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cs.NI2025
FedABC: Attention-Based Client Selection for Federated Learning with Long-Term View
Wenxuan Ye, Xueli An, Junfan Wang +2
Native AI support is a key objective in the evolution of 6G networks, with Federated Learning (FL) emerging as a promising paradigm. FL allows decentralized clients to collaborativ…
cs.NI2024
Fast and Scalable Network Slicing by Integrating Deep Learning with Lagrangian Methods
Tianlun Hu, Qi Liao, Qiang Liu +2
Network slicing is a key technique in 5G and beyond for efficiently supporting diverse services. Many network slicing solutions rely on deep learning to manage complex and high-dim…
cs.NI2023
Advancing Federated Learning in 6G: A Trusted Architecture with Graph-based Analysis
Wenxuan Ye, Chendi Qian, Xueli An +2
Integrating native AI support into the network architecture is an essential objective of 6G. Federated Learning (FL) emerges as a potential paradigm, facilitating decentralized AI…