Abstract: A computer-implemented method comprising: receiving, by a first radio frequency (RF) receiving device, an RF data transmission from an RF transmitter; analyzing the received RF data transmission to estimate at least one RF feature; constructing, based on the at least one RF feature, an RF fingerprint of the RF transmitter which is specific to the first RF receiving device; and modifying the RF fingerprint to generate a modified RF fingerprint for use by a second RF receiving device, by applying, to the RF fingerprint, a conversion function reflecting a differential between respective contribution values associated with each of the first and second receiving devices.

Abstract: A computer-implemented method comprising: monitoring transmissions representing estimation of a wireless channel, between at least one wireless access point (AP) and a plurality of wireless stations (STAs); at a training stage, training a machine learning model on a training dataset comprising: (i) a plurality dataframes of a standard beamforming protocol associated with at least some of the monitored transmissions, and (ii) labels indicating an association between the dataframes and the STAs; and at an inference stage, applying the trained machine learning model to a target transmission representing estimation of a wireless channel, to predict whether the target transmission was transmitted from one of the STAs.