10 papers
Resource-Aware LLM Reasoning for Mobile Edge General Intelligence
Mingyi Luo, Ruichen Zhang, Xiangwang Hou +4
The rapid advancement of large language models (LLMs) has enabled an emergence of agentic artificial intelligence (AI) with powerful reasoning and autonomous decision-making capabi…
Split Federated Learning for Low-Altitude Wireless Networks: Joint Sensing, Communication, Computation, and Control Co-design
Xiangwang Hou, Xianghe Wang, Jiacheng Wang +4
Unmanned aerial vehicles (UAVs) with integrated sensing, communication, computation and control (ISC3) capabilities have become key enablers of next-generation wireless networks. F…
Efficient Resource Allocation for Multi-User and Multi-Target MIMO-OFDM Underwater ISAC
Wei Men, Longfei Zhao, Yong Liang Guan +3
Integrated sensing and communication (ISAC) technology is crucial for next-generation underwater networks. However, covering multiple users and targets and balancing sensing and co…
Is FISHER All You Need in The Multi-AUV Underwater Target Tracking Task?
Guanwen Xie, Jingzehua Xu, Ziqi Zhang +5
It is significant to employ multiple autonomous underwater vehicles (AUVs) to execute the underwater target tracking task collaboratively. However, it's pretty challenging to meet…
Energy-Efficient Federated Learning for Edge Real-Time Vision via Joint Data, Computation, and Communication Design
Xiangwang Hou, Jingjing Wang, Fangming Guan +3
Emerging real-time computer vision (CV) applications on wireless edge devices demand energy-efficient and privacy-preserving learning. Federated learning (FL) enables on-device tra…
Lightweight Federated Learning over Wireless Edge Networks
Xiangwang Hou, Jingjing Wang, Jun Du +3
With the exponential growth of smart devices connected to wireless networks, data production is increasing rapidly, requiring machine learning (ML) techniques to unlock its value.…