mlsanityData to 7 Oct 2026

Over the Air Deep Learning Based Radio Signal Classification

arXiv 1712.04578 ↗First posted 13 Dec 2017cs.LG eess.SPcited by 121

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Abstract (arXiv)

We conduct an in depth study on the performance of deep learning based radio signal classification for radio communications signals. We consider a rigorous baseline method using higher order moments and strong boosted gradient tree classification and compare performance between the two approaches across a range of configurations and channel impairments. We consider the effects of carrier frequency offset, symbol rate, and multi-path fading in simulation and conduct over-the-air measurement of radio classification performance in the lab using software radios and compare performance and training strategies for both. Finally we conclude with a discussion of remaining problems, and design considerations for using such techniques.

Key facts. Cited by 121 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Dec 2017.

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Citing papers per year: 2021: 21; 2022: 26; 2023: 9; 2024: 22; 2025: 24; 2026: 19.

121 papers.

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  1. 2024SGLP: A Similarity Guided Fast Layer Partition Pruning for Compressing Large Deep Modelscited by 24
  2. 2021Transfer Learning for Future Wireless Networks: A Comprehensive Surveycited by 18
  3. 2024A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Modelscited by 18
  4. 2021Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classificationcited by 17
  5. 2022Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Predictioncited by 17
  6. 2021An Efficient Deep Learning Model for Automatic Modulation Recognition Based on Parameter Estimation and Transformationcited by 15
  7. 2022A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challengescited by 15
  8. 2022Self-Contrastive Learning based Semi-Supervised Radio Modulation Classificationcited by 15
  9. 2021Interference Suppression Using Deep Learning: Current Approaches and Open Challengescited by 10
  10. 2021Adaptive Visibility Graph Neural Network and its Application in Modulation Classificationcited by 9
  11. 2022Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compressioncited by 9
  12. 2022Robust Bayesian Learning for Reliable Wireless AI: Framework and Applicationscited by 9
38 more
  1. 2023Multi-task Learning for Radar Signal Characterisationcited by 9
  2. 2022Large Scale Radio Frequency Signal Classificationcited by 8
  3. 2021A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networkscited by 7
  4. 2022WAIR-D: Wireless AI Research Datasetcited by 7
  5. 2024Enhancing Automatic Modulation Recognition through Robust Global Feature Extractioncited by 7
  6. 2025SpectrumFM: A Foundation Model for Intelligent Spectrum Managementcited by 6
  7. 2024Countermeasures Against Adversarial Examples in Radio Signal Classificationcited by 5
  8. 2025RadioLLM: Introducing Large Language Model into Cognitive Radio via Hybrid Prompt and Token Reprogrammingscited by 5
  9. 2021Deep Learning Radio Frequency Signal Classification with Hybrid Imagescited by 4
  10. 2023Multi-stage Learning for Radar Pulse Activity Segmentationcited by 4
  11. 2024Enhancing Automatic Modulation Recognition for IoT Applications Using Transformerscited by 4
  12. 2024Survey of Graph Neural Network for Internet of Things and NextG Networkscited by 4
  13. 2024Meta-Learning Guided Label Noise Distillation for Robust Signal Modulation Classificationcited by 4
  14. 2024Modulation and Coding for NOMA and RSMAcited by 4
  15. 2025FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognitioncited by 4
  16. 2021Can You Fix My Neural Network? Real-Time Adaptive Waveform Synthesis for Resilient Wireless Signal Classificationcited by 3
  17. 2021Gradient-based Adversarial Deep Modulation Classification with Data-driven Subsamplingcited by 3
  18. 2021ChaRRNets: Channel Robust Representation Networks for RF Fingerprintingcited by 3
  19. 2021The Tags Are Alright: Robust Large-Scale RFID Clone Detection Through Federated Data-Augmented Radio Fingerprintingcited by 3
  20. 2021Binarized ResNet: Enabling Robust Automatic Modulation Classification at the resource-constrained Edgecited by 3
  21. 2022Continuously Generalized Ordinal Regression for Linear and Deep Modelscited by 3
  22. 2022Mixture GAN For Modulation Classification Resiliency Against Adversarial Attackscited by 3
  23. 2023MoE-AMC: Enhancing Automatic Modulation Classification Performance Using Mixture-of-Expertscited by 3
  24. 2024Joint Signal Detection and Automatic Modulation Classification via Deep Learningcited by 3
  25. 2024A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classificationcited by 3
  26. 2024Filtered Randomized Smoothing: A New Defense for Robust Modulation Classificationcited by 3
  27. 2025DenoMAE2.0: Improving Denoising Masked Autoencoders by Classifying Local Patchescited by 3
  28. 2025EMind: A Foundation Model for Multi-task Electromagnetic Signals Understandingcited by 3
  29. 2026Multi-Modal Data-Enhanced Foundation Models for Prediction and Control in Wireless Networks: A Surveycited by 3
  30. 2021On the benefits of robust models in modulation recognitioncited by 2
  31. 2021BCNN: Binary Complex Neural Networkcited by 2
  32. 2021SafeAMC: Adversarial training for robust modulation recognition modelscited by 2
  33. 2022RF Signal Classification with Synthetic Training Data and its Real-World Performancecited by 2
  34. 2022Large Scale Radio Frequency Wideband Signal Detection & Recognitioncited by 2
  35. 2023Automatic Modulation Classification with Deep Neural Networkscited by 2
  36. 2025Few-Shot Radar Signal Recognition through Self-Supervised Learning and Radio Frequency Domain Adaptationcited by 2
  37. 2025AI/ML-Based Automatic Modulation Recognition: Recent Trends and Future Possibilitiescited by 2
  38. 2025Revolution of Wireless Signal Recognition for 6G: Recent Advances, Challenges and Future Directionscited by 2

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