642 research outputs found

    Securing UAV Communications Via Trajectory Optimization

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    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

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    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

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    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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