395 research outputs found
Intelligent-Reflecting-Surface-Assisted UAV Communications for 6G Networks
In 6th-Generation (6G) mobile networks, Intelligent Reflective Surfaces
(IRSs) and Unmanned Aerial Vehicles (UAVs) have emerged as promising
technologies to address the coverage difficulties and resource constraints
faced by terrestrial networks. UAVs, with their mobility and low costs, offer
diverse connectivity options for mobile users and a novel deployment paradigm
for 6G networks. However, the limited battery capacity of UAVs, dynamic and
unpredictable channel environments, and communication resource constraints
result in poor performance of traditional UAV-based networks. IRSs can not only
reconstruct the wireless environment in a unique way, but also achieve wireless
network relay in a cost-effective manner. Hence, it receives significant
attention as a promising solution to solve the above challenges. In this
article, we conduct a comprehensive survey on IRS-assisted UAV communications
for 6G networks. First, primary issues, key technologies, and application
scenarios of IRS-assisted UAV communications for 6G networks are introduced.
Then, we put forward specific solutions to the issues of IRS-assisted UAV
communications. Finally, we discuss some open issues and future research
directions to guide researchers in related fields
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
Secure NOMA-Based UAV-MEC Network Towards a Flying Eavesdropper
Non-orthogonal multiple access (NOMA) allows multiple users to share link resource for higher spectrum efficiency. It can be applied to unmanned aerial vehicle (UAV) and mobile edge computing (MEC) networks to provide convenient offloading computing service for ground users (GUs) with large-scale access. However, due to the line-of-sight (LoS) of UAV transmission, the information can be easily eavesdropped in NOMA-based UAV-MEC networks. In this paper, we propose a secure communication scheme for the NOMA-based UAV-MEC system towards a flying eavesdropper. In the proposed scheme, the average security computation capacity of the system is maximized while guaranteeing a minimum security computation requirement for each GU. Due to the uncertainty of the eavesdropper’s position, the coupling of multi-variables and the non-convexity of the problem, we first study the worst security situation through mathematical derivation. Then, the problem is solved by utilizing successive convex approximation (SCA) and block coordinate descent (BCD) methods with respect to channel coefficient, transmit power, central processing unit (CPU) computation frequency, local computation and UAV trajectory. Simulation results show that the proposed scheme is superior to the benchmarks in terms of the system security computation performance
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