642 research outputs found
Securing UAV Communications Via Trajectory Optimization
Unmanned aerial vehicle (UAV) communications has drawn significant interest
recently due to many advantages such as low cost, high mobility, and on-demand
deployment. This paper addresses the issue of physical-layer security in a UAV
communication system, where a UAV sends confidential information to a
legitimate receiver in the presence of a potential eavesdropper which are both
on the ground. We aim to maximize the secrecy rate of the system by jointly
optimizing the UAV's trajectory and transmit power over a finite horizon. In
contrast to the existing literature on wireless security with static nodes, we
exploit the mobility of the UAV in this paper to enhance the secrecy rate via a
new trajectory design. Although the formulated problem is non-convex and
challenging to solve, we propose an iterative algorithm to solve the problem
efficiently, based on the block coordinate descent and successive convex
optimization methods. Specifically, the UAV's transmit power and trajectory are
each optimized with the other fixed in an alternating manner until convergence.
Numerical results show that the proposed algorithm significantly improves the
secrecy rate of the UAV communication system, as compared to benchmark schemes
without transmit power control or trajectory optimization.Comment: Accepted by IEEE GLOBECOM 201
Physical layer security against eavesdropping in the internet of drones (IoD) based communication systems
rones or unmanned aerial vehicles (UAVs) communication technology, which has recently been
thoroughly studied and adopted by 3GPP standard (Release 15) due to its dynamic, flexible, and flying
nature, is expected to be an integral part of future wireless communications and Internet of drones
(IoD) applications. However, due to the unique transmission characteristics and nature of UAV systems
including broadcasting, dominant line of site and poor scattering, providing confidentiality for legitimate
receivers against unintended ones (eavesdroppers) appears to be a challenging goal to achieve in such
scenarios. Besides, the special features of UAVs represented by having limited power (battery-operated)
and precessing (light RAM and CPU capabilities), makes applying complex cryptography approaches
very challenging and inefficient for such systems. This motives the utilization of alternative approaches
enabled by physical layer security (PLS) concept for securing UAV-based systems. Techniques based
on PLS are deemed to be promising due to their ability to provide inherent secrecy that is complexity independent, where no matter what computational processing power the eavesdropper may have, there
is no way to decrypt the PLS algorithms. This work is dedicated to highlight and overview the latest
advances and state of art researches on the field of applying PLS to UAV systems in a unified and
structured manner. Particularity, it discusses and explains the different, possible PLS scenarios and
use cases of UAVs, which are categorized based on how the drone is utilized and employed in the
communication system setup. The main classified categories include the deployment of the flying, mobile
UAV as a 1) base station (BS), 2) user equipment (UE), 2) relay, or 4) jammer. Then, recommendations
and future open research issues are stated and discussed.No sponso
UAV Swarm-Enabled Aerial CoMP: A Physical Layer Security Perspective
Unlike aerial base station enabled by a single unmanned aerial vehicle (UAV),
aerial coordinated multiple points (CoMP) can be enabled by a UAV swarm. In
this case, the management of multiple UAVs is important. This paper considers
the power allocation strategy for a UAV swarm-enabled aerial network to enhance
the physical layer security of the downlink transmission, where an eavesdropper
moves following the trajectory of the swarm for better eavesdropping. Unlike
existing works, we use only the large-scale channel state information (CSI) and
maximize the secrecy throughput in a whole-trajectory-oriented manner. The
overall transmission energy constraint on each UAV and the total transmission
duration for all the legitimate users are considered. The non-convexity of the
formulated problem is solved by using max-min optimization with iteration. Both
the transmission power of desired signals and artificial noise (AN) are derived
iteratively. Simulation results are presented to validate the effectiveness of
our proposed power allocation algorithm and to show the advantage of aerial
CoMP by using only the large-scale CSI
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