WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 15, 2019
Two-stage Sequential Spectrum Sensing Detector based on Higher-Order Statistics for Cognitive Radio
Authors: ,
Abstract: In cognitive radio (CR), spectrum sensing techniques aim to allow cognitive users to effectively recycle the spectrum resources without interrupting the active primary users. Several detectors have been proposed including the energy detector, matched filters, and the cyclostationary detector but most of these are either too complex or unable to perform efficiently in low signal-to-noise ratio (SNR) environments, as blind detectors. In this paper, a partial two-stage sequential spectrum sensing algorithm based on higher-order statistics and energy detector is introduced to minimize the sensing time, and maximize the probability of detection, particularly for low SNR applications. The method first uses a filter bank to extract multiple narrow-band channels from the received wideband signal then compute the normalized power values using the energy detector in each time slot of sensing for all the sub-bands. These normalized power values are used as weights for the third-order cumulants estimated in those sub-bands. Based on these cumulants, a binary hypothesis testing problem is formulated and a low-complexity sequential probability ratio test (SPRT) is developed. At the constant false alarm rate of 0.1, computer simulation result is showing 37% of improvement in the detection probability of signals at a low SNR of -20 dB.
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Keywords: Spectrum sensing, filter banks, SPRT, energy detector, higher order statistics, cognitive radio
Pages: 9-13
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 15, 2019, Art. #2