An Adaptive Spectrum Sensing Algorithm under Noise Uncertainty
Shibing Zhang, Zhihua Bao · 2011
Spectrum sensing is an essential technique for cognitive radios. This paper addresses the spectrum sensing under uncertain noise power and proposes an adaptive spectrum sensing algorithm. The adaptive decision threshold of energy detection is derived, which is based on the weighted probability of detection and probability of false alarm. By means of estimating noise power and signal power, the decision threshold is able to adapt to the noise fluctuation. Simulation results show that the proposed algorithm has robustness to the noise uncertainty. It can be used for detecting various kinds of signal without any knowledge of noise power or signal power.