mlsanityData to 7 Oct 2026

Self-Contrastive Learning based Semi-Supervised Radio Modulation Classification

arXiv 2203.15932 ↗First posted 29 Mar 2022cs.LGcited by 15

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Abstract (arXiv)

This paper presents a semi-supervised learning framework that is new in being designed for automatic modulation classification (AMC). By carefully utilizing unlabeled signal data with a self-supervised contrastive-learning pre-training step, our framework achieves higher performance given smaller amounts of labeled data, thereby largely reducing the labeling burden of deep learning. We evaluate the performance of our semi-supervised framework on a public dataset. The evaluation results demonstrate that our semi-supervised approach significantly outperforms supervised frameworks thereby substantially enhancing our ability to train deep neural networks for automatic modulation classification in a manner that leverages unlabeled data.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 29 Mar 2022.

Builds on

6 of 20 references.

References · 6

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  3. 2017Over the Air Deep Learning Based Radio Signal Classificationcited by 121
  4. 2016Convolutional Radio Modulation Recognition Networkscited by 106
  5. 2017Distributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensorscited by 44
  6. 2019Data Augmentation for Deep Learning-based Radio Modulation Classificationcited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 3; 2024: 1; 2025: 7; 2026: 2.

15 papers.

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  1. 2022Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learningcited by 11
  2. 2025RadioLLM: Introducing Large Language Model into Cognitive Radio via Hybrid Prompt and Token Reprogrammingscited by 5
  3. 2025IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6Gcited by 5
  4. 2022CRONOS: Colorization and Contrastive Learning for Device-Free NLoS Human Presence Detection using Wi-Fi CSIcited by 3
  5. 2023Semi-Supervised RF Fingerprinting with Consistency-Based Regularizationcited by 3
  6. 2023Automatic Modulation Classification with Deep Neural Networkscited by 2
  7. 2024Multi-modal Data based Semi-Supervised Learning for Vehicle Positioningcited by 2
  8. 2023Semi-Supervised Learning via Swapped Prediction for Communication Signal Recognitioncited by 0
  9. 2025MCLRL: A Multi-Domain Contrastive Learning with Reinforcement Learning Framework for Few-Shot Modulation Recognitioncited by 0
  10. 2025ALWNN Empowered Automatic Modulation Classification: Conquering Complexity and Scarce Sample Conditionscited by 0
  11. 2025ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Modelscited by 0
  12. 2025Enhancing Automatic Modulation Recognition With a Reconstruction-Driven Vision Transformer Under Limited Labelscited by 0
3 more
  1. 2025Federated Self-Supervised Modulation Classification under Non-IID and Imbalanced Datacited by 0
  2. 2026Modulation Consistency-based Contrastive Learning for Self-Supervised Automatic Modulation Classificationcited by 0
  3. 2026Graph neural networks for sampling-invariant embeddings of organized signal setscited by 0