5 papers
Inverse-Reinforcement Learning Enabled Digital Twin for Intent-based Drone Networks
Jiahao Wang, Ruimin Yang, Hanzhi Yu +2
In this paper, the problem of the trajectory design for an intent-based drone operating in resource-constrained, dynamic wireless network environments is studied. In the considered…
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…
Digital Network Twins for Next-generation Wireless: Creation, Optimization, and Challenges
Zifan Zhang, Zhiyuan Peng, Hanzhi Yu +2
Digital network twins (DNTs), by representing a physical network using a virtual model, offer significant benefits such as streamlined network development, enhanced productivity, a…
Contrastive Language-Image Pre-Training Model based Semantic Communication Performance Optimization
Shaoran Yang, Dongyu Wei, Hanzhi Yu +3
In this paper, a novel contrastive language-image pre-training (CLIP) model based semantic communication framework is designed. Compared to standard neural network (e.g.,convolutio…
Optimizing Wireless Resource Management and Synchronization in Digital Twin Networks
Hanzhi Yu, Yuchen Liu, Zhaohui Yang +2
In this paper, we investigate an accurate synchronization between a physical network and its digital network twin (DNT), which serves as a virtual representation of the physical ne…