Federated Machine Learning for Intelligent IoT via Reconfigurable Intelligent Surface
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Abstract (arXiv)
Intelligent Internet-of-Things (IoT) will be transformative with the advancement of artificial intelligence and high-dimensional data analysis, shifting from "connected things" to "connected intelligence". This shall unleash the full potential of intelligent IoT in a plethora of exciting applications, such as self-driving cars, unmanned aerial vehicles, healthcare, robotics, and supply chain finance. These applications drive the need of developing revolutionary computation, communication and artificial intelligence technologies that can make low-latency decisions with massive real-time data. To this end, federated machine learning, as a disruptive technology, is emerged to distill intelligence from the data at network edge, while guaranteeing device privacy and data security. However, the limited communication bandwidth is a key bottleneck of model aggregation for federated machine learning over radio channels. In this article, we shall develop an over-the-air computation based communication-efficient federated machine learning framework for intelligent IoT networks via exploiting the waveform superposition property of a multi-access channel. Reconfigurable intelligent surface is further leveraged to reduce the model aggregation error via enhancing the signal strength by reconfiguring the wireless propagation environments.
Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Apr 2020.
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Citing papers per year: 2021: 6; 2022: 9; 2023: 4; 2024: 0; 2025: 2.
21 papers.
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- 2021Distributed Learning in Wireless Networks: Recent Progress and Future Challengescited by 125
- 2021Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applicationscited by 96
- 2022Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learningcited by 59
- 2021Fusion of Federated Learning and Industrial Internet of Things: A Surveycited by 28
- 2021Over-the-Air Decentralized Federated Learningcited by 18
- 2022Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networkscited by 15
- 2022Trustworthy Federated Learning via Blockchaincited by 15
- 2021Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challengescited by 12
- 2022Federated Learning and Meta Learning: Approaches, Applications, and Directionscited by 12
- 2022Over-the-Air Federated Learning via Second-Order Optimizationcited by 11
- 2023Over-the-Air Federated Learning and Optimizationcited by 10
- 2023Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networkscited by 7
9 more
- 2023Vertical Federated Learning over Cloud-RAN: Convergence Analysis and System Optimizationcited by 7
- 2022Differentially Private Federated Learning via Reconfigurable Intelligent Surfacecited by 5
- 2022A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detectioncited by 5
- 2023Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semanticscited by 5
- 2022Federated Reinforcement Learning for Real-Time Electric Vehicle Charging and Discharging Controlcited by 4
- 2021Reconfigurable Intelligent Surface Empowered Over-the-Air Federated Edge Learningcited by 2
- 2022Reconfigurable Intelligent Surface Enabled Spatial Multiplexing with Fully Convolutional Networkcited by 0
- 2025Task-Agnostic Federation over Decentralized Data: Research Landscape and Visionscited by 0
- 2025Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptationcited by 0
- 2025Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation14 Jul 2025
- 2025Task-Agnostic Federation over Decentralized Data: Research Landscape and Visions5 Mar 2025
- 2023Over-the-Air Federated Learning and Optimization16 Oct 2023
- 2023Vertical Federated Learning over Cloud-RAN: Convergence Analysis and System Optimization4 May 2023
- 2023Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networks9 Mar 2023
- 2023Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics3 Jan 2023
- 2022A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection2 Dec 2022
- 2022Federated Learning and Meta Learning: Approaches, Applications, and Directions24 Oct 2022
- 2022Federated Reinforcement Learning for Real-Time Electric Vehicle Charging and Discharging Control4 Oct 2022
- 2022Trustworthy Federated Learning via Blockchain13 Aug 2022
- 2022Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networks6 Jun 2022
- 2022Differentially Private Federated Learning via Reconfigurable Intelligent Surface31 Mar 2022
9 more
- 2022Over-the-Air Federated Learning via Second-Order Optimization29 Mar 2022
- 2022Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning24 Jan 2022
- 2022Reconfigurable Intelligent Surface Enabled Spatial Multiplexing with Fully Convolutional Network8 Jan 2022
- 2021Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications24 Nov 2021
- 2021Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges14 Nov 2021
- 2021Reconfigurable Intelligent Surface Empowered Over-the-Air Federated Edge Learning6 Sep 2021
- 2021Over-the-Air Decentralized Federated Learning15 Jun 2021
- 2021Distributed Learning in Wireless Networks: Recent Progress and Future Challenges5 Apr 2021
- 2021Fusion of Federated Learning and Industrial Internet of Things: A Survey4 Jan 2021
- 2021Distributed Learning in Wireless Networks: Recent Progress and Future Challengescited by 125
- 2021Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applicationscited by 96
- 2022Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learningcited by 59
- 2021Fusion of Federated Learning and Industrial Internet of Things: A Surveycited by 28
- 2021Over-the-Air Decentralized Federated Learningcited by 18
- 2022Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networkscited by 15
- 2022Trustworthy Federated Learning via Blockchaincited by 15
- 2021Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challengescited by 12
- 2022Federated Learning and Meta Learning: Approaches, Applications, and Directionscited by 12
- 2022Over-the-Air Federated Learning via Second-Order Optimizationcited by 11
- 2023Over-the-Air Federated Learning and Optimizationcited by 10
- 2023Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networkscited by 7
12 most cited of 21 All 21 (JSON)
- 2025Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation14 Jul 2025
- 2025Task-Agnostic Federation over Decentralized Data: Research Landscape and Visions5 Mar 2025
- 2023Over-the-Air Federated Learning and Optimization16 Oct 2023
- 2023Vertical Federated Learning over Cloud-RAN: Convergence Analysis and System Optimization4 May 2023
- 2023Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networks9 Mar 2023
- 2023Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics3 Jan 2023
- 2022A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection2 Dec 2022
- 2022Federated Learning and Meta Learning: Approaches, Applications, and Directions24 Oct 2022
- 2022Federated Reinforcement Learning for Real-Time Electric Vehicle Charging and Discharging Control4 Oct 2022
- 2022Trustworthy Federated Learning via Blockchain13 Aug 2022
- 2022Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networks6 Jun 2022
- 2022Differentially Private Federated Learning via Reconfigurable Intelligent Surface31 Mar 2022
12 newest of 21 All 21 (JSON)