Wideband cognitive sensing from a few bits

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Objective: Spectrum sensing is the most important element of cognitive radio, as it forms the ba-sis for adaptive spectrum sharing. Wideband spectrum sensing without frequency sweeping orNyquist-rate sampling is a challenging problem, especially for network sensing from low-end sen-sors with limited communication capabilities. Assume that each sensor can only down-convert,filter, and send out a binary signal when it measures energy above threshold at its filter?s output.Is it possible to form a satisfactory estimate of the ambient power spectrum using just a few suchbits? This is the question at the core of this project, and exciting preliminary results suggest thatthe answer is on the affirmative. A well-rounded research program has been designed to buildupon these preliminary findings. The research will evolve along four thrusts: i) core system designand performance analysis; ii) distributed implementation; iii) relevant extensions, such as adaptivesensing; and iv) software radio experiments.Intellectual merit: Power spectrum estimation from few wideband energy detection bits has neverbeen considered - yet is a fundamental extension of spectral analysis. Exciting new applicationsof convex optimization theory and methods will be found in the area of network-based spectrumestimation.Broader impacts: Wideband spectrum sensing using cheap sensors and few bits is a transformativeidea that has the potential to permeate the benefits of cognitive radio down to commodity hardware- something currently far from reality. The topic is highly conducive for involving students andtraining the next generation of wireless engineers.