徐家品, 杨智. 基于随机矩阵特征值比的频谱感知改进算法[J]. 电波科学学报, 2015, 30(2): 282-288. doi: 10.13443/j.cjors.2014042901
      引用本文: 徐家品, 杨智. 基于随机矩阵特征值比的频谱感知改进算法[J]. 电波科学学报, 2015, 30(2): 282-288. doi: 10.13443/j.cjors.2014042901
      XU Jiapin, YANG Zhi. Improved spectrum sensing algorithms based on eigenvalue ratio of random matrix[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2015, 30(2): 282-288. doi: 10.13443/j.cjors.2014042901
      Citation: XU Jiapin, YANG Zhi. Improved spectrum sensing algorithms based on eigenvalue ratio of random matrix[J]. CHINESE JOURNAL OF RADIO SCIENCE, 2015, 30(2): 282-288. doi: 10.13443/j.cjors.2014042901

      基于随机矩阵特征值比的频谱感知改进算法

      Improved spectrum sensing algorithms based on eigenvalue ratio of random matrix

      • 摘要: 针对认知无线电中现有频谱感知方法的不足, 利用大维随机矩阵理论分析了随机矩阵的渐近谱特性, 研究了接收信号样本协方差矩阵平均特征值的分布特性, 提出两种基于随机矩阵特征值比的频谱感知改进算法.改进算法不需要知道主用户信号的先验信息, 也不需要知道背景噪声的功率, 得到的判决阈值也具有十分简单的闭式表达式.仿真结果表明, 在低样本点、低协作用户数、低信噪比和低虚警概率的条件下, 改进算法也可以获得很好的感知性能.

         

        Abstract: Aiming at the shortcomings of the existing spectrum sensing methods in cognitive radio, two improved algorithms based on the eigenvalue ratio of random matrix are proposed through using the property of asymptotic spectrum of random matrix by means of random matrix theory and researching distribution of average eigenvalue of the covariance matrix of the received signals. Improved algorithms not only need neither the prior knowledge of primary signal, nor the power of background noise, but also have quite simple closed form expressions. Simulation results show that the improved algorithms can get a good performance even under the situation of few samples, few collaborative users, low signal to noise ratio and low false alarm probability.

         

      /

      返回文章
      返回