17 citations · 22 across the 10 of their papers we have counts for
3 papers · 1 filter
Optimizing Reinforcement Learning Training over Digital Twin Enabled Multi-fidelity Networks
Hanzhi Yu, Hasan Farooq, Julien Forgeat +4
In this paper, we investigate a novel digital network twin (DNT) assisted deep learning (DL) model training framework. In particular, we consider a physical network where a base st…
Multi-Task Learning as enabler for General-Purpose AI-native RAN
Hasan Farooq, Julien Forgeat, Shruti Bothe +2
The realization of data-driven AI-native architecture envisioned for 6G and beyond networks can eventually lead to multiple machine learning (ML) workloads distributed at the netwo…
A Digital Twin for Reconfigurable Intelligent Surface Assisted Wireless Communication
Baoling Sheen, Jin Yang, Xianglong Feng +1
Reconfigurable Intelligent Surface (RIS) has emerged as one of the key technologies for 6G in recent years, which comprise a large number of low-cost passive elements that can smar…