Spectrum Sensing Algorithm Based on Double Threshold and Two-Stage Detection Under a Low SNR

In cognitive radio networks, spectrum sensing algorithms almost perform poor in low signal-to-noise ratio (SNR) sensing environment, it does need to improve detection probability by increasing the detection time. In order to solve the mentioned problems, a new spectrum sensing algorithm based on the double threshold and two-stage detection strategy under the condition of low SNR is put forward in this paper. First of all, when a false-alarm probability is given, the sampling length is found out under the different SNR level. Then the first stage detection is carried out by designing the two detection threshold. Finally the second stage detection is implemented for the center portion of the double threshold and the final detection result is gotten. Simulations and analysis show that, when the SNR is low, the proposed algorithm not only has a short average sensing time but also has a good performance in a small false-alarm probability constraint condition and low algorithm complexity.