5 papers
PEMNet: Towards Autonomous and Enhanced Environment-Aware Mobile Networks
Lei Li, Yanqing Xu, Ye Xue +4
With 5G deployment and the evolution toward 6G, mobile networks must make decisions in highly dynamic environments under strict latency, energy, and spectrum constraints. Achieving…
RF-LSCM: Pushing Radiance Fields to Multi-Domain Localized Statistical Channel Modeling for Cellular Network Optimization
Bingsheng Peng, Shutao Zhang, Xi Zheng +3
Accurate localized wireless channel modeling is a cornerstone of cellular network optimization, enabling reliable prediction of network performance during parameter tuning. Localiz…
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…
ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-k-Cut Problems
Yeqing Qiu, Ye Xue, Akang Wang +3
The Max-k-Cut problem is a fundamental combinatorial optimization challenge that generalizes the classic NP-complete Max-Cut problem. While relaxation techniques are commonly emplo…