Enhanced Spectrum Sensing With Dual Threshold and Opinion Fusion in Cognitive Radio Networks

Abstract

Cognitive radio technology has emerged to address spectrum underutilization, enabling secondary users to access unused spectrum by accurately detecting the presence or absence of primary users. Traditional spectrum sensing methods rely on energy-based detection using a single threshold, but often yield ambiguous results, especially in noisy environments or with low signal-to-noise ratios. To overcome this, the paper proposes a novel energy-based spectrum sensing mechanism using generalized energy detection (GED), dual thresholding, and fused decisions. GED enhances the distinction between noise and signal, while dual thresholding more effectively determines primary user presence. The fused decision process reduces uncertainty in borderline cases by considering inputs from other secondary users, ensuring a more accurate final decision. Experimental results demonstrate the superiority of this approach in terms of detection accuracy, reduced false alarms, and lower bit error rates compared to state-of-the-art methods.