Reconfigurable intelligent surface and UAV-assisted communications: a deep reinforcement learning approach

The thesis carries out comprehensive optimization and evaluation of various DRL algorithms for several real-life applications including UAV's trajectory design, power allocation, data collection, wireless power transfer and RIS's phase shift matrix adjustment.<br><br>The thesis presents three major contributions.

Firstly, we design a new UAV-assisted Internet-of -things (IoT) system relying on the shortest flight path of the UAVs while maximising the amount of data collected from IoT devices. then, a DRL-based technique is conceived for finding