CRODA-ST: Single-Target Cross-Receiver Open-Set Radio Fingerprint Recognition

Fengchong Yao; Jianbing Li; Qing Liu; Kefeng Song; Haitao Li; Song Wang; Feixiang Wang

CRODA-ST: Single-Target Cross-Receiver Open-Set Radio Fingerprint Recognition

Signal Processing 2026-06-30 v1 Artificial Intelligence

Authors: Fengchong Yao , Jianbing Li , Qing Liu , Kefeng Song , Haitao Li , Song Wang , Feixiang Wang

Abstract

Radio frequency fingerprint identification (RFFI) provides a physical-layer credential for Internet of Things devices, but open-set decisions become fragile when a threshold calibrated on a source receiver is transferred to a target receiver. Receiver shift can lower the confidence of known transmitters and cause false rejection; closed-set alignment can have the opposite effect by pulling unseen target transmitters into known regions and increasing false acceptance. This letter presents CRODA-ST, a structure-first adaptation framework for singlesource single-target cross-receiver open-set RFFI. Its two components target the bottlenecks behind unreliable source-calibrated rejection: Discriminative Structure Anchoring (DSA) restores target-receiver known-class references from limited labeled target enrollment samples, and Rejection-Oriented Alignment (ROA) reduces receiver-sensitive confidence fluctuations around the anchored structure. On the WiSig ManyTx dataset, CRODA-ST reaches 0.9092 known-class accuracy, 0.9692 AUROC, and 0.9580 OSCR. Score-sweep analysis further reduces FPR90 to 0.0469.

Keywords

radio frequency fingerprint identification open-set recognition cross-receiver adaptation deep learning IoT security

Cite

@article{arxiv.2607.02567,
  title  = {CRODA-ST: Single-Target Cross-Receiver Open-Set Radio Fingerprint Recognition},
  author = {Fengchong Yao and Jianbing Li and Qing Liu and Kefeng Song and Haitao Li and Song Wang and Feixiang Wang},
  journal= {arXiv preprint arXiv:2607.02567},
  year   = {2026}
}