2 citations · 2 across the 14 of their papers we have counts for
14 papers
Performance Analysis of End-to-End LEO Satellite-Aided Shore-to-Ship Communications: A Stochastic Geometry Approach
Xu Hu, Bin Lin, Xiao Lu +4
Low Earth orbit (LEO) satellite networks have shown strategic superiority in maritime communications, assisting in establishing signal transmissions from shore to ship through spac…
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…
RadioMamba: Breaking the Accuracy-Efficiency Trade-off in Radio Map Construction via a Hybrid Mamba-UNet
Honggang Jia, Nan Cheng, Xiucheng Wang +4
Radio map (RM) has recently attracted much attention since it can provide real-time and accurate spatial channel information for 6G services and applications. However, current deep…
RadioDiff-3D: A 3D3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communication
Xiucheng Wang, Qiming Zhang, Nan Cheng +5
Radio maps (RMs) serve as a critical foundation for enabling environment-aware wireless communication, as they provide the spatial distribution of wireless channel characteristics.…
Toward Low-Altitude Airspace Management and UAV Operations: Requirements, Architecture and Enabling Technologies
Guiyang Luo, Jinglin Li, Qixun Zhang +6
The low-altitude economy (LAE) is rapidly advancing toward intelligence, connectivity, and coordination, bringing new challenges in dynamic airspace management, unmanned aerial veh…
An Enhanced Dual-Currency VCG Auction Mechanism for Resource Allocation in IoV: A Value of Information Perspective
Wei Wang, Nan Cheng, Conghao Zhou +5
The Internet of Vehicles (IoV) is undergoing a transformative evolution, enabled by advancements in future 6G network technologies, to support intelligent, highly reliable, and low…
ALWNN Empowered Automatic Modulation Classification: Conquering Complexity and Scarce Sample Conditions
Yunhao Quan, Chuang Gao, Nan Cheng +4
In Automatic Modulation Classification (AMC), deep learning methods have shown remarkable performance, offering significant advantages over traditional approaches and demonstrating…
A Channel-Triggered Backdoor Attack on Wireless Semantic Image Reconstruction
Jialin Wan, Jinglong Shen, Nan Cheng +5
This paper investigates backdoor attacks in image-oriented semantic communications. The threat of backdoor attacks on symbol reconstruction in semantic communication (SemCom) syste…
User-centric Service Provision for Edge-assisted Mobile AR: A Digital Twin-based Approach
Conghao Zhou, Jie Gao, Yixiang Liu +3
Future 6G networks are envisioned to support mobile augmented reality (MAR) applications and provide customized immersive experiences for users via advanced service provision. In t…
GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV Network
Yuhao Pan, Xiucheng Wang, Zhiyao Xu +3
Unmanned Aerial Vehicles (UAVs), due to their low cost and high flexibility, have been widely used in various scenarios to enhance network performance. However, the optimization of…
Structural Knowledge-Driven Meta-Learning for Task Offloading in Vehicular Networks with Integrated Communications, Sensing and Computing
Ruijin Sun, Yao Wen, Nan Cheng +3
Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computin…
Knowledge-Driven Deep Learning Paradigms for Wireless Network Optimization in 6G
Ruijin Sun, Nan Cheng, Changle Li +2
In the sixth-generation (6G) networks, newly emerging diversified services of massive users in dynamic network environments are required to be satisfied by multi-dimensional hetero…
Imperfect Digital Twin Assisted Low Cost Reinforcement Training for Multi-UAV Networks
Xiucheng Wang, Nan Cheng, Longfei Ma +3
Deep Reinforcement Learning (DRL) is widely used to optimize the performance of multi-UAV networks. However, the training of DRL relies on the frequent interactions between the UAV…
Mobile Metaverse: A Road Map from Metaverse to Metavehicles
Yilong Hui, Gaosheng Zhao, Nan Cheng +2
With the rapid development of communication technologies and extended reality (XR), the services and applications of the Metaverse are gradually entering our lives. However, the cu…