This paper investigates a learning-based approach autonomously and jointly optimizing the trajectory of unmanned aerial vehicle (UAV), phase shifts of ...
Aug 8, 2023 · This paper investigates a learning-based approach autonomously and jointly optimizing the trajectory of unmanned aerial vehicle (UAV), phase ...
This paper investigates a learning-based approach autonomously and jointly optimizing the trajectory of unmanned aerial vehicle (UAV), phase shifts of ...
This paper explored the learning-based optimization of UAV trajectory, RIS phase shifts, and FL aggregation weights for. FL in RIS-assisted UAV-enabled networks ...
Apr 15, 2024 · Some use deep learning. Heejae et al. [24] formulated an RIS-carried UAV federated learning model, proposed resource allocation in an RIS ...
Missing: Weighted | Show results with:Weighted
Jul 17, 2022 · A novel federated deep reinforcement learning (F-DRL) approach is developed to solve this challenging problem with one dynamic long-term ...
Federated Learning for RIS-Assisted UAV-Enabled Wireless Networks: Learning-Based Optimization for UAV Trajectory, RIS Phase Shifts and Weighted Aggregation.
The problem of maximizing the achievable data rate by using long short-term memory and federated learning is formulated and the method that consists of two ...
Missing: Weighted Aggregation.
This letter investigates machine learning approach for the joint optimal phase shift and beamforming in the reconfigurable intelligent surface (RIS) assisted ...
A Survey on Model-based, Heuristic, and Machine Learning Optimization Approaches in RIS-aided Wireless Networks · no code implementations • 25 Mar 2023 • Hao ...