Motivated by emerging technologies for energy efficient analog computing and continuous-time processing, this paper proposes continuous-time minimum mean squared error estimation for multiple-input multiple-output (MIMO) systems based on an ordinary differential equation. Mean squared error (MSE) is a principal detection performance measure of estimation methods for MIMO systems. We derive an analytical MSE formula that indicates the MSE at any time. The MSE of the proposed method depends on a regularization parameter which affects the convergence property of the MSE. Furthermore, we extend the proposed method by using a time-dependent regularization parameter to achieve better convergence performance. Numerical experiments indicated excellent agreement with the theoretical values and improvement in the convergence performance owing to the use of the time-dependent parameter.
翻译:本文在节能模拟计算和连续时间处理新技术的推动下,提出基于普通差分方程的多投入多产出(MIIMO)系统的连续最低平均正方差估计。平均正方差(MSE)是MOIMO系统估算方法的主要检测性能衡量标准。我们得出一个分析性MSE公式,表明在任何时候的MSE值。拟议方法的MSE值取决于一个影响到MSE趋同特性的正规化参数。此外,我们通过使用一个取决于时间的正规化参数来扩大拟议方法的范围,以实现更好的趋同性能。数字实验表明,由于使用时间参数,理论值与趋同性效果的改进非常一致。