mlsanityData to 7 Oct 2026

Towards an Intelligent Edge: Wireless Communication Meets Machine Learning

arXiv 1809.00343 ↗First posted 2 Sep 2018cs.IT cs.LG cs.NIcited by 94

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Abstract (arXiv)

The recent revival of artificial intelligence (AI) is revolutionizing almost every branch of science and technology. Given the ubiquitous smart mobile gadgets and Internet of Things (IoT) devices, it is expected that a majority of intelligent applications will be deployed at the edge of wireless networks. This trend has generated strong interests in realizing an "intelligent edge" to support AI-enabled applications at various edge devices. Accordingly, a new research area, called edge learning, emerges, which crosses and revolutionizes two disciplines: wireless communication and machine learning. A major theme in edge learning is to overcome the limited computing power, as well as limited data, at each edge device. This is accomplished by leveraging the mobile edge computing (MEC) platform and exploiting the massive data distributed over a large number of edge devices. In such systems, learning from distributed data and communicating between the edge server and devices are two critical and coupled aspects, and their fusion poses many new research challenges. This article advocates a new set of design principles for wireless communication in edge learning, collectively called learning-driven communication. Illustrative examples are provided to demonstrate the effectiveness of these design principles, and unique research opportunities are identified.

Key facts. Cited by 94 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Sep 2018.

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Citing papers per year: 2021: 31; 2022: 15; 2023: 15; 2024: 14; 2025: 8; 2026: 11.

94 papers.

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  1. 2021Distributed Learning in Wireless Networks: Recent Progress and Future Challengescited by 125
  2. 2021Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Approachcited by 105
  3. 2023Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networkscited by 95
  4. 2024AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networkscited by 64
  5. 2021Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edgecited by 56
  6. 2021Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysiscited by 51
  7. 2021Hierarchical Federated Learning with Quantization: Convergence Analysis and System Designcited by 47
  8. 2021Task-Oriented Communication for Multi-Device Cooperative Edge Inferencecited by 47
  9. 2024WirelessLLM: Empowering Large Language Models Towards Wireless Intelligencecited by 43
  10. 2021Quantized Federated Learning under Transmission Delay and Outage Constraintscited by 37
  11. 2021Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraintscited by 34
  12. 2021Applications and Techniques for Fast Machine Learning in Sciencecited by 32
38 more
  1. 2022Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AIcited by 31
  2. 2021Federated Edge Learning with Misaligned Over-The-Air Computationcited by 28
  3. 2023Green Edge AI: A Contemporary Surveycited by 24
  4. 2021UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approachcited by 20
  5. 2022Parallel Successive Learning for Dynamic Distributed Model Training over Heterogeneous Wireless Networkscited by 18
  6. 2022Scalable and Low-Latency Federated Learning with Cooperative Mobile Edge Networkingcited by 18
  7. 2023Communication-Efficient Split Learning via Adaptive Feature-Wise Compressioncited by 18
  8. 2021Communication-Efficient Federated Learning via Quantized Compressed Sensingcited by 17
  9. 2021Joint Optimization of Communications and Federated Learning Over the Aircited by 13
  10. 2021Faithful Edge Federated Learning: Scalability and Privacycited by 13
  11. 2021Federated Learning over Wireless IoT Networks with Optimized Communication and Resourcescited by 13
  12. 2022Task-Oriented Communication for Edge Video Analyticscited by 13
  13. 2022Federated Learning and Meta Learning: Approaches, Applications, and Directionscited by 12
  14. 2022Task-Oriented Over-the-Air Computation for Multi-Device Edge AIcited by 12
  15. 2024A Survey on Integrated Sensing, Communication, and Computationcited by 12
  16. 2021Federated Learning over Wireless Networks: A Band-limited Coordinated Descent Approachcited by 11
  17. 2022Vertical Federated Edge Learning with Distributed Integrated Sensing and Communicationcited by 11
  18. 2022Predictive GAN-powered Multi-Objective Optimization for Hybrid Federated Split Learningcited by 11
  19. 2021Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networkscited by 10
  20. 2021Wirelessly Powered Federated Edge Learning: Optimal Tradeoffs Between Convergence and Power Transfercited by 10
  21. 2021Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learningcited by 10
  22. 2023MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central Updatescited by 10
  23. 2023Spectrum Breathing: Protecting Over-the-Air Federated Learning Against Interferencecited by 9
  24. 2021Federated Learning over Noisy Channels: Convergence Analysis and Design Examplescited by 8
  25. 2023Optimization of Image Transmission in a Cooperative Semantic Communication Networkscited by 8
  26. 2021Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learningcited by 7
  27. 2024Tackling Distribution Shifts in Task-Oriented Communication with Information Bottleneckcited by 7
  28. 2021BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackerscited by 6
  29. 2022Energy-Aware Edge Association for Cluster-based Personalized Federated Learningcited by 6
  30. 2024Attention-aware Semantic Communications for Collaborative Inferencecited by 6
  31. 2021Accelerating Edge Intelligence via Integrated Sensing and Communicationcited by 5
  32. 2022Over-the-Air Federated Learning with Privacy Protection via Correlated Additive Perturbationscited by 5
  33. 2024Collaborative Edge AI Inference over Cloud-RANcited by 5
  34. 2025Revisiting Outage for Edge Inference Systemscited by 5
  35. 2021Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challengescited by 4
  36. 2021Multiplierless MP-Kernel Machine For Energy-efficient Edge Devicescited by 4
  37. 2022On Federated Learning with Energy Harvesting Clientscited by 4
  38. 2023Asynchronous Wireless Federated Learning with Probabilistic Client Selectioncited by 4

50 most cited of 94 All 94 (JSON)