高速场景下基于叠加导频的迭代EKF信道估计方法

针对正交频分复用（Orthogonal Frequency Division Multiplexing，OFDM）系统在高速移动场景下时/频域选择性衰落（双选衰落）和非平稳特性给信道估计带来的技术挑战，本文采用导频与数据叠加的帧结构，提出一种基于基扩展模型（Basis Expansion Model，BEM）的迭代扩展卡尔曼滤波（iterative Extend-Kalman Filter，iEKF）信道估计方法.基于BEM信道模型且采用EKF信道估计方法可以联合估计出信道冲激响应（Channel Impulse Response，CIR）与时变的时域自相关系数，有效消除子载波间干扰（Inter Carrier Interference，ICI）.同时，为了进一步消除叠加导频位置处的数据符号干扰，我们提出将叠加位置处的数据和导频先解耦、后重构再进行迭代EKF的信道估计方法.仿真分析表明，相较传统叠加导频的信道估计方法和导频符号辅助调制（Pilot Symbol Assisted Modulation，PSAM）估计方法，本文提出的信道估计方法在高速场景特别是低信噪比的条件下，具有更高的估计精度，更强的鲁棒性及更大的吞吐量.

Iterative EKF Channel Estimation Method Based on Superimposed Pilot in High Mobility Scenarios

For the technical challenges brought by time/frequency-domain selective fading (double-selective fading) and non-stationary characteristics in channel estimation for orthogonal frequency division multiplexing (OFDM) system,an iterative extend-Kalman filter (iEKF) channel estimation method based on basis expansion model (BEM) with the frame structure of superimposed pilot is proposed.Based on the BEM and the EKF channel estimation method,the channel impulse response (CIR) and the time-varying time-domain autocorrelation coefficient can be jointly estimated to effectively eliminate inter carrier interference (ICI).At the same time,it's need to eliminate the interference of data symbols at the superimposed position.So for the superimposed position,the channel estimation is proposed in which decoupling data and pilot firstly,reconstructing subsequently,and performing the iEKF algorithm finally.The simulation analysis shows that compared with the traditional superimposed pilot channel estimation method and the pilot symbol assisted modulation (PSAM) estimation method,the proposed channel estimation method has higher estimation accuracy,stronger robustness and greaterer throughput in high-speed railway scenario especially under low signal-to-noise ratio (SNR) conditions.