New Patent for “Device and method for reliable classification of wireless signals”

WIoT Institute Professors Salvatore D’Oro, Francesco Restuccia, and Tommaso Melodia were recently awarded a patent  for “Device and method for reliable classification of wireless signals.” This solution leverages AI and feedback from receivers to “adapt” transmitted waveforms so that receivers can better classify them, while maintaining waveforms decodedable.

Patent Abstract

“A machine learning (ML) agent operates at a transmitter to optimize signals transmitted across a communications channel. A physical signal modifier modifies a physical layer signal prior to transmission as a function of a set of signal modification parameters to produce a modified physical layer signal. The ML agent parses a feedback signal from a receiver across the communications channel, and determines a present tuning status as a function of the signal modification parameters and the feedback signal. The ML agent generates subsequent signal modification parameters based on the present tuning status and a set of stored tuning statuses, thereby updating the physical signal modifier to generate a subsequent modified physical layer signal to be transmitted across the communications channel.”

Source: uspto.gov

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