An algorithm for energy detection based on noise variance estimation under noise uncertainty
Xiaofeng Hu, Xianzhong Xie, Ting Song, Weijia Lei · 2012
Energy detection is popularly used in the detection of idle spectrum because of its simple implement and low complexity. But, the detection performance can be observably affected due to noise uncertainty. Papers have proposed some solutions to resist the effects of noise uncertainty. However, most of these papers are assumed that the noise uncertainty interval is known to the detector, designing algorithms to detect the primary user signal. Few algorithms are designed to estimate the range of the noise uncertainty. This paper presents an algorithm for energy detection based on noise variance estimation that can be relatively accurate estimated the noise uncertainty interval. The simulation results show that in the case of the noise uncertainty interval is unknown to the detector, our proposed algorithm can detect well, which is similar to the theoretical detection, and its complexity is also very low.