QPSK数字接收机中的SNR估计的新方法

通过对基于判决反馈的信噪比最大似然估计推导过程的分析，得出：判决反馈最大似然估计得到的估计值是有偏估计；利用基带数据的高阶矩特性，可以获得渐近无偏估计。该文提出了两种新的SNR的迭代求解方法。一种是基于NDA(Non-Data-Aided)最大似然估计的梯度迭代求解方法，这种方法与其它迭代方法相比，具有更好的收敛性能。另一种是基于统计参量的迭代方法，它不需要对输入数据进行存储；而且在相同的信噪比估计性能下，与其它迭代运算相比，运算量大大降低，尤其适合于低信噪比下信噪比估计要求高的应用中。最后，文章对比了几种SNR估计子的性能与运算量。

New SNR Estimation Methods in Digital QPSK Receiver

SNR maximum likelihood estimator based on data directed decision was evaluated first, and was concluded as a biased estimator. An unbiased estimator can be acquired through high order moments of received data. Two SNR estimators based on iteration method were developed in this paper. One is solving the QPSK NDA maximum likelihood equation by gradient approximation, which has better convergence performance than other methods. The other is based on the statistical parameters of received data, which not only makes received data buffering unnecessary, but also reduces iteration calculation greatly compared with other iteration methods, and more important, not at the cost of estimation performance degradation. Finally, the result of several SNR estimators in performance and calculation were compared and analyzed.