most citedToward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challenges

1 citations · 1 across the 1 of their papers we have counts for

collaborators

3 papers

cs.LG2025

RadioDiff-: Helmholtz Equation Informed Generative Diffusion Model for Multi-Path Aware Radio Map Construction

Xiucheng Wang, Qiming Zhang, Nan Cheng +4

In this paper, we propose a novel physics-informed generative learning approach, named RadioDiff-, for accurate and efficient multipath-aware radio map (RM) construction. As f…

cs.LG2024

RadioDiff: An Effective Generative Diffusion Model for Sampling-Free Dynamic Radio Map Construction

Xiucheng Wang, Keda Tao, Nan Cheng +4

Radio map (RM) is a promising technology that can obtain pathloss based on only location, which is significant for 6G network applications to reduce the communication costs for pat…

eess.SY2024★ 1 cited

Toward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challenges

Nan Cheng, Xiucheng Wang, Zan Li +3

This article presents a digital twin (DT)-enhanced reinforcement learning (RL) framework aimed at optimizing performance and reliability in network resource management, since the t…