Low Power Spectrum Sensing for Cognitive Radios

Project Member: Sharon Xiao

As wireless usage grows exponentially in the coming decades, cognitive radios have been proposed as a promising solution to the problem of spectrum scarcity. The proposal allows for spectrum re-use, letting unlicensed users operate on licensed bands when their primary users are absent. In such a system, spectrum sensing is necessary to identify idle bands as well as to rapidly detect the return of a primary user. In order to assure non-interference with primary user activities, a cognitive radio system must be able to reliably detect extremely weak signals down to the low and negative SNR regimes. Furthermore, spectrum sensing must be implemented with minimal power and complexity overhead to be realizable in mobile applications.

This research explores techniques for robust and low power spectrum sensing, initially focusing on the UHF DTV bands which have been approved for cognitive radio operations by the FCC. For minimum power, we propose an analog system using sub-Nyquist equivalent-time sampling and simple energy detection. To meet sensitivity requirements for weak signals, we seek out the DTV pilot tone, a narrowband feature with an SNR improvement over overall channel SNR. We can further more robustly extract the pilot from noise by adding a second, time-delayed receive path and autocorrelating the pilot.