mlsanityData to 14 Oct 2026

Interpretable Feature Learning for RF Fingerprinting via Polar MKANs

arXiv 2608.19881 ↗First posted 20 Aug 2026eess.SP cs.LGcited by 0

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Abstract (arXiv)

Radio frequency (RF) fingerprinting authenticates wireless devices from hardware-induced I/Q impairments, typically with deep learning feature extractors that are accurate but opaque, limiting their use in security critical settings. We propose Polar Monotonic Kolmogorov-Arnold Networks (Polar MKAN), a block partitioned monotonic encoder on polar inputs in which each latent dimension depends exclusively on magnitude or phase, yielding channel separation and monotone responses by construction. On a synthetic gain and carrier frequency offset (CFO) benchmark, Polar MKAN reaches 57.2 percent DCI Disentanglement versus at most 12.9 percent for unpartitioned baselines. We further evaluate the detection accuracy trade off on real data and the sensitivity to blind CFO compensation.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 24 references that are in the map. First posted on arXiv 20 Aug 2026.

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References · 15

  1. 2017A Unified Approach to Interpreting Model Predictionscited by 6,555
  2. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,070
  3. 2013Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Mapscited by 2,371
  4. 2018Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representationscited by 941
  5. 2024KAN: Kolmogorov-Arnold Networkscited by 649
  6. 2021Interpretable Machine Learning: Fundamental Principles and 10 Grand Challengescited by 367
  7. 2020Measuring Disentanglement: A Review of Metricscited by 70
  8. 2024A Survey on Kolmogorov-Arnold Networkcited by 68
  9. 2021WiSig: A Large-Scale WiFi Signal Dataset for Receiver and Channel Agnostic RF Fingerprintingcited by 21
  10. 2022Disentangled Representation Learning for RF Fingerprint Extraction under Unknown Channel Statisticscited by 5
  11. 2024Towards Robust RF Fingerprint Identification Using Spectral Regrowth and Carrier Frequency Offsetcited by 2
  12. 2025Factorized Disentangled Representation Learning for Interpretable Radio Frequency Fingerprintcited by 1
3 more
  1. 2025Cross-Receiver Generalization for RF Fingerprint Identification via Feature Disentanglement and Adversarial Trainingcited by 1
  2. 2025Design Principles of Zero-Shot Self-Supervised Unknown Emitter Detectorscited by 1
  3. 2026Monotonic Kolmogorov-Arnold Networks: A Theoretical and Empirical Study of Monotonicity as an Inductive Biascited by 1

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