mlsanityData to 14 Oct 2026

Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation

arXiv 2102.02946 ↗First posted 5 Feb 2021cs.IT eess.SP math.ITcited by 29

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Abstract (arXiv)

Federated learning (FL) as a promising edge-learning framework can effectively address the latency and privacy issues by featuring distributed learning at the devices and model aggregation in the central server. In order to enable efficient wireless data aggregation, over-the-air computation (AirComp) has recently been proposed and attracted immediate attention. However, fading of wireless channels can produce aggregate distortions in an AirComp-based FL scheme. To combat this effect, the concept of dynamic learning rate (DLR) is proposed in this work. We begin our discussion by considering multiple-input-single-output (MISO) scenario, since the underlying optimization problem is convex and has closed-form solution. We then extend our studies to more general multiple-input-multiple-output (MIMO) case and an iterative method is derived. Extensive simulation results demonstrate the effectiveness of the proposed scheme in reducing the aggregate distortion and guaranteeing the testing accuracy using the MNIST and CIFAR10 datasets. In addition, we present the asymptotic analysis and give a near-optimal receive beamforming design solution in closed form, which is verified by numerical simulations.

Key facts. Cited by 29 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Feb 2021.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 10; 2023: 8; 2024: 6; 2025: 2; 2026: 1.

29 papers.

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  1. 2024ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Trainingcited by 12
  2. 2022Over-the-Air Federated Learning via Second-Order Optimizationcited by 11
  3. 2023Over-the-Air Federated Learning and Optimizationcited by 10
  4. 2022FedGiA: An Efficient Hybrid Algorithm for Federated Learningcited by 8
  5. 2022Balancing Accuracy and Integrity for Reconfigurable Intelligent Surface-aided Over-the-Air Federated Learningcited by 8
  6. 2021User Scheduling for Federated Learning Through Over-the-Air Computationcited by 7
  7. 2023Advancements in Federated Learning: Models, Methods, and Privacycited by 7
  8. 2021BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackerscited by 6
  9. 2024Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioningcited by 6
  10. 2022CFLIT: Coexisting Federated Learning and Information Transfercited by 4
  11. 2025Optimizing Communication and Device Clustering for Clustered Federated Learning with Differential Privacycited by 4
  12. 2025Age-Based Device Selection and Transmit Power Optimization in Over-the-Air Federated Learningcited by 3
17 more
  1. 2022Resource Allocation for Compression-aided Federated Learning with High Distortion Ratecited by 2
  2. 2023Keep It Simple: Fault Tolerance Evaluation of Federated Learning with Unreliable Clientscited by 2
  3. 2022Optimization-based Block Coordinate Gradient Coding for Mitigating Partial Stragglers in Distributed Learningcited by 1
  4. 2022Matching Pursuit Based Scheduling for Over-the-Air Federated Learningcited by 1
  5. 2022Communication Efficient Distributed Learning over Wireless Channelscited by 1
  6. 2023Digital Over-the-Air Federated Learning in Multi-Antenna Systemscited by 1
  7. 2023Over-the-Air Federated Edge Learning with Error-Feedback One-Bit Quantization and Power Controlcited by 1
  8. 2023Over-the-Air Federated Averaging with Limited Power and Privacy Budgetscited by 1
  9. 2024FLARE: A New Federated Learning Framework with Adjustable Learning Rates over Resource-Constrained Wireless Networkscited by 1
  10. 2022Efficient and Privacy Preserving Group Signature for Federated Learningcited by 0
  11. 2022Random Orthogonalization for Federated Learning in Massive MIMO Systemscited by 0
  12. 2023Joint Power Control and Data Size Selection for Over-the-Air Computation Aided Federated Learningcited by 0
  13. 2023Federated Linear Bandit Learning via Over-the-Air Computationcited by 0
  14. 2024Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networkscited by 0
  15. 2024Waveform Design for Over-the-Air Computingcited by 0
  16. 2024Over-the-Air Federated Learning in Cell-Free MIMO with Long-term Power Constraintcited by 0
  17. 2026Logit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networkscited by 0