123 citations · 378 across the 22 of their papers we have counts for
4 papers · 1 filter
Spatio-temporal Modeling for Large-scale Vehicular Networks Using Graph Convolutional Networks
Juntong Liu, Yong Xiao, Yingyu Li +3
The effective deployment of connected vehicular networks is contingent upon maintaining a desired performance across spatial and temporal domains. In this paper, a graph-based fram…
Towards Ubiquitous AI in 6G with Federated Learning
Yong Xiao, Guangming Shi, Marwan Krunz
With 5G cellular systems being actively deployed worldwide, the research community has started to explore novel technological advances for the subsequent generation, i.e., 6G. It i…
A Generative Learning Approach for Spatio-temporal Modeling in Connected Vehicular Network
Rong Xia, Yong Xiao, Yingyu Li +2
Spatio-temporal modeling of wireless access latency is of great importance for connected-vehicular systems. The quality of the molded results rely heavily on the number and quality…
Federated Orchestration for Network Slicing of Bandwidth and Computational Resource
Yingyu Li, Anqi Huang, Yong Xiao +3
Network slicing has been considered as one of the key enablers for 5G to support diversified IoT services and application scenarios. This paper studies the distributed network slic…