Sub-Nyquist cooperative wideband spectrum sensing based on multicoset sampling for TV white spaces

摘要

Cognitive access to TV white space (TVWS) calls for reliable and fast spectrum sensing over a wide bandwidth, which challenges traditional spectrum sensing schemes operating at or above Nyquist rate. Sub-Nyquist sampling has attracted significant interests for wideband spectrum sensing. In this paper, we propose a sub-Nyquist wideband spectrum sensing algorithm that can estimate the spectrum of a multiband signal without sampling at full bandwidth through the use of multiple low-speed analog-to-digital converters based on multicoset sampling. To improve the detection performance under compressed measurements, cooperative spectrum sensing is adopted by fusing the sensing decisions of multiple secondary users (SUs). For energy conservation, we select the minimum number of participating SUs based on their channel conditions to achieve the desired high global detection probability. The mathematical model of the proposed sub-Nyquist wideband sensing algorithm is derived and verified by numerical analysis and tested on real-time TVWS signals.