7 citations · 8 across the 9 of their papers we have counts for
9 papers
Knowledge-Driven Multi-Agent Reinforcement Learning for Computation Offloading in Cybertwin-Enabled Internet of Vehicles
Ruijin Sun, Xiao Yang, Nan Cheng +2
By offloading computation-intensive tasks of vehicles to roadside units (RSUs), mobile edge computing (MEC) in the Internet of Vehicles (IoV) can relieve the onboard computation bu…
Label-free Deep Learning Driven Secure Access Selection in Space-Air-Ground Integrated Networks
Zhaowei Wang, Zhisheng Yin, Xiucheng Wang +3
In Space-air-ground integrated networks (SAGIN), the inherent openness and extensive broadcast coverage expose these networks to significant eavesdropping threats. Considering the…
Distilling Knowledge from Resource Management Algorithms to Neural Networks: A Unified Training Assistance Approach
Longfei Ma, Nan Cheng, Xiucheng Wang +3
As a fundamental problem, numerous methods are dedicated to the optimization of signal-to-interference-plus-noise ratio (SINR), in a multi-user setting. Although traditional model-…
Interpretable and Secure Trajectory Optimization for UAV-Assisted Communication
Yunhao Quan, Nan Cheng, Xiucheng Wang +3
Unmanned aerial vehicles (UAVs) have gained popularity due to their flexible mobility, on-demand deployment, and the ability to establish high probability line-of-sight wireless co…
Scalable Resource Management for Dynamic MEC: An Unsupervised Link-Output Graph Neural Network Approach
Xiucheng Wang, Nan Cheng, Lianhao Fu +5
Deep learning has been successfully adopted in mobile edge computing (MEC) to optimize task offloading and resource allocation. However, the dynamics of edge networks raise two cha…
Digital Twin-Assisted Knowledge Distillation Framework for Heterogeneous Federated Learning
Xiucheng Wang, Nan Cheng, Longfei Ma +3
In this paper, to deal with the heterogeneity in federated learning (FL) systems, a knowledge distillation (KD) driven training framework for FL is proposed, where each user can se…
Digital Twin-Assisted Efficient Reinforcement Learning for Edge Task Scheduling
Xiucheng Wang, Longfei Ma, Haocheng Li +3
Task scheduling is a critical problem when one user offloads multiple different tasks to the edge server. When a user has multiple tasks to offload and only one task can be transmi…
Green Interference Based Symbiotic Security in Integrated Satellite-terrestrial Communications
Zhisheng Yin, Nan Cheng, Tom H. Luan +2
In this paper, we investigate secure transmissions in integrated satellite-terrestrial communications and the green interference based symbiotic security scheme is proposed. Partic…
Cybertwin-enabled 6G Space-air-ground Integrated Networks: Architecture, Open Issue, and Challenges
Zhisheng Yin, Tom H. Luan, Nan Cheng +2
Space-air-ground integrated network (SAGIN) is considered as a core requirement in emerging 6G networks, which integrates the terrestrial and non-terrestrial networks to reach the…