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http://dx.doi.org/10.3837/tiis.2019.03.005

Quickest Spectrum Sensing Approaches for Wideband Cognitive Radio Based On STFT and CS  

Zhao, Qi (School of Electronic and Information Engineering, Beihang University)
Qiu, Wei (School of Electronic and Information Engineering, Beihang University)
Zhang, Boxue (School of Electronic and Information Engineering, Beihang University)
Wang, Bingqian (AVIC Beijing Precision Engineering Institute Aircraft Industry)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.3, 2019 , pp. 1199-1212 More about this Journal
Abstract
This paper proposes two wideband spectrum sensing approaches: (i) method A, the cumulative sum (CUSUM) algorithm with short-time Fourier transform, taking advantage of the time-frequency analysis for wideband spectrum. (ii)method B, the quickest spectrum sensing with short-time Fourier transform and compressed sensing, shortening the time of perception and improving the speed of spectrum access or exit. Moreover, method B can take advantage of the sparsity of wideband signals, sampling in the sub-Nyquist rate, and it is more suitable for wideband spectrum sensing. Simulation results show that method A significantly outperforms the single serial CUSUM detection for small SNRs, while method B is substantially better than the block detection based spectrum sensing in small probability of the false alarm.
Keywords
Quickest detection; CUSUM; Spectrum sensing; STFT; Compressed sensing;
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