272 citations · 553 across the 23 of their papers we have counts for
23 papers
Analysis and Detection of RIS-based Spoofing in Integrated Sensing and Communication (ISAC)
Tingyu Shui, Po-Heng Chou, Walid Saad +1
Integrated sensing and communication (ISAC) is a key feature of next-generation 6G wireless systems, allowing them to achieve high data rates and sensing accuracy. While prior rese…
Continual Reinforcement Learning for Digital Twin Synchronization Optimization
Haonan Tong, Mingzhe Chen, Jun Zhao +4
This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base…
A Resilience Perspective on C-V2X Communication Networks under Imperfect CSI
Tingyu Shui, Walid Saad, Mingzhe Chen
Cellular vehicle-to-everything (C-V2X) networks provide a promising solution to improve road safety and traffic efficiency. One key challenge in such systems lies in meeting differ…
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…
A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks
Sihua Wang, Mingzhe Chen, Xuanlin Liu +3
In this paper, a joint task, spectrum, and transmit power allocation problem is investigated for a wireless network in which the base stations (BSs) are equipped with mobile edge c…
Delay Minimization for Federated Learning Over Wireless Communication Networks
Zhaohui Yang, Mingzhe Chen, Walid Saad +4
In this paper, the problem of delay minimization for federated learning (FL) over wireless communication networks is investigated. In the considered model, each user exploits limit…
UVeQFed: Universal Vector Quantization for Federated Learning
Nir Shlezinger, Mingzhe Chen, Yonina C. Eldar +2
Traditional deep learning models are trained at a centralized server using labeled data samples collected from end devices or users. Such data samples often include private informa…
Wireless Communications for Collaborative Federated Learning
Mingzhe Chen, H. Vincent Poor, Walid Saad +1
Internet of Things (IoT) services will use machine learning tools to efficiently analyze various types of data collected by IoT devices for inference, autonomy, and control purpose…
Meta-Reinforcement Learning for Trajectory Design in Wireless UAV Networks
Ye Hu, Mingzhe Chen, Walid Saad +2
In this paper, the design of an optimal trajectory for an energy-constrained drone operating in dynamic network environments is studied. In the considered model, a drone base stati…
Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks
Sihua Wang, Mingzhe Chen, Changchuan Yin +4
In this paper, the problem of minimizing energy and time consumption for task computation and transmission is studied in a mobile edge computing (MEC)-enabled balloon network. In t…
Distributed and Democratized Learning: Philosophy and Research Challenges
Minh N. H. Nguyen, Shashi Raj Pandey, Kyi Thar +4
Due to the availability of huge amounts of data and processing abilities, current artificial intelligence (AI) systems are effective in solving complex tasks. However, despite the…
Machine Learning for Predictive Deployment of UAVs with Multiple Access
Linyan Lu, Zhaohui Yang, Mingzhe Chen +2
In this paper, a machine learning based deployment framework of unmanned aerial vehicles (UAVs) is studied. In the considered model, UAVs are deployed as flying base stations (BS)…
Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms
Tengchan Zeng, Omid Semiari, Mohammad Mozaffari +3
Unmanned aerial vehicle (UAV) swarms must exploit machine learning (ML) in order to execute various tasks ranging from coordinated trajectory planning to cooperative target recogni…
Artificial Intelligence Aided Next-Generation Networks Relying on UAVs
Xiao Liu, Mingzhe Chen, Yuanwei Liu +3
Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments. In the AI-enabled UAV-aided wireless netw…
Gated Recurrent Units Learning for Optimal Deployment of Visible Light Communications Enabled UAVs
Yining Wang, Mingzhe Chen, Zhaohui Yang +3
In this paper, the problem of optimizing the deployment of unmanned aerial vehicles (UAVs) equipped with visible light communication (VLC) capabilities is studied. In the studied m…
A Joint Learning and Communications Framework for Federated Learning over Wireless Networks
Mingzhe Chen, Zhaohui Yang, Walid Saad +3
In this paper, the problem of training federated learning (FL) algorithms over a realistic wireless network is studied. In particular, in the considered model, wireless users execu…
Machine Learning for Wireless Connectivity and Security of Cellular-Connected UAVs
Ursula Challita, Aidin Ferdowsi, Mingzhe Chen +1
Cellular-connected unmanned aerial vehicles (UAVs) will inevitably be integrated into future cellular networks as new aerial mobile users. Providing cellular connectivity to UAVs w…