认知无线电中基于阵列天线和协方差矩阵的频谱感知算法

该文提出一种基于阵列天线和协方差矩阵的频谱感知算法，该算法能够在噪声不确定性的条件下进行盲频谱感知。该算法在协方差矩阵的基础上，构建新的检测统计量，推导判决门限，对检测统计量与判决门限进行比较进而做出最终判决；在主用户信号到达方向与认知用户接收天线法线方向不一致的情况下，为使认知用户能完全接收主用户信号，利用了阵列天线技术。仿真结果表明，与Zeng等人(2009)提出的绝对值协方差矩阵频谱感知算法(Covariance Absolute Value Spectrum Sensing, CAVSS)相比，该算法判决门限的计算方法更加准确；在相同条件下，该算法的检测概率高于CAVSS。

Spectrum Sensing Algorithm in Cognitive Radio Based on Array Antenna and Covariance Matrix

A spectrum sensing algorithm based on covariance matrix and array antenna is reported. It can perform blind spectrum sensing under a condition of uncertainty noise. The new test statistics for spectrum sensing based on the covariance matrix is constructed and the decision threshold based on the test statistics is derived, thus allowing the comparison of the test statistics with the decision threshold to make a final decision. In order to enable cognitive users to fully receive signals of cognitive primary user in the case that the arrival direction of primary signal and the receiving antenna of cognitive users is not consistent, this algorithm applies array antenna to the spectrum sensing based on covariance matrix. Simulation results show that the performance of the proposed spectrum sensing algorithm is superior to the Covariance Absolute Value Spectrum Sensing (CAVSS) algorithm proposed by Zeng (2009).