利用协方差矩阵信息的多天线频谱感知算法

A Multiple Antennas Spectrum Sensing Method by Using the Information of Covariance Matrix

为了降低多天线信号频谱偏移、相位随机性和噪声的不均匀性、不确定性对频谱感知性能的影响,该文利用接收信号协方差矩阵主对角线包含主用户的主要信息,以及协方差矩阵元素的平均方差反映元素波动程度的特点,构造对角线元素绝对值的平方和与其平均方差之比的频谱感知的检验统计量,推导了该统计量服从的概率分布函数,在给定虚警概率的情况下,可推得判决门限。在瑞利衰落信道和AWGN(加性高斯白噪声)信道下的仿真结果表明:本文算法性能优于局部方差法,随着接收天线数和采样点数增加,本文算法性能提升大于局部方差法。

In order to reduce the impacts of multiple antennas signals＇ frequency offset, random phase and the nonunifor- mity, uncertainty of noise on spectrum sensing performance, a spectrum sensing method is proposed, whose detection sta- tistics is the ratio of the sum of the squares of the main diagonal elements＇ absolute values of the covariance matrix to its mean variance, because the main diagonal elements of the covariance matrix include primary users＇ major information, as well as, the mean variance of covariance matrix elements reveals the degree of elements＇ fluctuation. The probability density function of the test statistics is derived and a detection threshold with a given false alarm probability is obtained. The simu- lation results in Additive White Gaussian Noise （AWGN） channel and Rayleigh fading channel show that the proposed al- gorithm is better than the local variance algorithm. As the number of the receiving antennas and the sampling number in- crease, the proposed algorithm has a larger performance improvement than the local variance algorithm.