56 citations · 127 across the 5 of their papers we have counts for
6 papers
Geometry-Aware Resource Allocation for Network-Level ISAC Systems
Xiao-Yang Wang, Luting Kong, Lei Cao +7
Network-level integrated sensing and communication (ISAC) is recognized as a transformative technology for next-generation mobile radio systems. By enabling collaboration among mul…
Improving Convergence for Semi-Federated Learning: An Energy-Efficient Approach by Manipulating Over-the-Air Distortion
Jingheng Zheng, Hui Tian, Wanli Ni +2
In this paper, we propose a hybrid learning framework that combines federated and split learning, termed semi-federated learning (SemiFL), in which over-the-air computation is util…
Semi-Federated Learning: Convergence Analysis and Optimization of A Hybrid Learning Framework
Jingheng Zheng, Wanli Ni, Hui Tian +3
Under the organization of the base station (BS), wireless federated learning (FL) enables collaborative model training among multiple devices. However, the BS is merely responsible…
Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networks
Wanli Ni, Jingheng Zheng, Hui Tian
Implementing existing federated learning in massive Internet of Things (IoT) networks faces critical challenges such as imbalanced and statistically heterogeneous data and device d…
Balancing Accuracy and Integrity for Reconfigurable Intelligent Surface-aided Over-the-Air Federated Learning
Jingheng Zheng, Hui Tian, Wanli Ni +2
Over-the-air federated learning (AirFL) allows devices to train a learning model in parallel and synchronize their local models using over-the-air computation. The integrity of Air…
QoS-Constrained Federated Learning Empowered by Intelligent Reflecting Surface
Jingheng Zheng, Wanli Ni, Hui Tian
This paper investigates the model aggregation process in an over-the-air federated learning (AirFL) system, where an intelligent reflecting surface (IRS) is deployed to assist the…