22 citations · 30 across the 20 of their papers we have counts for
10 papers · 1 filter
User-Centric Communication Service Provision for Edge-Assisted Mobile Augmented Reality
Conghao Zhou, Jie Gao, Shisheng Hu +3
Future 6G networks are envisioned to facilitate edge-assisted mobile augmented reality (MAR) via strengthening the collaboration between MAR devices and edge servers. In order to p…
Revolutionizing QoE-Driven Network Management with Digital Agents in 6G
Xuemin Shen, Xinyu Huang, Jianzhe Xue +3
In this article, we present a digital agent (DA)-assisted network management framework for future sixth generation (6G) networks considering user quality of experience (QoE). A nov…
Digital Twin-Assisted Robust and Adaptive Resource Slicing in LEO Satellite Networks
Mingcheng He, Huaqing Wu, Conghao Zhou +3
Resource slicing in low Earth orbit satellite networks (LSN) is essential to support diversified services. In this paper, we investigate a resource slicing problem in LSN to reserv…
User-centric Immersive Communications in 6G: A Data-oriented Framework via Digital Twin
Conghao Zhou, Shisheng Hu, Jie Gao +3
In this article, we present a novel user-centric service provision for immersive communications (IC) in 6G to deal with the uncertainty of individual user behaviors while satisfyin…
Meta Learning Based Adaptive Cooperative Perception in Nonstationary Vehicular Networks
Kaige Qu, Zixiong Qin, Weihua Zhuang
To accommodate high network dynamics in real-time cooperative perception (CP), reinforcement learning (RL) based adaptive CP schemes have been proposed, to allow adaptive switching…
When Digital Twin Meets Generative AI: Intelligent Closed-Loop Network Management
Xinyu Huang, Haojun Yang, Conghao Zhou +3
Generative artificial intelligence (GAI) and digital twin (DT) are advanced data processing and virtualization technologies to revolutionize communication networks. Thanks to the p…
Accuracy-Aware Cooperative Sensing and Computing for Connected Autonomous Vehicles
Xuehan Ye, Kaige Qu, Weihua Zhuang +1
To maintain high perception performance among connected and autonomous vehicles (CAVs), in this paper, we propose an accuracy-aware and resource-efficient raw-level cooperative sen…
Digital Twin Assisted Intelligent Network Management for Vehicular Applications
Kaige Qu, Weihua Zhuang
The emerging data-driven methods based on artificial intelligence (AI) have paved the way for intelligent, flexible, and adaptive network management in vehicular applications. To e…
Model-Assisted Learning for Adaptive Cooperative Perception of Connected Autonomous Vehicles
Kaige Qu, Weihua Zhuang, Qiang Ye +2
Cooperative perception (CP) is a key technology to facilitate consistent and accurate situational awareness for connected and autonomous vehicles (CAVs). To tackle the network reso…
Digital Twin-based 3D Map Management for Edge-assisted Device Pose Tracking in Mobile AR
Conghao Zhou, Jie Gao, Mushu Li +3
Edge-device collaboration has the potential to facilitate compute-intensive device pose tracking for resource-constrained mobile augmented reality (MAR) devices. In this paper, we…