基于导频和修正Kalman滤波的MIMO-OFDM信道估计方法

Channel estimation method for MIMO-OFDM systems based on pilots and modified Kalman filter

提出了一种适用于时间频率选择性衰落信道的MIMO-OFDM系统的组合信道估计方法。采用AR过程对信道进行建模,利用基于导频的低维Kalman滤波算法进行信道估计,并采用LS算法估计时变的信道衰减因子。Kalman滤波跟踪了信道的时域相关性,为了同时跟踪信道的频域相关性,采用了一种基于MMSE(minimum mean square error)的合并器对Kalman滤波算法进行修正。仿真表明,提出的这种组合算法降低了传统的Kalman滤波结构的复杂度,能够跟踪信道的时频变化,改进了基于LS准则的信道估计算法,并且与复杂的高维Kalman滤波算法的信道估计性能相当。

A combined channel estimation method of time-frequency-selective fading channels in MIMO-OFDM systems was proposed. The time-varying channel was modeled as an autoregressive （AR） process and a low-dimensional Kalman filter based on pilots was used to estimate the AR parameters, and the LS（least square） algorithm was adopted to track the time-varying channel fading factors. The Kahnan estimator explored the time-domain correlation of the channel, and a minimum mean square error （MMSE） combiner was used to modify the Kalman estimates. The proposed solution could reduce the complexity of the high-dimensional Kalman filter and track the channel both in frequency and time domains. The simulation results show that this method improves the LS estimates and has a comparable performance to the complex high-dimensional Kalman channel estimation method.