1 citations · 1 across the 8 of their papers we have counts for
9 papers
Large-Scale Bandwidth and Power Optimization for Multi-Modal Edge Intelligence Autonomous Driving
Xinrao Li, Tong Zhang, Shuai Wang +3
Edge intelligence autonomous driving (EIAD) offers computing resources in autonomous vehicles for training deep neural networks. However, wireless channels between the edge server…
Accelerating Federated Edge Learning via Topology Optimization
Shanfeng Huang, Zezhong Zhang, Shuai Wang +2
Federated edge learning (FEEL) is envisioned as a promising paradigm to achieve privacy-preserving distributed learning. However, it consumes excessive learning time due to the exi…
Integrated Sensing, Communication, and Computation Over-the-Air: MIMO Beamforming Design
Xiaoyang Li, Fan Liu, Ziqin Zhou +4
To support the unprecedented growth of the Internet of Things (IoT) applications, tremendous data need to be collected by the IoT devices and delivered to the server for further co…
Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling
Maojun Zhang, Guangxu Zhu, Shuai Wang +3
The popular federated edge learning (FEEL) framework allows privacy-preserving collaborative model training via frequent learning-updates exchange between edge devices and server.…
Data Partition and Rate Control for Learning and Energy Efficient Edge Intelligence
Xiaoyang Li, Shuai Wang, Guangxu Zhu +3
The rapid development of artificial intelligence together with the powerful computation capabilities of the advanced edge servers make it possible to deploy learning tasks at the w…
Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model
Guoliang Li, Shuai Wang, Jie Li +3
Human motion recognition (HMR) based on wireless sensing is a low-cost technique for scene understanding. Current HMR systems adopt support vector machines (SVMs) and convolutional…