Identification of RF Devices Through Constellation Patterns Using Complex-Valued Neural Networks

Complex-valued neural network (CvNN)-based device identification is proposed to enhance the security of communications. Devices have in-phase/quadrature (I/Q) impairments that arise from variations in the manufacturing process. An access point (AP) receives I/Q symbols from a device and forms a constellation pattern, which has a unique feature of the device’s inherent I/Q impairments. The CvNN is able to recognize the device by categorizing the pattern. Simulations demonstrate that the CvNN has a lower error rate in identification than a realvalued neural network. This is because the CvNN captures the inherent correlation in complex-valued I/Q symbols caused by I/Q imbalances.