SpecSense: Learning-Based Wideband Spectrum Sensing
Blind detection and tracking of low-probability-of-intercept signals, developed during a research internship. A statistical approach to wideband spectrum sensing learns each signal’s arrival process from heavily undersampled observations.
With only 1–5% real-time coverage, the resulting model directs a small number of radios. An optimal cooperative scheduling algorithm extends the approach to multiple receivers, improving prediction over the state of the art.