  Spectrum sensing enables cognitive radio systems to detect unused portions of
the radio spectrum and then use them while avoiding interferences to the
primary users. Energy detection is one of the most used techniques for spectrum
sensing because it does not require any prior information about the
characteristics of the primary user signal. However, this technique does not
distinguish between the signal and the noise. It has a low performance at low
SNR, and the selection of the threshold becomes an issue because the noise is
uncertain. The detection performance of this technique can be further improved
using a dynamic selection of the sensing threshold. In this work, we
investigate a dynamic selection of this threshold by measuring the power of
noise present in the received signal using a blind technique. The proposed
model was implemented and tested using GNU Radio software and USRP units. Our
results show that the dynamic selection of the threshold based on measuring the
noise level present in the received signal during the detection process
increases the probability of detection and decreases the probability of false
alarm compared to the ones of energy detection with a static threshold.
