基于扩展卡尔曼滤波的MIMO迭代信道估计方法

MIMO iterative channel estimation based on extended Kalman filter

针对高速移动场景下信道快衰落、非平稳等特性导致下行链路信道估计性能受限的问题,提出了一种适用于高速移动环境下行链路的MIMO信道估计方法。采用自回归过程对信道建模,构造自反馈的扩展卡尔曼滤波器(EKF)追踪信道响应及其时域相关系数。采用迭代接收机的结构解决了在MIMO环境下观测方程欠定的问题。仿真结果表明,在高速移动环境下所提方法相较于最小二乘估计等传统方法提升了信道估计的均方误差和系统的误码率性能,可应用于高速列车无线通信设备的接收机基带信号处理系统。

In high-speed environment, fast fading and non-stationary limits the channel estimation performance, so a channel estimation method for high-speed mobility in MIMO downlink was proposed. A self-feedback extended Kalman filter （EKF） was set UP to track the channel response and correlation parameters. An iterative detector ＆ de- coder receiver was adopted to deal with the problem that the observation equation is an underdetermined equation. The simulation results show that compared with least squares（LS） in high speed environment, the proposed method improves the channel estimation accuracy and performance of whole system. And it could be applied in baseband signal processing of wireless receiver in high-speed train.