摘要
广义SSME算法(GSSME:Generalized Split-Symbol Moment Estimator)是在SSME算法的基础上把每个符号均匀分成多段而得来的。本文提出了复数加性高斯白噪声中基于迭代GSSME算法的MPSK信号盲信噪比估计算法,推导了每符号采样点数和分段数之间的关系。分别对BPSK、QPSK和8PSK信号进行了计算机仿真,并与常规SSME算法进行了比较。结果表明当信噪比高于一定值时,迭代的GSSME算法能达到更小的偏差和均方误差,并且估计性能与MPSK信号的调制阶数M无关。
The Generalized Split-Symbol Moment Estimator (GSSME) comes from the SSME with the change that the symbol interval is divided into several subintervals greater than two as that in the SSME. An iterative GSSME-based blind Signal-to-Noise (SNR) estimation algorithm for MPSK signals is presented in this paper,and the relationship between the sample numbers per symbol and the number of subintervals is derived. Simulations are performed for BPSK, QPSK and 8PSK signals, respectively, and compared with the SSME. It is shown that the GSSME can achieve a lower bias and mean square error (MSE) when the true SNR is above certain value. Further the performance of the GSSME is independent of the order M of the MPSK signals.
出处
《信号处理》
CSCD
北大核心
2007年第3期394-397,共4页
Journal of Signal Processing
基金
国防预研项目