基于随机矩阵理论的DET合作频谱感知算法

针对认知无线电系统中的频谱感知问题，该文采用随机矩阵理论(Random Matrix Theory, RMT)对多认知用户(Secondary User, SU)接收信号采样协方差矩阵的最大特征值的分布特性进行了分析和研究，提出了一种新的基于双特征值判决门限(Double Eigenvalue Threshold, DET)的合作频谱感知算法。由该算法感知性能的理论分析可知:DET合作感知算法无需主用户(Primary User, PU)发射机信号的先验知识，也不需要预先知道信道背景噪声功率。仿真结果表明，与传统的频谱感知方法相比，该方法只需较少的认知用户就能获得较高的感知性能，并且对噪声的不确定性具有较强的鲁棒性。

DET Cooperative Spectrum Sensing Algorithm Based on Random Matrix Theory

In this paper, the DET (Double Eigenvalue Threshold) cooperative spectrum sensing algorithm is proposed through analyzing maximum eigenvalue distribution of the covariance matrix of the received signals by means of random matrix theory. DET cooperative sensing algorithm needs neither the prior acknowledge of the signal transmitted from primary user, nor the noise power in advance. Simulation results show that the proposed scheme can gain higher sensing performance with a few of secondary users and is more robust to the noise uncertainty compared with the conventional sensing schemes.