272 citations · 553 across the 23 of their papers we have counts for
7 papers · 1 filter
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges
Mingzhe Chen, Deniz Gündüz, Kaibin Huang +4
The next-generation of wireless networks will enable many machine learning (ML) tools and applications to efficiently analyze various types of data collected by edge devices for in…
Distributed Reinforcement Learning for Age of Information Minimization in Real-Time IoT Systems
Sihua Wang, Mingzhe Chen, Zhaohui Yang +4
In this paper, the problem of minimizing the weighted sum of age of information (AoI) and total energy consumption of Internet of Things (IoT) devices is studied. In the considered…
Lifelong Learning for Minimizing Age of Information in Internet of Things Networks
Zhenzhen Gong, Qimei Cui, Christina Chaccour +3
In this paper, a lifelong learning problem is studied for an Internet of Things (IoT) system. In the considered model, each IoT device aims to balance its information freshness and…
Optimization of User Selection and Bandwidth Allocation for Federated Learning in VLC/RF Systems
Chuanhong Liu, Caili Guo, Yang Yang +3
Limited radio frequency (RF) resources restrict the number of users that can participate in federated learning (FL) thus affecting FL convergence speed and performance. In this pap…
Meta-Reinforcement Learning for Reliable Communication in THz/VLC Wireless VR Networks
Yining Wang, Mingzhe Chen, Zhaohui Yang +4
In this paper, the problem of enhancing the quality of virtual reality (VR) services is studied for an indoor terahertz (THz)/visible light communication (VLC) wireless network. In…
Artificial Intelligence Driven UAV-NOMA-MEC in Next Generation Wireless Networks
Zhong Yang, Mingzhe Chen, Xiao Liu +4
Driven by the unprecedented high throughput and low latency requirements in next-generation wireless networks, this paper introduces an artificial intelligence (AI) enabled framewo…
Federated Learning for 6G: Applications, Challenges, and Opportunities
Zhaohui Yang, Mingzhe Chen, Kai-Kit Wong +2
Traditional machine learning is centralized in the cloud (data centers). Recently, the security concern and the availability of abundant data and computation resources in wireless…