mlsanityData to 14 Oct 2026

A Survey on Over-the-Air Computation

arXiv 2210.11350 ↗First posted 20 Oct 2022cs.IT cs.AI eess.SPcited by 21

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Abstract (arXiv)

Communication and computation are often viewed as separate tasks. This approach is very effective from the perspective of engineering as isolated optimizations can be performed. However, for many computation-oriented applications, the main interest is a function of the local information at the devices, rather than the local information itself. In such scenarios, information theoretical results show that harnessing the interference in a multiple access channel for computation, i.e., over-the-air computation (OAC), can provide a significantly higher achievable computation rate than separating communication and computation tasks. Moreover, the gap between OAC and separation in terms of computation rate increases with more participating nodes. Given this motivation, in this study, we provide a comprehensive survey on practical OAC methods. After outlining fundamentals related to OAC, we discuss the available OAC schemes with their pros and cons. We provide an overview of the enabling mechanisms for achieving reliable computation in the wireless channel. Finally, we summarize the potential applications of OAC and point out some future directions.

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 96 of its 270 references that are in the map. First posted on arXiv 20 Oct 2022.

Builds on

96 of 270 references.

References · 96

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
  2. 2018signSGD: Compressed Optimisation for Non-Convex Problemscited by 571
  3. 2018Split learning for health: Distributed deep learning without sharing raw patient datacited by 395
  4. 2020SplitFed: When Federated Learning Meets Split Learningcited by 310
  5. 2018Distributed learning of deep neural network over multiple agentscited by 279
  6. 2018Federated Learning via Over-the-Air Computationcited by 219
  7. 2018Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version)cited by 191
  8. 2019Federated Learning over Wireless Fading Channelscited by 183
  9. 2022Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communicationscited by 175
  10. 2021Distributed Learning in Wireless Networks: Recent Progress and Future Challengescited by 129
  11. 2020One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysiscited by 112
  12. 2018Wireless Network Intelligence at the Edgecited by 92
38 more
  1. 2020The Kolmogorov-Arnold representation theorem revisitedcited by 89
  2. 2019Detailed comparison of communication efficiency of split learning and federated learningcited by 77
  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. 2022Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learningcited by 59
  6. 2022Vertical Federated Learning: Challenges, Methodologies and Experimentscited by 55
  7. 2020Wireless Federated Learning with Local Differential Privacycited by 52
  8. 2020Blind Federated Edge Learningcited by 43
  9. 2020Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approachcited by 33
  10. 2021Federated Edge Learning with Misaligned Over-The-Air Computationcited by 30
  11. 2020Convergence of Federated Learning over a Noisy Downlinkcited by 29
  12. 2019Over-the-Air Computation Systems: Optimization, Analysis and Scaling Lawscited by 27
  13. 2021Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregationcited by 22
  14. 2022Joint Device Selection and Power Control for Wireless Federated Learningcited by 20
  15. 2020Decentralized SGD with Over-the-Air Computationcited by 16
  16. 2021Edge Federated Learning Via Unit-Modulus Over-The-Air Computationcited by 16
  17. 2022Semi-Decentralized Federated Learning with Collaborative Relayingcited by 16
  18. 2022Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networkscited by 15
  19. 2021Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?cited by 14
  20. 2021Turning Channel Noise into an Accelerator for Over-the-Air Principal Component Analysiscited by 14
  21. 2021Accelerated Gradient Descent Learning over Multiple Access Fading Channelscited by 14
  22. 2022Random Orthogonalization for Federated Learning in Massive MIMO Systemscited by 14
  23. 2021Over-the-Air Computation via Reconfigurable Intelligent Surfacecited by 13
  24. 2021Distributed Learning over a Wireless Network with FSK-Based Majority Votecited by 13
  25. 2016Over-the-air Function Computation in Sensor Networkscited by 11
  26. 2021Hierarchical Over-the-Air Federated Edge Learningcited by 11
  27. 2022Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graphcited by 11
  28. 2021Over-the-Air Aggregation for Federated Learning: Waveform Superposition and Prototype Validationcited by 10
  29. 2022Over-the-Air Federated Edge Learning with Hierarchical Clusteringcited by 10
  30. 2022Over-the-Air Computation Based on Balanced Number Systems for Federated Edge Learningcited by 10
  31. 2021Over-the-Air Computation with DFT-spread OFDM for Federated Edge Learningcited by 9
  32. 2022Distributed Learning over a Wireless Network with Non-coherent Majority Vote Computationcited by 9
  33. 2018Blind Over-the-Air Computation and Data Fusion via Provable Wirtinger Flowcited by 8
  34. 2020Over-the-Air Computation Systems: Optimal Design with Sum-Power Constraintcited by 8
  35. 2021Communication-Efficient Split Learning Based on Analog Communication and Over the Air Aggregationcited by 8
  36. 2021Over-the-Air Federated Multi-Task Learning Over MIMO Multiple Access Channelscited by 8
  37. 2022Over-the-Air Federated Learning with Energy Harvesting Devicescited by 8
  38. 2022Balancing Accuracy and Integrity for Reconfigurable Intelligent Surface-aided Over-the-Air Federated Learningcited by 8

50 most cited of 96 All 96 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 4; 2024: 6; 2025: 3; 2026: 7.

21 papers.

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  1. 2022Task-Oriented Over-the-Air Computation for Multi-Device Edge AIcited by 14
  2. 2023Over-the-Air Federated Learning and Optimizationcited by 10
  3. 2024Collaborative Edge AI Inference over Cloud-RANcited by 5
  4. 2024Private Collaborative Edge Inference via Over-the-Air Computationcited by 5
  5. 2024Over-the-Air Federated Learning via Weighted Aggregationcited by 5
  6. 2025Universal Approximation with XL MIMO Systems: OTA Classification via Trainable Analog Combiningcited by 5
  7. 2024Adaptive Federated Learning Over the Aircited by 4
  8. 2024Robust Federated Learning Over the Air: Combating Heavy-Tailed Noise with Median Anchored Clippingcited by 3
  9. 2025Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processingcited by 3
  10. 2023Graph Neural Networks over the Air for Decentralized Tasks in Wireless Networkscited by 2
  11. 2026Over-The-Air Extreme Learning Machines with XL Reception via Nonlinear Cascaded Metasurfacescited by 2
  12. 2026Compression Tells Intelligence: Visual Coding, Visual Token Technology, and the Unificationcited by 2
9 more
  1. 2023Over-the-Air Federated Learning with Compressed Sensing: Is Sparsification Necessary?cited by 1
  2. 2024Collaborative Inference over Wireless Channels with Feature Differential Privacycited by 1
  3. 2023Wireless Federated k-Means Clustering with Non-coherent Over-the-Air Computationcited by 0
  4. 2025Machine Intelligence on Wireless Edge Networkscited by 0
  5. 2026Hybrid Channel Estimation with Quantized Phase Feedback for Over-the-Air Computationcited by 0
  6. 2026MD-AirComp+: Adaptive Quantization for Blind Massive Digital Over-the-Air Computationcited by 0
  7. 2026Federated Multi Agent Deep Learning and Neural Networks for Advanced Distributed Sensing in Wireless Networkscited by 0
  8. 2026Out-of-Air Computation: Enabling Structured Function Extraction from Wireless Superpositioncited by 0
  9. 2026Over-The-Air Extreme Learning Machines with Nonlinear Stacked Intelligent Metasurfacescited by 0