Identifying transponder hardware or waveform in wireless network via machine learning module

Abstract

The disclosure provides processes to generate an identification tag for a transponder in a wireless network via a machine learning module. Methods of the disclosure include capturing, via a wireless receiver within a wireless network, a plurality of time-domain communication samples of a transponder operating within the wireless network. A multi-dimensional tensor is generated, indicating a plurality of features of the time-domain communication samples of the transponder. A machine learning module converts the multi-dimensional tensor into a one-dimensional feature vector indicating the plurality of features of the time-domain communication samples. The machine learning module extracts a hardware identification feature for the transponder from the one-dimensional feature vector. The machine learning module includes: an embedding component for extracting the one-dimensional feature vector from a multi-dimensional tensor indicating a set of hardware intrinsic features; or an attentional component for deducing a hardware signature from the one-dimensional feature vector.