Optical transceiver tuning using machine learning

Abstract

A test and measurement device has a connection to allow the test and measurement device to connect to an optical transceiver, one or more processors, configured to execute code that causes the one or more processors to: initially set operating parameters for the optical transceiver to average parameters, acquire a waveform from the optical transceiver, measure the acquired waveform and determine if operation of the transceiver passes or fails, send the waveform and the operating parameters to a machine learning system to obtain estimated parameters if the transceiver fails, adjust the operating parameters based upon the estimated parameters, and repeat the acquiring, measuring, sending, and adjusting as needed until the transceiver passes. A method to tune optical transceivers includes connecting a transceiver to a test and measurement device, setting operating parameters for the transceiver to an average set of parameters, acquiring a waveform from the transceiver, measuring the waveform to determine if the transceiver passes or fails, sending the waveform and operating parameters to a machine learning system when the transceiver fails, using the machine learning system to provide adjusted operating parameters, setting the operating parameters to the adjusted parameters, and repeating the acquiring, measuring, sending, using, and setting until the transceiver passes.