SIMO信道中基于奇异值分解的盲信噪比估计算法

摘要

信噪比(SNR)是现代通信信号处理中一个重要参数,许多算法需要它作为先验信息以获取最佳估计性能.针对单输入多输出(SIMO)系统的信噪比估计问题,本文提出了一种盲信噪比估计算法.该算法利用多路信号协方差矩阵的奇异值分解(SVD),通过计算矩阵的最大特征值实现各路信号信噪比估计.该算法无需知道信号的先验信息,能够对加性高斯白噪声信道(AWGN)和多径信道下常用的数字调制信号进行信噪比估计.仿真结果表明该算法具有良好的估计性能.与单路信号中基于SVD信噪比估计算法相比,该算法无需估计信号空间与噪声空间维数,提高了估计精度,同时大大减小计算复杂度.%SNR( Signal-to-Noise Ratio) is an important parameter in modern communication signal processing, and many algorithms need this information to obtain optimal performance. A new blind SNR estimation algorithm is proposed for signal-to-noise ratio (SNR) estimation over single-input multiple-output ( SIMO) system in this paper. The new SIMO SNR estimation technique is based on singular-value decomposition ( SVD) of received signal covariance matrix, by computing the maximum eigenvalue of the matrix to estimate SNR. The algorithm can estimate the SNR of digital modulation signals commonly used in additional white Gaussian noise (AWGN) channels and multipath channels without prior information of the modulation type. The simulation results show that this algorithm offers excellent performance. Compared with the SVD-based method in single-input single-output( SISO) system, the proposed algorithm can enhance the estimating accuracy without computing the dimensions of signal and noise space, and achieve estimations with a small computational complexity.