Page 26 - Read Online

Page 21 Ayass et al. Intell Robot 2022;2(1):20-36 https://dx.doi.org/10.20517/ir.2021.07

[1]
their deployment advantages and mobility . There are two types of UAVs: fixed-wing and multi-rotor. The
first is better applied to military applications, while the second is applied to provide wireless coverage to
ground users. Moreover, UAVs are being applied in the following areas: efficient crop monitoring, delivery
of goods, intelligent monitoring of places for security, carrying out surveys of various locations, developing
a real-time map, coverage in telecommunications areas, and so on . In addition, UAVs can support many
[2]
[2]
Internet of Things (IoT) applications by providing real-time, accurate sensing/monitoring data .
UAVs as aerial base stations will be an essential module for future wireless technologies, as they can support
high data rate transmission for users located in disaster situations (e.g., after earthquakes, terrorist attacks,
and so on) and when there is no typical cellular infrastructure.

Cellular networks are considered to be an alternative for drone communications because most commercial
UAV systems employ IEEE 802.11 WLAN technology for sensor data, commands, and control, which
operates in the unlicensed spectrum raising issues such as reliability and security . Moreover, cellular
[3]
networks with UAV-mounted base stations can enhance cellular networks, offering services where the
traditional networks do not due to, e.g., costs. Besides all the applications cited above, UAVs as aerial base
stations could be promptly dispatched, cheaply maintained, and easily maneuvered. UAVs can be used as
end devices through cellular networks too . Thus, UAVs could benefit the current network infrastructure,
[4]
in terms of coverage, reliability, and security. There are also some ongoing standardization activities
[4]
(security monitoring, rescue services, etc.) with UAVs .

Some challenges to using UAVs as a main part of future mobile communications networks, serving as
mobile users or mobile base stations, are interference, special mobility, and handover management. Unlike
terrestrial networks, UAVs are mobile devices that move in a three-dimensional (3D) environment, which
[5]
further complicates mobility issues as moving to a new location would disconnect the current users.
Despite these problems, UAVs are becoming important for aerial communication . Although UAVs offer
[6,7]
numerous benefits for future wireless communication networks, their handover is a concern that must be
studied deeply .
[5]

The future generation wireless networks will be extremely dense and heterogeneous (with different
technologies), likely equipped with moving and flying BSs (base stations). This makes the existing network
planning techniques, which are mainly static and designed based on expensive field tests, not suitable for the
future wireless networks. The utilization of artificial intelligence (AI) techniques for network planning has
recently received interest in the research community. UAVs as aerial base stations for cellular networks are
commonly used to support wireless coverage. However, an intelligent handover method must be proposed
for UAV networks for when handover is triggered for a device moving to different UAVs.

One of the key premises in this development is the integration of AI into mobile communication networks.
In this context, AI and machine learning techniques are expected to provide solutions for the various
problems that have already been identified when UAVs are used for communication purposes such as
channel modeling, resource management, positioning, interference from the terrestrial node, and handover.

This paper is structured as follows. Flying ad hoc network (FANET) concepts are discussed in Section 2.
Section 3 outlines the FANET challenges and perspectives. The related works are presented in Section 4.
Section 5 describes the proposed handover management by the fuzzy system in detail and the results
obtained from the simulation. Section 6 summarizes the conclusion and makes suggestions for future work.