Spatial Deep Learning for Site-Specific Movement Optimization of Aerial Base Stations

no code implementations • 16 Dec 2023 • Jiangbin Lyu, Xu Chen, Jiefeng Zhang, Liqun Fu

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (ABSs) to provide wireless connectivity for ground users (GUs) in various emergency scenarios.

Energy-Efficient Cyclical Trajectory Design for UAV-Aided Maritime Data Collection in Wind

no code implementations • 2 Jun 2020 • Yifan Zhang, Jiangbin Lyu, Liqun Fu

We aim to minimize the UAV's energy consumption in completing the task by jointly optimizing the communication time scheduling among the buoys and the UAV's flight trajectory subject to wind effect, which is a non-convex problem and difficult to solve optimally.

Scheduling

Placement Optimization of Aerial Base Stations with Deep Reinforcement Learning

no code implementations • 19 Nov 2019 • Jin Qiu, Jiangbin Lyu, Liqun Fu

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (ABSs) to assist terrestrial infrastructure for keeping wireless connectivity in various emergency scenarios.

reinforcement-learning Reinforcement Learning (RL)