CRODA-ST: Single-Target Cross-Receiver Open-Set Radio Fingerprint Recognition
For IoT device authentication, it solves the problem of unreliable open-set decisions when transferring a threshold from source to target receiver.
CRODA-ST addresses open-set radio fingerprint recognition under receiver shift, achieving 0.9092 known-class accuracy, 0.9692 AUROC, and 0.9580 OSCR on the WiSig ManyTx dataset.
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.