一种基于噪声方差估计的自适应多门限能量检测算法

Algorithm for adaptive multi-threshold energy detection based on noise variance estimation

能量检测因其复杂度低的优势被广泛应用于空闲频谱感知中,但其性能受噪声方差不确定性影响严重。已有研究给出了一些解决方案,但是,大部分都是假设检测器对噪声的不确定性区间已知的情况下设计算法来进行主用户检测,很少有算法来估计噪声不确定区间。文中提出了一种基于噪声方差估计的自适应多门限能量检测算法,能较为精确地估计噪声方差不确定区间,从而自适应地设置判决多门限。仿真结果表明,在检测器对噪声不确定区间未知的情况下,文中算法得到的检测性能和理论检测性能非常接近。

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. Previous solutions for resisting the effects on the noise uncertainty are proposed. However, most studies 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 adaptive multi-threshold energy detection based on the noise variance estimation and the algorithm can estimate the noise uncertainty interval and adaptively adjust the multi- threshold parameters. The simulation results show that in the case of the noise uncertainty interval is un- known to the detector, the detection performance of the algorithm is similar to that of the theoretical detection.