
Using a UAV equipped with a directional movable antenna, controlled by a deep reinforcement learning algorithm, significantly improves the efficiency of data collection in backscatter sensor networks by optimizing antenna orientation and UAV trajectory.


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deep-reinforcement-learning-for-efficient-data-collection-in-backscatter-sensor-networks-using-a-uav-with-a-movable-antenna


Deep Reinforcement Learning for Efficient Data Collection in Backscatter Sensor Networks Using a UAV with a Movable Antenna


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This paper proposes a novel approach to enhance tracking and communication performance in integrated sensing and communication (ISAC) systems by utilizing a maneuverable bi-static configuration with airborne UAVs, optimizing their trajectories to minimize the tracking error while ensuring reliable communication.


adaptive-tracking-and-communication-using-a-maneuverable-bi-static-isac-system-with-airborne-uavs-


Adaptive Tracking and Communication Using a Maneuverable Bi-Static ISAC System with Airborne UAVs
