6 papers · 1 filter
A Foundation Model for Large-Scale Wireless Network Planning , Operation and Optimization
Xinyu Qin, Wenqiang Pu, Hongcheng Dong +6
Wireless cellular networks provide critical infrastructure for communication, transportation and industry, making reliable connectivity essential to modern society. Delivering this…
Point-Cloud-Assistant Localized Statistical Channel Prediction by Tangent Gaussian Splatting
Ye Xue, Yiheng Wang, Xinhua Shao +3
Accurate, site-specific channel information is crucial for optimizing next-generation wireless networks. Among various approaches, localized statistical channel modeling (LSCM), wh…
A Measurement Report Data-Driven Framework for Localized Statistical Channel Modeling
Xinyu Qin, Ye Xue, Qi Yan +3
Localized statistical channel modeling (LSCM) is crucial for effective performance evaluation in digital twin-assisted network optimization. Solely relying on the multi-beam refere…
Multi-Modal Neural Radio Radiance Field for Localized Statistical Channel Modelling
Yiheng Wang, Shutao Zhang, Ye Xue +1
This paper presents MM-LSCM, a self-supervised multi-modal neural radio radiance field framework for localized statistical channel modeling (LSCM) for next-generation network optim…
RadCloudSplat: Scatterer-Driven 3D Gaussian Splatting with Point-Cloud Priors for Radiomap Extrapolation
Yiheng Wang, Ye Xue, Shutao Zhang +2
A radiomap represents the spatial distribution of wireless signal strength, which is critical for applications like network optimization. However, constructing a radiomap relies on…
Riemannian Low-Rank Model Compression for Federated Learning with Over-the-Air Aggregation
Ye Xue, Vincent Lau
Low-rank model compression is a widely used technique for reducing the computational load when training machine learning models. However, existing methods often rely on relaxing th…