6 research outputs found
Full-Dimensional Rate Enhancement for UAV-Enabled Communications via Intelligent Omni-Surface
This paper investigates the achievable rate maximization problem of a
downlink unmanned aerial vehicle (UAV)-enabled communication system aided by an
intelligent omni-surface (IOS). Different from the state-of-the-art
reconfigurable intelligent surface (RIS) that only reflects incident signals,
the IOS can simultaneously reflect and transmit the signals, thereby providing
full-dimensional rate enhancement. To tackle such a problem, we formulate it by
jointly optimizing the IOS's phase shift and the UAV trajectory. Although it is
difficult to solve it optimally due to its non-convexity, we propose an
efficient iterative algorithm to obtain a high-quality suboptimal solution.
Simulation results show that the IOS-assisted UAV communications can achieve
more significant improvement in achievable rates than other benchmark schemes.Comment: 6 pages, 5 figure
Energy-Efficient UAV Communications in the Presence of Wind: 3D Modeling and Trajectory Design
The rapid development of unmanned aerial vehicle (UAV) technology provides
flexible communication services to terrestrial nodes. Energy efficiency is
crucial to the deployment of UAVs, especially rotary-wing UAVs whose propulsion
power is sensitive to the wind effect. In this paper, we first derive a
three-dimensional (3D) generalised propulsion energy consumption model (GPECM)
for rotary-wing UAVs under the consideration of stochastic wind modeling and 3D
force analysis. Based on the GPECM, we study a UAV-enabled downlink
communication system, where a rotary-wing UAV flies subject to stochastic wind
disturbance and provides communication services for ground users (GUs). We aim
to maximize the energy efficiency (EE) of the UAV by jointly optimizing the 3D
trajectory and user scheduling among the GUs based on the GPECM. We formulate
the problem as stochastic optimization, which is difficult to solve due to the
lack of real-time wind information. To address this issue, we propose an
offline-based online adaptive (OBOA) design with two phases, namely, an offline
phase and an online phase. In the offline phase, we average the wind effect on
the UAV by leveraging stochastic programming (SP) based on wind statistics;
then, in the online phase, we further optimize the instantaneous velocity to
adapt the real-time wind. Simulation results show that the optimized
trajectories of the UAV in both two phases can better adapt to the wind in
changing speed and direction, and achieves a higher EE compared with the
windless scheme. In particular, our proposed OBOA design can be applied in the
scenario with dramatic wind changes, and makes the UAV adjust its velocity
dynamically to achieve a better performance in terms of EE.Comment: 31 pages, 13 figure
UAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory Optimization
In this paper, a UAV is deployed as a flying base station to collect data
from time-constrained IoT devices and then transfer the data to a ground
gateway (GW). In general, the latency constraint at IoT users and the limited
storage capacity of UAV highly hinder practical applications of UAV-assisted
IoT networks. In this paper, full-duplex (FD) technique is adopted at the UAV
to overcome these challenges. In addition, half-duplex (HD) scheme for
UAV-based relaying is also considered to provide a comparative study between
two modes. In this context, we aim at maximizing the number of served IoT
devices by jointly optimizing bandwidth and power allocation, as well as the
UAV trajectory, while satisfying the requested timeout (RT) requirement of each
device and the UAV's limited storage capacity. The formulated optimization
problem is troublesome to solve due to its non-convexity and combinatorial
nature. Toward appealing applications, we first relax binary variables into
continuous values and transform the original problem into a more
computationally tractable form. By leveraging inner approximation framework, we
derive newly approximated functions for non-convex parts and then develop a
simple yet efficient iterative algorithm for its solutions. Next, we attempt to
maximize the total throughput subject to the number of served IoT devices.
Finally, numerical results show that the proposed algorithms significantly
outperform benchmark approaches in terms of the number of served IoT devices
and the amount of collected data.Comment: 30 pages, 11 figure
Optimization and Communication in UAV Networks
UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects