非高斯背景下基于信号相关性的频谱感知算法

Signal Correlation Based Spectrum Sensing Algorithm in Non-Gaussian Background

本文研究了一类Laplace非高斯背景噪声下的频谱检测问题,提出一种基于采样信号相关性的多用户协作频谱感知算法。此算法利用接收信号的统计相关性,设计了一种将协作用户统计协方差之和作为检测统计量的频谱检测算法,推导了该检测算法的统计门限、检测概率和虚警概率的闭式表达式。通过蒙特卡罗仿真,分析比较了Laplace非高斯噪声背景下新算法与已有算法在不同信噪比下的感知性能,理论分析与仿真结果验证了所提算法的有效性。

This paper studies spectrum detection problem in Laplace non-Gaussian noise background,and proposes a multi-user cooperative spectrum sensing algorithm based on the correlation of sampled signals.In this algorithm,based on the statistical correlation of received signals,the sum of statistical covariance of cooperative users is used as the detection statistic,and the closed form expressions of statistical threshold,detection probability,and false alarm probability of the detection algorithm are also derived.Through Monte Carlo simulation,the performance of the new algorithm and the related algorithms under the background of Laplace noise is analyzed and compared under different signal-to-noise ratios.The theoretical analysis and simulation results verify the effectiveness of the proposed algorithm.