Abstract: A signal transmitted by a trusted transmitter is sampled, and a machine-learning algorithm is trained using these samples to learn to distinguish the signal characteristics of the trusted transmitter from the signal characteristics of other transmitters. The machine-learning parameters learned to distinguish the trusted transmitter's signals can then be exported allowing other devices to authenticate signals from the trusted transmitter. Since the signal characteristics of the trusted transmitter is based on manufacturing variations, the transmitters of unauthorized users should be unable to replicate the signal characteristics of the trusted transmitter. Thus, the transmitters of unauthorized users should not be usable to spoof a device that uses the exported parameters to authenticate messages from the trusted transmitter.

Abstract: Provided herein are systems and methods for selecting a mm wave network sector for use by a vehicle operating within a network environment, the method including collecting data from a plurality of non-RF sensors on the vehicle, training, by the collected data in a deep learning inference (DL) engine, a locally trained model analyzing, using the trained model and the DL engine, the collected data to predict a sector of the mm wave network having a best alignment at a position of the vehicle; and probing the predicted sector of the mm wave network.

Abstract: Systems and methods are provided for selecting a beam direction of mm wave transmission for use by a vehicle operating within a network environment. The systems and methods include collecting data from a plurality of sensors on the vehicle to detect obstructions and other changes to an environment of the vehicle and of a base station that communicates with the vehicle. The systems and methods further include a library of digital twins, which are a virtual representation of the real-world environment, to identify beam directions of varying signal-to-noise ratios. The systems and methods further include determining from the data collected from the plurality of sensors a preferred digital twin and using the beam direction data corresponding to the digital twin to determine a beam direction for a transmitter of the vehicle to communicate with a receiver of the base station.