Hamiltonian Transformer with norm-preserving attention and phase embeddings outperforms baselines in RF fingerprinting on WiSig dataset, reaching 99.12% same-day accuracy and 61.64% at 150 transmitters.
WiSig: A large-scale WiFi signal dataset for receiver and channel agnostic RF fingerprinting.IEEE Access, 10:22808–22818, 2022
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Hamiltonian-Inspired Attention Mechanism for Scalable RF Transmitter Fingerprinting
Hamiltonian Transformer with norm-preserving attention and phase embeddings outperforms baselines in RF fingerprinting on WiSig dataset, reaching 99.12% same-day accuracy and 61.64% at 150 transmitters.