Abstract
Cognitive radio is a technology developed for the effective use of radio spectrum sources. The spectrum sensing function plays a key role in the performance of cognitive radio networks. In this study, we propose an online learning algorithm for the energy detection scheme, which aims to maximizing spectrum detection performance. Optimal threshold value, which is critical for the determination of the absence or the presence of a licensed user, was mathematically expressed in accordance with the balance between probability of detection and probability of false alarm. Performance of the proposed algorithm was tested on non-fading and different fading channels for low signal-to-noise ratio (SNR) regime with noise uncertainty. In conclusion of the simulation studies, improvement in spectrum detection performance according to optimal threshold value selection was observed.
Spectrum Sensing in Cognitive Radio Networks: Threshold Value Optimization and Analysis