mlsanityData to 14 Oct 2026

Analog-digital Scheduling for Federated Learning: A Communication-Efficient Approach

arXiv 2402.00318 ↗First posted 1 Feb 2024cs.LG cs.IT eess.SPcited by 5

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Abstract (arXiv)

Over-the-air (OTA) computation has recently emerged as a communication-efficient Federated Learning (FL) paradigm to train machine learning models over wireless networks. However, its performance is limited by the device with the worst SNR, resulting in fast yet noisy updates. On the other hand, allocating orthogonal resource blocks (RB) to individual devices via digital channels mitigates the noise problem, at the cost of increased communication latency. In this paper, we address this discrepancy and present ADFL, a novel Analog-Digital FL scheme: in each round, the parameter server (PS) schedules each device to either upload its gradient via the analog OTA scheme or transmit its quantized gradient over an orthogonal RB using the ``digital" scheme. Focusing on a single FL round, we cast the optimal scheduling problem as the minimization of the mean squared error (MSE) on the estimated global gradient at the PS, subject to a delay constraint, yielding the optimal device scheduling configuration and quantization bits for the digital devices. Our simulation results show that ADFL, by scheduling most of the devices in the OTA scheme while also occasionally employing the digital scheme for a few devices, consistently outperforms OTA-only and digital-only schemes, in both i.i.d. and non-i.i.d. settings.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 15 of its 21 references that are in the map. First posted on arXiv 1 Feb 2024.

Builds on

15 of 21 references.

References · 15

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
  2. 2016Federated Learning: Strategies for Improving Communication Efficiencycited by 1,475
  3. 2019Towards Federated Learning at Scale: System Designcited by 832
  4. 2019Federated Learning in Mobile Edge Networks: A Comprehensive Surveycited by 408
  5. 2019A Joint Learning and Communications Framework for Federated Learning over Wireless Networkscited by 263
  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. 2019Scheduling Policies for Federated Learning in Wireless Networkscited by 131
  10. 2020Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learningcited by 90
  11. 2020Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edgecited by 71
  12. 2020Blind Federated Edge Learningcited by 43
3 more
  1. 2020Multi-Stage Hybrid Federated Learning over Large-Scale D2D-Enabled Fog Networkscited by 42
  2. 2020Distributed Machine Learning for Wireless Communication Networks: Techniques, Architectures, and Applicationscited by 21
  3. 2023Delay-Aware Hierarchical Federated Learningcited by 9

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 1.

5 papers.

  1. 2025Biased Federated Learning under Wireless Heterogeneitycited by 4
  2. 2025Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processingcited by 3
  3. 2024Biased Over-the-Air Federated Learning under Wireless Heterogeneitycited by 2
  4. 2025Non-Convex Over-the-Air Heterogeneous Federated Learning: A Bias-Variance Trade-offcited by 1
  5. 2026Age-Aware Edge-Blind Federated Learning via Over-the-Air Aggregationcited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2023Channel and Gradient-Importance Aware Device Scheduling for Over-the-Air Federated Learning
  2. 2022Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control
  3. 2022Performance Optimization for Variable Bitwidth Federated Learning in Wireless Networks
  4. 2024Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
  5. 2022Over-the-Air Federated Learning via Second-Order Optimization
  6. 2024Adaptive Quantization Resolution and Power Control for Federated Learning over Cell-free Networks
  7. 2022Wireless Quantized Federated Learning: A Joint Computation and Communication Design
  8. 2025Quantized Analog Beamforming Enabled Multi-task Federated Learning Over-the-air