IEEE - Aerospace and Electronic Systems - October 2022 - 23
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higher layers of the communication infrastructure, e.g., to
the edges. This allows for keeping the complexity of the
UAVs low, thus enabling network scalability. On the other
hand, it presents challenging demands on the design of the
UAV control [4], [5], [12]. Edge-aided solutions ask for a
re-design of the communication and collaboration architecture
between the UAVs. In this direction, preliminary
studies foresee that the sixth generation (6G) wireless networks
will integrate the UAV-based flying networks
within the cellular infrastructure, facilitating the connection
with clouds or edges with high reliability and lower
latency [13], [14]. But, differently from 6G nonterrestrial
networks, in the following, we focus on communications
for networks of UAVs rather than communications
through/enabled by UAVs (see [15], [16], [17]).
In this article, we deal with a network of autonomous
UAVs with low complexity that performs three main functional
tasks: 1) sensing, 2) learning, and 3) communication.
The UAVs observe some features of the environment
(sensing), then estimate their states (e.g., targets' positions
or some features of the surrounding) and learn which
actions should be taken through interactions and experience
(learning). In this sense, we refer to the UAV intelligence
(UAV-I) as the ability to process the information,
collaborate, and navigate, i.e., to learn a control policy
that can maximize some mission-related performance.
With sensing, we indicate the operation that allows UAVs
to collect information from the environment. Sensing can
be active, where each UAV interrogates the environment
with probing signals, or passive, where the sensors measure
some physical parameter. All the collected data are
then processed for inferring some useful features for the
considered application. For example, the UAVs estimate
the positions of the targets by collecting range and angle
measurements through onboard low-cost radars [12], or
they optimize their positions for reducing the risk of electromagnetic
field exposure [18].
The main contributions of this article can be summarized
as follows.
We provide an overview of architectures and signal
processing techniques for a network of UAVs
Figure 1.
Example oflocalization-based applications with heterogeneous networks ofUAVs. U2U links are represented with continuous lines, whereas
communication assisted by the cellular infrastructure is represented with dashed line.
OCTOBER 2022
IEEE A&E SYSTEMS MAGAZINE
23
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IEEE - Aerospace and Electronic Systems - October 2022
Table of Contents for the Digital Edition of IEEE - Aerospace and Electronic Systems - October 2022
Contents
IEEE - Aerospace and Electronic Systems - October 2022 - Cover1
IEEE - Aerospace and Electronic Systems - October 2022 - Cover2
IEEE - Aerospace and Electronic Systems - October 2022 - Contents
IEEE - Aerospace and Electronic Systems - October 2022 - 2
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