UAV Assisted

UAV-assisted communication and networking research focuses on optimizing the use of unmanned aerial vehicles (UAVs) to enhance various wireless systems, primarily aiming to improve data throughput, energy efficiency, and data freshness. Current research employs diverse approaches, including reinforcement learning (e.g., Q-learning, Proximal Policy Optimization), federated learning, and deep neural networks, to address challenges like dynamic network topologies, unreliable channels, and efficient data collection in scenarios such as IoT networks and vehicular networks. These advancements hold significant potential for improving the performance and reliability of wireless communication systems in diverse applications, particularly in areas with limited or unreliable terrestrial infrastructure.