6 papers
Physics-informed Diffusion Models for Multi-scale Prediction of Reference Signal Received Power in Wireless Networks
Xiaoqian Qi, Haoye Chai, Yue Wang +2
The Reference Signal Received Power (RSRP) is a crucial factor that determines communication performance in mobile networks. Accurately predicting the RSRP can help network operato…
Denoising Refinement Diffusion Models for Simultaneous Generation of Multi-scale Mobile Network Traffic
Xiaoqian Qi, Haoye Chai, Sichang Liu +4
The planning, management, and resource scheduling of cellular mobile networks require joint estimation of mobile traffic across different layers and nodes. Mobile traffic generatio…
MobiGPT: A Foundation Model for Mobile Wireless Networks
Xiaoqian Qi, Haoye Chai, Yong Li
With the rapid development of mobile communication technologies, future mobile networks will offer vast services and resources for commuting, production, daily life, and entertainm…
Fed MobiLLM: Efficient Federated LLM Fine-Tuning over Heterogeneous Mobile Devices via Server Assisted Side-Tuning
Xingke Yang, Liang Li, Sicong Li +6
Collaboratively fine-tuning (FT) large language models (LLMs) over heterogeneous mobile devices fosters immense potential applications of personalized intelligence. However, such a…
Physics-driven AI for Channel Estimation in Cellular Network
Xiaoqian Qi, Haoye Chai, Yong Li
In cellular mobile networks, wireless channel quality (CQ) is a crucial factor in determining communication performance and user's network experience. Accurately predicting CQ base…
UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimization
Haoye Chai, Shiyuan Zhang, Xiaoqian Qi +2
Mobile traffic forecasting allows operators to anticipate network dynamics and performance in advance, offering substantial potential for enhancing service quality and improving us…