Approaching Domain Generalization with Embeddings for Robust Discrimination and Recognition of RF Communication Signals
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915579917500416 |
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| author | Henneke, Lukas Kurth, Frank |
| author_facet | Henneke, Lukas Kurth, Frank |
| contents | Radio frequency (RF) signal recognition plays a critical role in modern wireless communication and security applications. Deep learning-based approaches have achieved strong performance but typically rely heavily on extensive training data and often fail to generalize to unseen signals. In this paper, we propose a method to learn discriminative embeddings without relying on real-world RF signal recordings by training on signals of synthetic wireless protocols. We validate the approach on a dataset of real RF signals and show that the learned embeddings capture features enabling accurate discrimination of previously unseen real-world signals, highlighting its potential for robust RF signal classification and anomaly detection. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_23186 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Approaching Domain Generalization with Embeddings for Robust Discrimination and Recognition of RF Communication Signals Henneke, Lukas Kurth, Frank Signal Processing Radio frequency (RF) signal recognition plays a critical role in modern wireless communication and security applications. Deep learning-based approaches have achieved strong performance but typically rely heavily on extensive training data and often fail to generalize to unseen signals. In this paper, we propose a method to learn discriminative embeddings without relying on real-world RF signal recordings by training on signals of synthetic wireless protocols. We validate the approach on a dataset of real RF signals and show that the learned embeddings capture features enabling accurate discrimination of previously unseen real-world signals, highlighting its potential for robust RF signal classification and anomaly detection. |
| title | Approaching Domain Generalization with Embeddings for Robust Discrimination and Recognition of RF Communication Signals |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2510.23186 |