13 citations · 22 across the 56 of their papers we have counts for
14 papers · 1 filter
RadioDiff-Inv2: Differentiable Diffusion Inversion under Location Drift from Sparse Noisy Measurements for Radio Map Estimation
Xiucheng Wang, Kailong Wang, Nan Cheng
Radio map (RM) estimation is a key enabler for environment-aware optimization in 6G wireless networks. In practice, RM construction increasingly relies on crowdsourced received sig…
RadioDiff-FS: Physics-Informed Manifold Alignment in Few-Shot Diffusion Models for High-Fidelity Radio Map Construction
Xiucheng Wang, Zixuan Guo, Nan Cheng
Radio maps (RMs) provide spatially continuous propagation characterizations essential for 6G network planning, but high-fidelity RM construction remains challenging. Rigorous elect…
Learn for Variation: Efficient AAV Trajectory Learning through a Differentiable Wireless World Model
Xiucheng Wang, Zhenye Chen, Nan Cheng +2
Autonomous aerial vehicles (AAVs) enable data collection for sixth-generation Internet-of-Things networks, but their trajectories couple nonlinear wireless rates with long-horizon…
A Tutorial on Learning-Based Radio Map Construction: Data, Paradigms, and Physics-Awareness
Xiucheng Wang, Yuhao Pan, Nan Cheng +9
Radio maps (RMs) provide the digital representation of the wireless propagation environment, mapping complex geographical and topological boundary conditions to critical spatial-sp…
NLoS Localization with Single Base Station Based on Radio Map
Jiajie Xu, Yifan Guo, Xiucheng Wang +2
Accurate outdoor localization in Non-Line-of-Sight (NLoS) environments remains a critical challenge for wireless communication and sensing systems. Existing methods, including posi…
RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation
Xiucheng Wang, Qiming Zhang, Nan Cheng
Accurate localization of non-cooperative signal sources in non-line-of-sight (NLoS) environments remains a critical challenge with a wide range of applications, including autonomou…
Differentiable Projection-based Learn to Optimize in Wireless Network-Part I: Convex Constrained (Non-)Convex Programming
Xiucheng Wang, Xuan Zhao, Nan Cheng
This paper addresses a class of (non-)convex optimization problems subject to general convex constraints, which pose significant challenges for traditional methods due to their inh…
Erasing Noise in Signal Detection with Diffusion Model: From Theory to Application
Xiucheng Wang, Peilin Zheng, Nan Cheng
In this paper, a signal detection method based on the denoise diffusion model (DM) is proposed, which outperforms the maximum likelihood (ML) estimation method that has long been r…
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…
Toward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challenges
Nan Cheng, Xiucheng Wang, Zan Li +3
This article presents a digital twin (DT)-enhanced reinforcement learning (RL) framework aimed at optimizing performance and reliability in network resource management, since the t…
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…
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…
On-Demand Resource Management for 6G Wireless Networks Using Knowledge-Assisted Dynamic Neural Networks
Longfei Ma, Nan Cheng, Xiucheng Wang +2
On-demand service provisioning is a critical yet challenging issue in 6G wireless communication networks, since emerging services have significantly diverse requirements and the ne…