5 papers
Constructing and Evaluating Digital Twins: An Intelligent Framework for DT Development
Longfei Ma, Nan Cheng, Xiucheng Wang +4
The development of Digital Twins (DTs) represents a transformative advance for simulating and optimizing complex systems in a controlled digital space. Despite their potential, the…
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…
Effectively Heterogeneous Federated Learning: A Pairing and Split Learning Based Approach
Jinglong Shen, Xiucheng Wang, Nan Cheng +3
As a promising paradigm federated Learning (FL) is widely used in privacy-preserving machine learning, which allows distributed devices to collaboratively train a model while avoid…
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…