Fuzzy Hypothesis Testing for Cooperative Sequential Spectrum Sensing Under Noise Uncertainty

Abstract

Efficient and reliable spectrum sensing is extremely significant, especially in the presence of noise uncertainty in low SNR environment below which conventional detectors fail to be robust. In this letter, by the development of a sequential probability ratio test for the fuzzy hypothesis testing (FHT), we propose a novel cooperative sequential detector to deal with the effect of noise power uncertainty. In this approach, for every measurement, FHT is computed by each cognitive radio. Subsequently, fusion center sequentially accumulates these fuzzy test statistics and decides about the sensing time. Simulation results are illustrated to show the effectiveness and robustness of the proposed sequential FHT detector. The significant reduction in sample complexity is demonstrated for our scheme in comparison with energy detector, sequential crisp hypothesis testing detector, and fixed sample size FHT detector.