Towards Wireless Environment Cognizance Through Incremental Learning
Aniqua Baset, Christopher Becker, Kurt Derr, Samuel Ramirez, Sneha Kumar Kasera, Aditya Bhaskara · 2019
With the tremendous increase in the use of wireless devices, understanding the surrounding wireless/RF environment is becoming essential for many application areas. In this work, we develop the technical building blocks needed for a spectrum monitoring system that can incrementally learn about the signals present in a deployed environment. We achieve incremental learning (IL) by identifying and grouping the new/unknown signals and, automatically building new machine learning (ML) models for detecting them. A thorough evaluation of our approach demonstrates its adaptability and high accuracy with signal data from several over-the-air scenarios.