Inherent PA Non-Linearity, I/Q Imbalance Extraction & Zero-Trust Device Identification

Authenticating wireless transceivers by characterizing microscopic silicon manufacturing imperfections in power amplifiers and local oscillators.

Silicon Hardware Intrinsic Imperfections

Every RF transmitter possesses unique microscopic imperfections: mixer I/Q phase imbalances, non-linear power amplifier AM/AM curves, and phase noise phase drifts that cannot be cloned by software-defined radios.

Deep Feature Extraction and Authentication

ISACSecurity analyzes incoming preamble waveforms using convolutional neural networks and matched Hilbert transforms, verifying device identity in under 50 microseconds with a 99.9999% authentication accuracy.

Extraction of physical hardware impairments: I/Q imbalance, phase drift, and PA non-linearity
Zero-trust physical layer authentication in <50 µs prior to upper-layer handshakes
Resistant to cryptographic key theft, software cloning, and replay attacks
Device classification accuracy of 99.9999% across a fleet of 50,000 wireless nodes

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