3 papers
eess.SP2026
Parametrized Sharing for Multi-Agent Hybrid DRL for Multiple Multi-Functional RISs-Aided Downlink NOMA Networks
Chi-Te Kuo, Li-Hsiang Shen, Jyun-Jhe Huang
Multi-functional reconfigurable intelligent surface (MF-RIS) is conceived to address the communication efficiency thanks to its extended signal coverage from its active RIS capabil…
cs.AI2025
Multi-Functional RIS-Enabled in SAGIN for IoT: A Hybrid Deep Reinforcement Learning Approach with Compressed Twin-Models
Li-Hsiang Shen, Jyun-Jhe Huang
A space-air-ground integrated network (SAGIN) for Internet of Things (IoT) network architecture is investigated, empowered by multi-functional reconfigurable intelligent surfaces (…
cs.LG2025
Federated Deep Reinforcement Learning for Energy Efficient Multi-Functional RIS-Assisted Low-Earth Orbit Networks
Li-Hsiang Shen, Jyun-Jhe Huang, Kai-Ten Feng +2
In this paper, a novel network architecture that deploys the multi-functional reconfigurable intelligent surface (MF-RIS) in low-Earth orbit (LEO) is proposed. Unlike traditional R…