2 citations · 2 across the 7 of their papers we have counts for
8 papers
Survey-Free Radio Map Construction via HMM-Based Coarse-to-Fine Inference
Zheng Xing, Weibing Zhao, Guanghui Zhang +6
Traditional radio map construction methods mandate labor-intensive data collection and precise location labeling. To address these limitations, we propose a novel survey-free appro…
Annotation-Free Indoor Radio Mapping via Physics-Informed Trajectory Inference
Zheng Xing, Mengru Wu, Yi Zhang +6
Constructing indoor radio maps traditionally requires extensive site surveys with precise user-location labels, making the calibration process costly and time-consuming. Existing c…
Environment-Conditioned Diffusion Meta-Learning for Data-Efficient WiFi Localization
Jun Gao, Zheng Xing, Wenliang Lin +5
Fingerprinting-based localization often suffers from poor cross-environment generalization, especially when only a few labeled samples are available in the target environment. Exis…
EMS-FL: Federated Tuning of Mixture-of-Experts in Satellite-Terrestrial Networks via Expert-Driven Model Splitting
Angzi Xu, Zezhong Zhang, Zhi Liu +1
The rapid advancement of large AI models imposes stringent demands on data volume and computational resources. Federated learning, though designed to exploit distributed data and c…
RadioGen3D: 3D Radio Map Generation via Adversarial Learning on Large-Scale Synthetic Data
Junshen Chen, Angzi Xu, Zezhong Zhang +3
Radio maps are essential for efficient radio resource management in future 6G and low-altitude networks. While deep learning (DL) techniques have emerged as an efficient alternativ…
Self-Localizing MIMO Beam Mapping with Continuously Evolving Channel Memory
Wangqian Chen, Junting Chen, Shuguang Cui
Machine learning has greatly advanced data-driven channel modeling and resource optimization. However, most existing methods require accurately location-labeled datasets, which are…
Physics-Informed Neural Networks for MIMO Beam Map and Environment Reconstruction
Wangqian Chen, Junting Chen, Shuguang Cui
As communication networks evolve towards greater complexity (e.g., 6G and beyond), a deep understanding of the wireless environment becomes increasingly crucial. When explicit know…
Predictive Communications for Low-Altitude Networks
Junting Chen, Bowen Li, Hao Sun +2
The emergence of dense, mission-driven aerial networks supporting the low-altitude economy presents unique communication challenges, including extreme channel dynamics and severe c…