Papers use wireless device-dependent radio-metrics as fingerprints. A radio-metric is a component of radio signal, amplitude, frequency and bandwidth. Each device creates a unique set of radio-metrics in its emitted signal due to hardware variability during the production of the antennas, power amplifiers, ADC and DAC circuits.As a result, radio-metrics cannot be altered post-production, and thus provide a reliable means for distinguishing wireless devices.
In fact, the transmitted RF signal from a wireless device experiences hardware impairments, channel characteristics, and noise at the receiver. Distortions caused by channel-specific and noise-related effects are likely to have a more random structure. Distortions in a feature that are caused by transmitter hardware impairments should manifest themselves consistently across multiple frames from the same transmitter.
device-dependent fingerprints are Modulation based features like carrier Frequency offset, phase shift offset, I/Q origin offset in the constellation plane.
How can I simulate carrier frequency offset in MATLAB?
In the following reference 1, the carrier frequency difference (CFD) is used as a feature for distinguishing wireless devices and it is assumed as Gaussian distribution. Why can we assume that this feature is Gaussian distributed?
Why do noise and the channel not affect this feature?
CFO of different devices in the feature space