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

  • Khoi Khac Nguyen

Student thesis: Doctoral ThesisDoctor of Philosophy


This thesis proposes novel methods based on the deep reinforcement learning algorithms (DRL) for maximising the energy efficiency (EE), sum-rate in reconfigurable intelligent surface (RIS) and unmanned aerieal vehicles (UAV)-aided wireless communications. 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.

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
Date of AwardJul 2022
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SupervisorTrung Q. Duong (Supervisor)

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