Abstract
ABSTRACT This paper proposes hybrid binary logical regression with a gradient decent optimisation (GDO) algorithm for spectrum sensing. From multiple secondary users (SU) systems, all signal vectors are collected with cognitive radios (CRs), and the features associated with the signal vector are considered for decision statistics. The decision statistics are modelled with a hybrid binary logical regression with gradient decent (BLR-GD) algorithm, which improves efficiency. The gradient decent (GD) is accomplished with binary logical regression (BLD), in which the regression coefficients are calculated efficiently. For evaluating the performance of the proposed algorithm, the spectrum sensing is evaluated in low signal-to-noise ratio (SNR) and high SNR scenarios. The detection probability, accuracy, F-measure and ROC curve performance of the proposed approach will outperform other existing approaches. The latency value of the proposed approach has reached 0.009 ms, which shows the efficiency of the proposed approach with 5 G communication features.
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