Improving Wireless IoT Signals Across Communication Channels

ECE Research Assistant Professor Salvatore D’Oro, William Lincoln Smith Professor Tommaso Melodia, and Assistant Professor Francesco Restuccia were awarded a patent for “Device and method for reliable classification of wireless signals.”

Abstract Source: USPTO

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.

Related Faculty: Salvatore D'Oro, Tommaso Melodia, Francesco Restuccia

Related Departments:Electrical & Computer Engineering