In this paper, we introduce new totally blind spectrum sensing (SS) algorithms, for fast time-varying channel, based on eigenvalue decomposition (EVD) of the covariance matrix of the received signal. The new scheme is based on the sliding window whose the size depends on the coherence time of the channel. First, we evaluate the impact of the mobility on the detection performance. Then, by applying EVD in each window, we focus our study on the maximal estimated largest eigenvalue (MELE). We provide simulation results in order to validate the proposed theoretical expression of the probability density function of the MELE. Finally, simulation results illustrate the performance of the contributions and are compared to other SS methods.

在本文中，我们基于接收信号协方差矩阵的特征值分解（EVD），针对快速时变信道引入了新的全盲频谱感测（SS）算法。新方案基于滑动窗口，该滑动窗口的大小取决于通道的相干时间。首先，我们评估迁移率对检测性能的影响。然后，通过在每个窗口中应用EVD，我们将研究重点放在最大估计最大特征值（MELE）上。我们提供仿真结果，以验证提出的MELE概率密度函数的理论表达式。最后，仿真结果说明了贡献的性能，并与其他SS方法进行了比较。