96 citations · 101 across the 5 of their papers we have counts for
6 papers · 1 filter
Pushing AI to Wireless Network Edge: An Overview on Integrated Sensing, Communication, and Computation towards 6G
Guangxu Zhu, Zhonghao Lyu, Xiang Jiao +5
Pushing artificial intelligence (AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelli…
Task-Oriented Over-the-Air Computation for Multi-Device Edge AI
Dingzhu Wen, Xiang Jiao, Peixi Liu +3
Departing from the classic paradigm of data-centric designs, the 6G networks for supporting edge AI features task-oriented techniques that focus on effective and efficient executio…
Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AI
Dingzhu Wen, Peixi Liu, Guangxu Zhu +4
This paper studies a new multi-device edge artificial-intelligent (AI) system, which jointly exploits the AI model split inference and integrated sensing and communication (ISAC) t…
Toward Ambient Intelligence: Federated Edge Learning with Task-Oriented Sensing, Computation, and Communication Integration
Peixi Liu, Guangxu Zhu, Shuai Wang +4
In this paper, we address the problem of joint sensing, computation, and communication (SC) resource allocation for federated edge learning (FEEL) via a concrete case study o…
Training Time Minimization for Federated Edge Learning with Optimized Gradient Quantization and Bandwidth Allocation
Peixi Liu, Jiamo Jiang, Guangxu Zhu +5
Training a machine learning model with federated edge learning (FEEL) is typically time-consuming due to the constrained computation power of edge devices and limited wireless reso…
RIS-Assisted Secure Transmission Exploiting Statistical CSI of Eavesdropper
Cen Liu, Chang Tian, Peixi Liu
We investigate the reconfigurable intelligent surface (RIS) assisted downlink secure transmission where only the statistical channel of eavesdropper is available. To handle the sto…