collaborators

6 papers

eess.SP2026

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models

Yunzhe Zhu, Xuewen Liao, Zhenzhen Gao +2

Channel knowledge maps (CKMs) are regarded as key enablers of environment-aware communications in future wireless networks, as they provide location-specific channel information by…

eess.SP2026

Towards Intelligent Low-Altitude Wireless Network Deployment: Differentiable Channel Knowledge Map Construction and Trajectory Design

Le Zhao, Zesong Fei, Wenge Shi +4

Channel knowledge map (CKM) has emerged as a promising technique to leverage prior propagation knowledge in low-altitude wireless networks (LAWNs), yet state-of-the-art grid-based…

eess.SP2026

A Scalable Cloud-Edge Collaborative CKM Construction Framework Enabled by a Foundation Prior Model

Sixu Xiao, Yong Zeng, Haotian Rong +1

Channel knowledge maps (CKMs) provide a site-specific, location-indexed knowledge base that supports environment-aware communications and sensing in 6G networks. In practical deplo…

eess.SP2026

BeamCKMDiff: Beam-Aware Channel Knowledge Map Construction via Diffusion Transformer

Le Zhao, Yining Wang, Xinyi Wang +2

Channel knowledge map (CKM) is emerging as a critical enabler for environment-aware 6G networks, offering a site-specific database to significantly reduce pilot overhead. However,…

eess.SP2026

Effective outdoor pathloss prediction: A multi-layer segmentation approach with weighting map

Yuan Gao, Tao Wen, Wenjing Xie +4

Predicting pathloss by considering the physical environment is crucial for effective wireless network planning. Traditional methods, such as ray tracing and model-based approaches,…

eess.SP2025

Channel Knowledge Map Construction via Physics-Inspired Diffusion Model Without Prior Observations

Yunzhe Zhu, Xuewen Liao, Zhenzhen Gao +2

The ability to construct channel knowledge map (CKM) with high precision is essential for environment awareness in 6G wireless systems. However, most existing CKM construction meth…