Enhancing the Spectrum Sensing Technique Based on Covariance Absolute Value Using Double Adaptive Thresholds

A new wireless communication technique called cognitive radio deals with the issue of the unutilized spectrum. Cognitive users can continuously scan the permitted spectrum to look for empty areas. Spectrum sensing is an essential element of Cognitive Radio (CR) for the detection of licensed users. Due to the Signal to Noise Ratio (SNR), noise uncertainty in spectrum sensing would make the detection unreliable. In this paper, the Two Adaptive Threshold based on Covariance Absolute Values (TATCAV) is proposed to increase detection performance in the presence of noise uncertainty. According to the computer simulations using Matlab 2021b, the value of the probability of detection is Pd=92.7% as compared to the results of Two Thresholds based on Covariance Absolute Values (TTCAV) Pd = 79.9% at SNR=-18, noise uncertainty Nu =1.761dB, and using Quadrature Amplitude modulation (QAM). The misdetection probability for the proposed approach is Pm =7.2% under the same circumstances. According to the simulations, the proposed approach results are considerably better than the results of the two fixed threshold approach.