From the 1 of 22 linked papers with an AI index.
22 papers
Radar-Aided Near-Field Beam Prediction via Beam Map Learning for XL-MIMO V2I Communications
Jiali Nie, Yu Han, Yuanhao Cui +3
The paper introduces a passive radar‑aided framework that predicts near‑field beams for XL‑MIMO vehicle‑to‑infrastructure links by learning a mapping from radar Bartlett spectra to…
CORF-GS: Real-Time Wireless Radiance Field Reconstruction via Coupled Optical-RF Gaussian Splatting
Jinya Zhang, Jiajia Guo, Chao-Kai Wen +1
Recent advances in 3D Gaussian Splatting (3DGS)-based wireless radiance field (WRF) reconstruction provide an efficient solution for wireless channel modeling. However, existing WR…
Multi-Modal Environment-Aware Beam Management for Massive MIMO: A Geometry-Driven Virtual Base Station Framework
Yijie Bian, Wei Guo, Jie Yang +4
High-frequency massive multiple-input multiple-output (MIMO) systems promise ultra-high data rates. However, efficient beam management remains challenging due to the prohibitive be…
Physics-Informed Path-Parametric Learning for Efficient and Lightweight CSI Feedback
Chunyu Ling, Jiajia Guo, Yiming Cui +4
Channel State Information (CSI) feedback is vital for high spectral efficiency in wireless systems, yet high-dimensional CSI introduce significant feedback overhead. Recent deep le…
Propagation-Consistent Wireless Environment Digital Twin Construction Under Sparse Measurements
Junjie Ai, Shurui Xu, Yanqing Ren +6
Digital twins (DTs) are promising for wireless deployment, optimization, and data generation, but building a propagation-faithful twin from sparse real measurements remains difficu…
Multimodal-NF: A Wireless Dataset for Near-Field Low-Altitude Sensing and Communications
Mengyuan Li, Qianfan Lu, Jiachen Tian +5
Environment-aware 6G wireless networks demand the deep integration of multimodal and wireless data. However, most existing datasets are confined to 2D terrestrial far-field scenari…