Cyclostationary-Based Architectures for Spectrum Sensing in IEEE 802.22 WRAN

Abstract

The well known noise rejection property of the cyclostationary spectrum makes it an ideal candidate for spectrum sensing in low SNR environments such as the IEEE 802.22 WRAN, which stipulates detection of primary signals at -20.8dB. In this paper, we propose two novel detector architectures that exploit cyclostationary properties: the Spectral Correlation Density (SCD), and the Magnitude Squared Coherence (MSC). Through extensive simulations, both on generated data and real world ATSC capture data, we show that our detector achieves an improvement of 2.5dB compared to existing proposals. Additionally, we compare our proposal against two popular choices for spectrum sensing in cognitive radio -- the matched filter detection and energy detection, and show the superiority of cyclostationary spectrum sensing in such low SNR environments.