12 citations · 25 across the 24 of their papers we have counts for
24 papers
Brain-Inspired Decentralized Satellite Learning in Space Computing Power Networks
Peng Yang, Ting Wang, Haibin Cai +3
Satellite networks are able to collect massive space information with advanced remote sensing technologies, which is essential for real-time applications such as natural disaster m…
Towards Effective and Interpretable Semantic Communications
Youlong Wu, Yuanmin Shi, Shuai Ma +3
With the exponential surge in traffic data and the pressing need for ultra-low latency in emerging intelligence applications, it is envisioned that 6G networks will demand disrupti…
Federated Fine-Tuning for Pre-Trained Foundation Models Over Wireless Networks
Zixin Wang, Yong Zhou, Yuanming Shi +1
Pre-trained foundation models (FMs), with extensive number of neurons, are key to advancing next-generation intelligence services, where personalizing these models requires massive…
Task-oriented Over-the-air Computation for Edge-device Co-inference with Balanced Classification Accuracy
Xiang Jiao, Dingzhu Wen, Guangxu Zhu +3
Edge-device co-inference, which concerns the cooperation between edge devices and an edge server for completing inference tasks over wireless networks, has been a promising techniq…
Collaborative Edge AI Inference over Cloud-RAN
Pengfei Zhang, Dingzhu Wen, Guangxu Zhu +3
In this paper, a cloud radio access network (Cloud-RAN) based collaborative edge AI inference architecture is proposed. Specifically, geographically distributed devices capture rea…
Satellite Federated Edge Learning: Architecture Design and Convergence Analysis
Yuanming Shi, Li Zeng, Jingyang Zhu +3
The proliferation of low-earth-orbit (LEO) satellite networks leads to the generation of vast volumes of remote sensing data which is traditionally transferred to the ground server…