We are pleased to announce that DeepSig has been awarded a contract to apply our machine learning-based radio technology to NASA's space-to-space and space-to-ground communications links.
Working with the NASA Glenn Research Center, DeepSig's communications technology will be applied to NASA's Tracking and Data Relay Satellites (TDRS) System and tested on NASA's Space Communications and Navigation (SCaN) Testbed to evaluate the performance gains that can be realized with Artificial Intelligence in space communications systems.
DeepSig's program with NASA is called the "Cognitive Communications Autoencoder" (80GRC017C0048), referring to the "channel autoencoder" that was first developed by DeepSig principals. A "channel autoencoder" is a machine learning-based system that has learned to communicate using measurements from the wireless channel. This approach to communications design allows for substantial performance gains relative to traditional approaches, and is covered in more detail in our scientific publications (available here).
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