBee, and Bluetooth are widely used for fast deployment and small- to medium-scale
applications [
6
,
7
]. Licensed wireless technologies such as 5G/6G, on the other hand, are used to satisfy
the requirements of broadband access everywhere, high device mobility, and integration of a massive
number of UAVs in an ultra-reliable way [
14
]. Based on the spectrum type (licensed/unlicensed),
the most suitable wireless technologies for FANETs are categorized in Table 1. To provide wireless
connectivity in the immediate vicinity, unlicensed or short-range wireless technologies have the ability
to offer off-the-shelf, lightweight, and cost-effective wireless connectivity. Unlicensed technologies
offer information transfer in the instant vicinity ranging from millimeters to a few hundred meters.
The most suitable short-range wireless technologies are Wi-Fi, Bluetooth, and ZigBee, which can
be used for medium and low data rate applications of FANETs. Wi-Fi provides a set of specifications for
the implementation of wireless local area networks (WLANs) with radio bands of 2.4, 3.6, 5, and 60 GHz,
respectively. IEEE 802.11a/b/g/n/ac is the first choice of variants for many FANET applications to
provide the required throughput for transmitting medium size data such as video and images [
15
].
The standard Wi-Fi system has a transmission range of approximately 100 m. A multi-hop networking
scheme may expand the transmission range to kilometers. However, it cuts down the lifetime of the
network from hours to minutes. An alternative to Wi-Fi is the use of low-cost and low-power radios
like Bluetooth and ZigBee. Bluetooth (IEE 802.15.1) is a possible candidate for the deployment of
FANETs at low cost and low power manners. It operates in an unlicensed frequency band of 2.4 GHz
with a contact range of 10 to 100 m and uses a distributed frequency-hopping transmission spectrum.
Bluetooth technology, with data rate ranging from 1 to 3 Mbps and a capacity of 24 Mbps, can be used in
three different models. The new version of Bluetooth core specification is Bluetooth 5 [
16
]. The primary
focus of Bluetooth 5 is to improve data rate, coverage, energy efficiency, and coexistence with other
technologies. Given the major improvements, Bluetooth 5 appears to be a possible candidate for
implementing future FANET systems at low cost and low power manners. Similarly, ZigBee technology
is widely used in applications that require long battery life, low data rates, and secure networking.
It ranges from 10 to 100 m and is less expensive and convenient than proprietary communication
technologies such as Bluetooth and Wi-Fi.
Low-power wide area networks (LPWAN) can be another good option that consumes less energy
and offers a wide range of connectivity for UAVs [
17
–
20
]. LPWAN allows transmitting data for a
longer duration of time and without much loss of energy resources. LoRaWAN has been designed as a
convention explicitly for the management of low energy consumption transmissions when Internet of
Things (IoT) devices on LPWAN [
21
,
22
]. For IoT users, LoRaWAN uses a novel network paradigm
for bidirectional connectivity, localization, and mobility management services [
23
]. It provides a new
framework for LPWAN execution for long-range communications. It has the potential to operate over
the ISM band (868 MHz and 900 MHz) with data rates ranging from 0.3 kbps to 50 kbps and network
coverage from 5 to 15 km [
24
–
26
]. Sigfox, similar to LoRaWAN, is a low-speed but low-power and
long-range solution for UAVs. It uses the same ISM band as LoRaWAN. One of the advantages of
Sigfox is that it supports open-sight up to 30 km of range.

Drones 2020,4, 65 4 of 14
Table 1. Comparison between the various communication technologies for FANETs.
Communication
Technology Standard/Service Category Spectrum Type Frequency/Medium Device Mobility Theoretical Data Rate Range
Indoor-Outdoor Latency
Wi-Fi
802.11 Unlicensed 2.4 GHz IR Yes Up to 2 Mbps 20–100 m
<5 ms
802.11a Unlicensed 5 GHz Yes Up to 54 Mbps 35–120 m
802.11b Unlicensed 2.4 GHz Yes Up to 11 Mbps 35–140 m
802.11n Unlicensed 2.4/5 GHz Yes Up to 600 Mbps 70–250 m
802.11g Unlicensed 2.4 GHz Yes Up to 54 Mbps 38–140 m
802.11ac Unlicensed 5 GHz Yes Up to 866.7 Mbps 35–120 m
ZigBee 802.15.4 Unlicensed 2.4 GHz Yes Up to 25 kbps 10–100 m 15 ms
Bluetooth V5 802.15.1 Unlicensed 2.4 GHz Yes Up to 2 Mbps 10–200 m 3 ms
LoRaWAN IEEE 802.15.4g Unlicensed 868 MHz, 915 MHz Yes Up to 50 kbps 05–15 km
Device Class Dependent
Sigfox - Unlicensed 868 MHz, 902 MHz Yes Up to 100 bps 03–30 km 2 s
NB-IoT
•LTE Cat NB1
•LTE Cat NB2 licensed 200 KHz Yes Up to 250 kbps 10–35 km 1.6–10 s
5G
•mMTC
•URLLC
•eMBB
licensed
•Sub-6 GHz
•MmWave for fixed access Yes Up to 1 Gbps Wide Area 1 ms
B5G
•mMTC
•URLLC
•eMBB
•Hybrid (URLLC +eMBB)
licensed
•Sub-6 GHz
•MmWave for fixed access Yes Up to 100 Gbps Wide Area 1 ms
6G
•MBRLLC
•mURLLC
•HCS
•MPS
licensed
•Sub-6 GHz
•MmWave for mobile access
•
Exploration of higher frequency
and THz bands (above 300 GHz)
•Non-RF (e.g., optical, VLC, etc.)
Yes Up to 1 Tbps Wide Area <1 ms

Drones 2020,4, 65 5 of 14
If the unlicensed wireless technologies are not capable of meeting the UAV throughput
requirements, traditional cellular communications can be used as a backhaul for providing data
transmission services in two sights. Narrow band Internet of Things (NB-IoT) is a LPWA standard
technology designed to provide connectivity and access to new services for a wide range of the
latest IoT devices. NB-IoT, especially in deep coverage, significantly improves user device power
consumption, system capacity, and spectrum efficiency. Moreover, as the later proposals in 5G have
made it conceivable to conceptualize cellular systems beyond 5G (B5G) and sixth-generation (6G),
able of unleashing the complete potential of copious, past-including autonomous administrations
as well as emerging trends. They give capacity extension methodologies to resolve the issue of
gigantic connectivity and give ultra-high throughput, indeed in extraordinary or crisis circumstances
where there may be shifting framework densities, transmission capacity as well as traffic pattern.
These technologies can moreover be valuable to FANETs by empowering UAVs to communicate
specifically with each other and at the same time with a fixed communication framework. Within the
same setting, the limited onboard processing capacity of small UAVs, storage, and battery imperatives
raises a number of concerns over the effective execution of complex assignments. Leveraging the
cloud storage facility offered by 5G to offload both computation and storage-intensive activities
from resource-constrained UAVs to remote cloud servers is an effective technique to overcome these
limitations. Furthermore, the deployment of UAVs as a flying base station (BS) with other physical
layering mechanisms such as massive MIMO, cognitive radios, mmWave, and others as a prerequisite,
is a promising approach to achieve data-hungry services [27].
The above discussions led to the conclusion that depending on the range and throughput
requirements, Bluetooth, ZigBee, Wi-Fi, LoRaWAN, and Sigfox can be considered, depending on the
range and throughput requirements [
28
]. 5G and 6G can be a more suitable choice if the coverage area
is large, together with high throughput demands. However, these technologies require the existing
telecommunications infrastructure.
3. Applications and Feasibility of the Wireless Technologies
The use of small UAVs for multiple insurgents, civilian, and commercial applications is expected
to produce good results when it comes to providing accurate and reliable data transfer. As shown
in Figure 2, some of the areas where FANETs can be used are search and rescue, mail and delivery,
traffic monitoring, precision agriculture, reconnaissance, and others.
Drones 2020, 4, x FOR PEER REVIEW 8 of 14
Figure 2. Advantages, key wireless technologies, applications, and challenges of flying ad-hoc
networks.
4. Challenges
4.1. Security and Privacy
The design consideration of small UAVs rarely addresses the security considerations [7]. This
vulnerability could adversely affect the network security and privacy, resulting in colossal damage
to the information exchange operations within the network. An intruder intending to harm the
FANET system has many options for carrying out malicious intentions. For example, the attacker can
transmit plenty of reservation requests, eavesdrop the control messages, and/or forge the
information. UAVs connected with Wi-Fi are considered to be more unsecure as opposed to cellular
networks due to unreliable links and poor security mechanisms [43]. The authors in [44], ascertained
that Wi-Fi-based UAVs were vulnerable to fundamental security attacks. Someone with an
appropriate transmitter could attach to a UAV and embed commands into a progressing session,
making it easy to interpret any UAV. In addition, UAVs can become a luring target for physical
attacks in the event that it hovers over a hostile environment, which is another aspect of security
concern in the UAV network [45–48]. In such instances, an attacker dissembles the captured UAV to
gain access to retrieve internal data via common interfaces or ports such as a USB.
Global positioning system (GPS) spoofing [49–54] is another major security threat affecting the
privacy of small UAVs in which UAV GPS signals are manipulated by an intruder. An adversary
generally transmits fake GPS signals to an intended UAV with a slightly higher power than the actual
GPS signals in this attack in order to trick the UAV into thinking that it is at another location. This
technique can therefore be used by the attacker to send the UAV to the desired predetermined area
where it can be effortlessly captured [55]. The attack environment used to exploit the GPS spoofing
vulnerability of the commercial drone of the 3D Robotics firm is presented in Figure 3. A laptop with
a virtual machine and a Linux operating system equipped with Ubuntu 14.04 and BladeRF X40 are
required to exploit the particular vulnerability of transmitting fake coordinates. This can, however,
be possible only if the necessary libraries have been designed to work with the BladeRF [56]. The
cooperative localization system must use the actual positions of neighboring UAVs and their
associated distances in order to avoid the GPS spoofing attack to help UAVs determine their desired
location.
Figure 2.
Advantages, key wireless technologies, applications, and challenges of flying ad-hoc networks.

Drones 2020,4, 65 6 of 14
3.1. Search and Rescue (SAR)
SAR missions are amongst the most popular aerial robotics driving applications. This is largely
due to UAVs’ unique features such as versatility, flexibility, and scalability in contrast with human
vehicles [
29
]. Furthermore, the UAVs are able to fly autonomously, access difficult terrain, and perform
tasks of data collection, which are impossible for human vehicles. The advent of FANETs has further
increased UAV participation in active search and rescue operations [
30
]. In the event of unexpected
natural disasters, hazardous gas intrusions, wildfires, avalanches, and the rapid identification of
missing persons, FANETs will serve as the first line of protection. In such scenarios, FANETs could
be deployed in the affected areas, in exchange for sending humanitarian aid that could be at risk.
UAVs were first used during the 2005 Hurricane Katrina search and rescue missions and later in the
2011 Fukushima and 2015 Nepal earthquake, respectively [31].
In [
32
], the authors proposed a modern search and rescue operations (SARO) strategy to search
for survivors following major disasters on the assumption that wireless communication network cells
are partly functional while taking advantage of the UAV-based network. These SAROs are based on
the notion that nearly all survivors should be equipped with handheld remote gadgets called User
Equipment (UEs), which function on the ground as human-based sensors. The control messages in
SAR operations include the exchange of task assignment, position and heading, and map information,
while the data messages involve either images or video streaming, requiring a minimum data rate
of 1 Mbps and 2 Mbps, respectively. In addition, the delay limits for these operations is about 50 ms
and 100 ms and covers small- to medium-sized areas. Thus, keeping these parameters in mind,
unlicensed (i.e., Wi-Fi and Bluetooth 5) technologies can be used for limited coverage areas and a
fewer number of nodes, whereas cellular technologies can be used for large coverage areas and mass
deployment of UAVs.
3.2. Mailing and Delivery
Package delivery is one of the most enticing UAV applications supported by major courier
companies for quick, cost-effective and efficient transportation of packages that weigh less than a UAV
maximum bearing load [
33
]. For example, Amazon reports that 83 percent of its packages weigh less
than 2.5 kg [
34
], while the average FedX package weighs less than 5 kg [
35
]. Moreover, the adoption of
UAVs is increasing rapidly due to the growing trend of online ordering in congested cities, especially in
the retail sector. Many major retailers and logistics companies are stepping up efforts to integrate small
UAVs into their transport systems to solve the problem of “last mail” delivery. The authors in [
36
]
illustrated the plans of large retailers and logistics companies as follows: DHL launched its drone
delivery service for express and emergency products and began the first automated drone delivery to
Juist Island in 2014; later on, DHL successfully made more than 100 deliveries in the Bavarian Alps
in early 2016 through its Parcelcopter 3.0 drone; UPS tested the delivery of a successful automated
drone in Florida in 2017 from the roof of a company electric vehicle; and through securing a U.S.
patent, Amazon created major competition to legalize its UAV distribution project called “Prime Air.”
Patent and Trademark Office are dropping packages from drones to consumers through the use
of parachutes.
Mailing and delivery operations require low throughputs for trajectory planning, however,
the coverage areas may be large. The communication range of unlicensed technologies is limited, so it
is therefore possible to use any appropriate licensed technology for mailing and delivery operations.
3.3. Traffic Monitoring
Roadway traffic surveillance is also a possible application where FANETs can replace the laborious
and complex infrastructures used for observations. UAVs are less costly than traditional traffic control
devices used on the roadside such as loop detectors, video surveillance cameras, and microwave
sensors [37]. Moreover, data obtained from detector technology is somewhat statistical in nature and

Drones 2020,4, 65 7 of 14
does not provide precise tracking of the individual vehicle path within the stream of traffic. It limits the
use of data obtained in the study of calibration, human driving behaviors, and simulation models [
38
].
Additionally, disasters can easily damage the fixed structures located along the road side used for
computing, communications, and electrical systems. Such shortcomings result in a complete lack of
the transport network capacity to track and gather data [
39
]. Alternatively, the FANETs that can track
and record accidents or perform traffic management statistics are an economically and socially viable
choice because of their 3D movement, high speed, and wide coverage.
In traffic monitoring, UAVs are involved in transmitting images and video streaming to the
control center in real-time; thus, licensed technologies will be a better choice. In addition, licensed
technologies make use of existing communication infrastructures, particularly in urban areas and can
operate without line-of-sight.
3.4. Precision Agriculture
Management of agriculture production includes the monitoring of crop health. Despite manned
aerial vehicles having been used in this sector over the decades, however, the new concept of
autonomous UAVs is considered more beneficial as they conduct field operations with greater precision
on smaller as well as wider fields [
40
]. High-resolution crop images can be taken with the aid of small
UAVs. The captured images are processed in order to produce relevant information, which can then be
used for future decision-making. Crop health is defined using data obtained from the color imaging
mapping of the normalized vegetation difference index (NDVI) [
41
]. These color images are usually
obtained through a multispectral high-definition camera installed on the UAVs. NDVIs are counted as
separating healthy from unhealthy plants, which is achieved by calculating the level of chlorophyll
in crops. It takes advantage of the knowledge to identify the area under greater stress. The decision
support engine (DSE) is responsible for taking the appropriate steps to process the task.
The coverage area in precision agriculture can be small or medium in size. Short-range wireless
technologies, particularly Wi-Fi, can be the most appropriate choice to meet the requirements in terms
of coverage, latency, and throughput in crop health monitoring.
3.5. Reconnaissance
For a long time, UAVs have been used for surveillance applications. However, with the advent
of FANETs, the idea of surveillance is supposed to be more revolutionized. UAV plays a key role in
reducing human intervention in patrolling a particular geographic location. Aerial surveillance tasks
may involve collecting battlefield information, mapping areas affected by earthquakes, and monitoring
law enforcement activities. Taking photographs of items distributed over large regions and areas
of interest can also be used in surveillance work. For example, a border surveillance UAV group
can detect not only unplanned humanitarian problems including weapons and drugs, but illegal
border crossings [
42
]. The collected information can then be analyzed and transferred directly to
the Intelligence Control Centers. However, data sensitivity calls for high precision and accuracy
for immediate intervention. All such surveillance missions are complex in nature and are usually
intolerant to false alarms.
Similar to search and rescue operations, in reconnaissance, unlicensed (i.e., Wi-Fi and Bluetooth 5)
technologies can be used for cases of limited coverage areas and fewer number of nodes connectivity,
whereas licensed technologies can be used for large coverage areas and mass deployment of UAVs.
4. Challenges
4.1. Security and Privacy
The design consideration of small UAVs rarely addresses the security considerations [
7
].
This vulnerability could adversely affect the network security and privacy, resulting in colossal
damage to the information exchange operations within the network. An intruder intending to harm the

Drones 2020,4, 65 8 of 14
FANET system has many options for carrying out malicious intentions. For example, the attacker can
transmit plenty of reservation requests, eavesdrop the control messages, and/or forge the information.
UAVs connected with Wi-Fi are considered to be more unsecure as opposed to cellular networks due to
unreliable links and poor security mechanisms [
43
]. The authors in [
44
], ascertained that Wi-Fi-based
UAVs were vulnerable to fundamental security attacks. Someone with an appropriate transmitter
could attach to a UAV and embed commands into a progressing session, making it easy to interpret
any UAV. In addition, UAVs can become a luring target for physical attacks in the event that it hovers
over a hostile environment, which is another aspect of security concern in the UAV network [
45
–
48
].
In such instances, an attacker dissembles the captured UAV to gain access to retrieve internal data via
common interfaces or ports such as a USB.
Global positioning system (GPS) spoofing [
49
–
54
] is another major security threat affecting the
privacy of small UAVs in which UAV GPS signals are manipulated by an intruder. An adversary
generally transmits fake GPS signals to an intended UAV with a slightly higher power than the
actual GPS signals in this attack in order to trick the UAV into thinking that it is at another location.
This technique can therefore be used by the attacker to send the UAV to the desired predetermined
area where it can be effortlessly captured [
55
]. The attack environment used to exploit the GPS
spoofing vulnerability of the commercial drone of the 3D Robotics firm is presented in Figure 3.
A laptop with a virtual machine and a Linux operating system equipped with Ubuntu 14.04 and
BladeRF X40 are required to exploit the particular vulnerability of transmitting fake coordinates.
This can, however, be possible only if the necessary libraries have been designed to work with the
BladeRF [
56
]. The cooperative localization system must use the actual positions of neighboring UAVs
and their associated distances in order to avoid the GPS spoofing attack to help UAVs determine their
desired location.
Drones 2020, 4, x FOR PEER REVIEW 9 of 14
Figure 3. Global positioning system (GPS) spoofing vulnerability for the commercial drone of the
company 3D Robotics [52].
4.2. Safety
FANETs deployed for various applications raise major safety issues, for example, crashing
UAVs could cause tremendous damage to property or humans on the ground. This could be the
result of a mid-air collisions, technological malfunction, or misuse by its operator [57,58]. Extreme
weather conditions such as turbulence, lightning, battery life, and lifting capability have caused
public property concerns about the failure of UAVs. In addition, there is also a significant risk of
airborne accidents, leading to widespread devastation due to the sharing of airspace with other
passenger planes in larger cities.
4.3. Energy Limitations
Limited onboard energy is one of the main limitations impeding the development of small
UAVs. The key issue with small UAVs is flight time, because small UAVs of the general domain use
standard onboard batteries that have a finite life time [59]. Additionally, it is hard to swap UAV
batteries during the flight. Completing the resource-hungry applications for the FANET system in a
timely fashion, is therefore a crucial task.
4.4. Storage and Computation Restrictions
The limited storage and computing capabilities mounted on small UAVs do not allow for
computational-intensive tasks to be performed locally [45]. Moreover, the data aggregated by the
small UAVs could be too large for the same UAV to process and store it onboard, as it engages in the
monitoring task [46]. It also requires high computing and storage capacity. In addition, performing
computationally intensive assignments may result in slower response times, which in turn can
impede the overall performance of FANETs.
4.5. Routing
Routing allows for the UAVs to collaborate and coordinate amongst themselves and set up an
optimal route for data transmission. Routing is the most challenging job in FANETs due to the unique
attributes of UAVs such as high mobility, 3D movement, and rapid topology changes [60–63]. In
addition, highly sensitive applications need FANETs to provide accurate, stable, and efficient data
transfer. To make the applications and services more persistent and active, it is therefore important
to develop and choose suitable routing protocols for FANETs. Network efficiency in terms of
throughput and response time are important parameters, which is based on the potency of the
algorithm running within the routing protocol.
Figure 3.
Global positioning system (GPS) spoofing vulnerability for the commercial drone of the
company 3D Robotics [52].
4.2. Safety
FANETs deployed for various applications raise major safety issues, for example, crashing UAVs
could cause tremendous damage to property or humans on the ground. This could be the result of
a mid-air collisions, technological malfunction, or misuse by its operator [
57
,
58
]. Extreme weather
conditions such as turbulence, lightning, battery life, and lifting capability have caused public property
concerns about the failure of UAVs. In addition, there is also a significant risk of airborne accidents,
leading to widespread devastation due to the sharing of airspace with other passenger planes in
larger cities.
4.3. Energy Limitations
Limited onboard energy is one of the main limitations impeding the development of small UAVs.
The key issue with small UAVs is flight time, because small UAVs of the general domain use standard
onboard batteries that have a finite life time [
59
]. Additionally, it is hard to swap UAV batteries during

Drones 2020,4, 65 9 of 14
the flight. Completing the resource-hungry applications for the FANET system in a timely fashion,
is therefore a crucial task.
4.4. Storage and Computation Restrictions
The limited storage and computing capabilities mounted on small UAVs do not allow for
computational-intensive tasks to be performed locally [
45
]. Moreover, the data aggregated by the
small UAVs could be too large for the same UAV to process and store it onboard, as it engages in the
monitoring task [
46
]. It also requires high computing and storage capacity. In addition, performing
computationally intensive assignments may result in slower response times, which in turn can impede
the overall performance of FANETs.
4.5. Routing
Routing allows for the UAVs to collaborate and coordinate amongst themselves and set up an
optimal route for data transmission. Routing is the most challenging job in FANETs due to the
unique attributes of UAVs such as high mobility, 3D movement, and rapid topology changes [
60
–
63
].
In addition, highly sensitive applications need FANETs to provide accurate, stable, and efficient data
transfer. To make the applications and services more persistent and active, it is therefore important to
develop and choose suitable routing protocols for FANETs. Network efficiency in terms of throughput
and response time are important parameters, which is based on the potency of the algorithm running
within the routing protocol.
4.6. Path Planning and Navigation
Unless UAVs collide with each other and with moving objects that appear stable or dynamic in the
flying space, FANETs cannot guarantee safe operation. Thus, path planning and navigation of multiple
UAVs have become a prime concern to efficiently accomplish the assigned task [
64
]. To prevent a
possible collision and ensure the safety of the whole system, a predictive method must be established
for path planning and navigation in order to find the best way to avoid collisions.
5. Open Research Topics
The research on FANETs is still in its infancy. As a flying platform, a UAV network may further
contribute to various services. For more guidance in the study, some open research topics are
mentioned below.
5.1. Aerial Blockchain
An emerging trend for adaptive security of privacy preferences in UAV communication networks
supported by 5G, B5G, and 6G is expected to be the aerial blockchain. The privacy and integrity
of data collected by UAVs can be assured using an aerial blockchain approach [
65
]. Furthermore,
the integration of blockchain and 5G/6G technologies make the UAV communication more secure
against cybersecurity vulnerabilities [
66
]. Blockchain-enabled UAV softwarization can also be used
to provide UAV network communication services with flexible, dynamic, and on-the-fly decision
capabilities [
67
]. Although numerous research efforts have been devoted to blockchain technology in
UAV networks, researchers have not yet explored blockchain-enabled UAV network softwarization [
67
].
5.2. High-Speed Backhaul Connectivity
To support high data rate services, backhaul networks in 6G need to manage the huge amount
of data to integrate the UAV networks with the core network. For high-speed backhaul connectivity,
optical fiber and FSO networks can be a potential solution here; however, any increase in the
performance of these networks is challenging due to the demand for exponential data growth [68].

Drones 2020,4, 65 10 of 14
5.3. Deep Reinforcement Learning
Since cellular technology is a key enabler for providing high-speed data communication services
to the swarm of UAVs in the sky, however, it enforces challenges like supporting mobility [
69
].
Deep-reinforcement learning techniques can be used to refine handover decisions dynamically to
ensure stable communication. In addition, deep-reinforcement learning methods may also be used to
find the optimal way to avoid collisions during real-time path planning and navigation [70,71].
5.4. Energy Harvesting Technologies
Limited battery power and limited weight restrictions with a short flight duration time of UAVs
is still a key factor in preventing the involvement of FANETs in a wide range of applications.
Charging UAVs using energy harvesting technologies can overcome the short flight duration
problem [72].
5.5. Virtualization of Unmanned Aerial Vehicles (UAV)-Enabled 5G Networks
UAVs can potentially be integrated into the Internet to leverage the cloud computing facility,
web technologies, and service-oriented infrastructures for enabling smart IoT applications [
73
].
Within the same settings, UAV resources can be virtualized and integrated into an interconnected
environment with other network resources. Therefore, in the future, efficient methods for the
virtualization of UAV-enabled 5G networks need to be developed.
6. Conclusions
A flying ad-hoc network (FANET) is a flying platform that controls the autonomous dynamic
movement of numerous UAVs, simply called drones. However, wireless communication systems
that connect multiple UAVs to a FANET system have the potential for further improvements.
Wireless communication systems that can be deployed quickly to functional FANETs in challenging
environments are currently in high demand. In addition, for long transmission range and high
data rate applications, traditional cellular communication systems can be used as a backhaul link.
The inclusion of 5G and 6G technologies will make UAV networks ultra-reliable and ubiquitous.
However, challenges such as security and privacy, limited onboard energy and restricted computational
capabilities confine the participation of FANETs in a wide range of applications. A perfect balance
between communication technologies, security schemes, and energy harvesting methods are required
to provide secure and efficient communication links with long flight times and minimal communication
latencies for different real-time applications. Therefore, in this article, key enabling technologies,
applications, challenges, and open research problems were thoroughly investigated.
Author Contributions:
Conceptualization, M.A.K. and F.N.; Methodology, M.A.K. and F.N.; Software, M.A.K. and
F.N.; Validation, M.A.K., F.N., and I.U.; Formal analysis, M.A.K., F.N., and I.U.; Investigation, M.A.K. and
F.N.; Resources, M.A.K. and A.A.-Z.; Data curation, M.A.K. and K.A.A.-D.; Writing—original draft preparation,
M.A.K.; F.N., K.A.A.-D., and A.A.-Z.; Writing—review and editing, M.A.K., A.A.-Z., and K.A.A.-D.; Visualization,
M.A.K., A.A.-Z., and K.A.A.-D.; Supervision, F.N. All authors have read and agreed to the published version of
the manuscript.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest.

Drones 2020,4, 65 11 of 14
Abbreviations
The following abbreviations are used in this manuscript.
UAV Unmanned Aerial Vehicle
FANETs Flying Ad-Hoc Networks
IMU Inertial Measurement Unit
GPS Global Positioning System
BS Base Station
FSO Free Space Optics
DSE Decision Support Engine
NDVI Normalized Vegetation Difference Index
6G Sixth-Generation
B5G Beyond Fifth-Generation
mmWave Millimeter Wave
SAR Search and Rescue
LPWAN Low-Power Wide Area Networks
MEC Multi-Access Edge Computing
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