Reconfigurable Intelligent Surface-assisted Multi-UAV Networks: Efficient Resource Allocation with Deep Reinforcement Learning
In this paper, we propose reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicles (UAVs) networks that can utilise both advantages of UAV's agility and RIS's reflection for enhancing the network's performance. To aim at maximising the energy efficiency (EE) of the considered networks, we jointly optimise the power allocation of the UAVs and the phase-shift matrix of the RIS. A deep reinforcement learning (DRL) approach is proposed for solving the continuous optimisation problem with time-varying channels in a centralised fashion. Moreover, a parallel learning approach is also proposed for reducing the information transmission requirement of the centralised approach. Numerical results show a significant improvement of our proposed schemes compared with the conventional approaches in terms of EE, flexibility, and processing time. Our proposed DRL methods for RIS-assisted UAV networks can be used for real-time applications due to their capability of instant decision-making and handling the time-varying channel with the dynamic environmental setting.
Code (0)
등록된 구현이 없습니다.
Tasks
Decision MakingDeep Reinforcement LearningReinforcement Learning (RL)Similar Papers 제목 키워드 기반
Pathloss modeling of reconfigurable intelligent surface assisted THz wireless systems
This paper presents an analytical pathloss model for reconfigurable intelligent surface (RIS) assisted terahertz (THz) wireless systems. Specifically, the model accommodates both the THz link and the RIS particularities.…
Ergodic capacity analysis of reconfigurable intelligent surface assisted wireless systems
This paper presents the analytic framework for evaluating the ergodic capacity (EC) of the reconfigurable intelligent surface (RIS) assisted systems. Moreover, high-signal-to-noise-ratio and high-number of reflection uni…
Reconfigurable Intelligent Surface -Assisted Ambient Backscatter Communications -- Experimental Assessment
Sixth generation (6G) mobile networks may include new passive technologies, such as ambient backscatter communication or the use of reconfigurable intelligent surfaces, to avoid the emission of waves and the correspondin…
TAGPersonalized Over-the-Air Federated Learning with Personalized Reconfigurable Intelligent Surfaces
Over-the-air federated learning (OTA-FL) provides bandwidth-efficient learning by leveraging the inherent superposition property of wireless channels. Personalized federated learning balances performance for users with d…
Federated LearningMulti-Task LearningPersonalized Federated LearningTwo-Stage Resource Allocation in Reconfigurable Intelligent Surface Assisted Hybrid Networks via Multi-Player Bandits
This paper considers a resource allocation problem where several Internet-of-Things (IoT) devices send data to a base station (BS) with or without the help of the reconfigurable intelligent surface (RIS) assisted cellula…
Thompson Sampling