MPSK信号的最大似然SNR估计方法

该文利用最大似然准则分别推导了对于MPSK信号的数据辅助SNR估计方法、判决指向SNR估计方法和一种新的盲信噪比估计方法。文章对这些算法的性能进行了分析和计算机仿真，并与其它一些SNR估计算法进行了比较。分析和仿真的结果显示数据辅助的SNR方法性能优越，很好地符合了信噪比估计性能下限(CRLB)。判决指向算法性能依赖于判决的准确程度，在高信噪比时性能较好；而在低信噪比条件时，特别是小于OdB以后其估计有较大偏差。新的盲SNR估计算法对于BPSK信号具有估计范围广、精度高和复杂度小的特点，但是当M增加时性能会明显下降。

On the Maximum-Likelihood SNR Estimation Algorithm for MPSK Signals

The data-aimed (DA) Signal-to-Noise Ratio (SNR) estimation algorithm, Decision-Directed (DD) SNR estimation algorithm and a new blind SNR estimation algorithm for MPSK signals are presented in this paper with maximum-likelihood principle. The detail performance analysis, computer simulation and performance comparing with other SNR estimation algorithms are completed. The analysis and simulation results show that the DA algorithm has a perfect performance and as good as the performance lower bounds. The performance of DD algorithm depends directly on the accuracy of decision, so it is good when the SNR is high. But when the SNR is low and, especially, less than 0dB, the estimation has relatively great bias. The new blind SNR estimation algorithm has broad estimation range, good performance and low computational complexity for M=2 (BPSK), but the performance degrades while M is increasing.