自适应非零延迟MMSE盲均衡算法

An Adaptive Non-Zero Delay MMSE Blind Equalization Algorithm

针对单输入多输出(SIMO)模型提出一种基于非零延迟均衡器的自适应最小均方误差(MMSE)盲均衡算法,该方法通过均衡器系数、不同延迟下的截短协方差矩阵及信号子空间三者之间的关系将零延迟均衡器推广到非零延迟均衡器。该方法不同于传统的零延迟均衡算法,可利用信道的多阶参数进行盲均衡使其减小信道一阶参数对均衡效果的影响,且对信道阶数过估计具有鲁棒性。文章给出了算法的Batch实现过程,同时为更好地适应一般时变信道环境和实现实时处理的要求,利用快速次子空间追踪算法(FDPM)通过递归迭代得到算法的自适应实现过程。仿真实验表明在信道一阶参数能量较小或信道阶数过估计的条件下,即使信噪比较低,算法仍具有良好的均方误差(MSE)性能,此外自适应算法能够在几百个样本值内使信号快速达到收敛。

In view of SIMO model,an adaptive MMSE blind equalization algorithm is proposed based on the non-zero delay equalizer.The method,through the relationships between the equalizer coefficients,the Variance matrices and the signal subspaces,is to extend the zero-delay equalizer to a non-zero delay equalizer.This method is different from the traditional zero-delay equalization algorithm,and can be utilized by the channel's multi-level parameters for performing blind equalization to reduce the influence of the firstorder parameters of the channel on the equalization effect,and has robust to the overestimation of the channel order.In order to better adapt to the general time-varying channel environment and realize the real-time processing requirements,this paper presents a fast implementation of the algorithm by FDPM through recursive iteration.The simulation experiments show that the algorithm still has a good Mean Square Error (MSE)performance even if the signal-to-noise ratio is low under the condition that the firstorder energy of the channel is small or the channel order is overestimated.In addition,the adaptive algorithm can quickly converge within a few hundred sample values.