A Robust Simultaneous Likelihood Ratio Test Detector for Wideband Spectrum Sensing under Non-Gaussian Noise

In cognitive radio, wideband spectrum sensing is challenging in detecting low signal-to-noise ratio signals dominated by non-Gaussian noises. Traditional methods outlined in current literature often fail to provide satisfactory detection performance in the aforesaid scenario. To address this issue, we propose the use of a simultaneous likelihood ratio test (SLRT) as a statistical method to detect the primary signal in a non-Gaussian noise environment. The SLRT-based detector (SLRTD) detects the changes in the received signal statistics with respect to the additive noise. In the SLRT detector, the test statistics of the received signal are estimated using the robust standard deviation to counteract the impact of non-Gaussian noise. Furthermore, detection performance is enhanced through cooperative sensing in a multi-node environment. Our simulations, conducted in both Gaussian and non-Gaussian noise environments using a Universal-Filtered Multi-Carrier (UFMC) signal, demonstrate the superior accuracy of our robust detectors in the presence of non-Gaussian such as Bernoulli, Laplacian, symmetric α-stable distributions noise. This improved accuracy provides reassurance of the effectiveness of our proposed method.