mlsanityData to 14 Oct 2026

Over-The-Air Federated Learning Over Scalable Cell-free Massive MIMO

arXiv 2212.06482 ↗First posted 13 Dec 2022eess.SP cs.IT cs.LGcited by 2

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Abstract (arXiv)

Cell-free massive MIMO is emerging as a promising technology for future wireless communication systems, which is expected to offer uniform coverage and high spectral efficiency compared to classical cellular systems. We study in this paper how cell-free massive MIMO can support federated edge learning. Taking advantage of the additive nature of the wireless multiple access channel, over-the-air computation is exploited, where the clients send their local updates simultaneously over the same communication resource. This approach, known as over-the-air federated learning (OTA-FL), is proven to alleviate the communication overhead of federated learning over wireless networks. Considering channel correlation and only imperfect channel state information available at the central server, we propose a practical implementation of OTA-FL over cell-free massive MIMO. The convergence of the proposed implementation is studied analytically and experimentally, confirming the benefits of cell-free massive MIMO for OTA-FL.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 36 of its 50 references that are in the map. First posted on arXiv 13 Dec 2022.

Builds on

36 of 50 references.

References · 36

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
  2. 2019Advances and Open Problems in Federated Learningcited by 3,046
  3. 2019On the Convergence of FedAvg on Non-IID Datacited by 1,229
  4. 2019A Joint Learning and Communications Framework for Federated Learning over Wireless Networkscited by 263
  5. 2018Federated Learning via Over-the-Air Computationcited by 219
  6. 2018Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version)cited by 191
  7. 2019Federated Learning over Wireless Fading Channelscited by 183
  8. 2019Scheduling Policies for Federated Learning in Wireless Networkscited by 131
  9. 2020One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysiscited by 112
  10. 2019Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocationcited by 94
  11. 2020Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learningcited by 90
  12. 2020Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approachcited by 81
24 more
  1. 2020Over-the-Air Federated Learning from Heterogeneous Datacited by 73
  2. 2020Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edgecited by 71
  3. 2020Privacy For Free: Wireless Federated Learning Via Uncoded Transmission With Adaptive Power Controlcited by 63
  4. 2019On Analog Gradient Descent Learning over Multiple Access Fading Channelscited by 62
  5. 2019Device Scheduling with Fast Convergence for Wireless Federated Learningcited by 46
  6. 2020Blind Federated Edge Learningcited by 43
  7. 2019Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networkscited by 39
  8. 2020Energy-Efficient Resource Management for Federated Edge Learning with CPU-GPU Heterogeneous Computingcited by 39
  9. 2019Accelerating DNN Training in Wireless Federated Edge Learning Systemscited by 34
  10. 2020Federated Learning and Wireless Communicationscited by 27
  11. 2019Cell-Free Massive MIMO for Wireless Federated Learningcited by 25
  12. 2020Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learningcited by 24
  13. 2019Scalable Cell-Free Massive MIMO Systemscited by 23
  14. 2019Energy-Aware Analog Aggregation for Federated Learning with Redundant Datacited by 23
  15. 2021Communication-Efficient ADMM-based Federated Learningcited by 14
  16. 2020Communication Efficient Federated Learning over Multiple Access Channelscited by 11
  17. 2018Ubiquitous Cell-Free Massive MIMO Communicationscited by 8
  18. 2021Device Scheduling and Update Aggregation Policies for Asynchronous Federated Learningcited by 7
  19. 2021Robust Federated Learning via Over-The-Air Computationcited by 6
  20. 2021Cell-Free Massive MIMO for 6G Wireless Communication Networkscited by 4
  21. 2022Over-The-Air Federated Learning under Byzantine Attackscited by 4
  22. 2022Communication-Efficient Federated Learning over MIMO Multiple Access Channelscited by 4
  23. 2020The Road to 6G: Ten Physical Layer Challenges for Communications Engineerscited by 3
  24. 2022Improving Fairness for Cell-Free Massive MIMO Through Interference-Aware Massive Accesscited by 1

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Cited by year

Citing papers per year: 2024: 2.

2 papers.

  1. 2024Accelerating Energy-Efficient Federated Learning in Cell-Free Networks with Adaptive Quantizationcited by 1
  2. 2024Over-the-Air Federated Learning in Cell-Free MIMO with Long-term Power Constraintcited by 0