MIMO-OFDM系统基于指数平滑的改进信道估计算法

Improved Channel Estimation Algorithm Based on Exponential Smoothing for MIMO-OFDM System

多输入多输出-正交频分复用(MIMO-OFDM)系统在时变信道中,最小二乘(LS)信道估计算法估计精度低。为了解决这一问题,提出了基于指数平滑的改进信道估计算法,将LS信道估计算法和指数平滑理论相结合,充分利用时变信道的变化规律及指数平滑算法抑制随机干扰的等效低通滤波特性,通过迭代运算,将前一时刻的预测结果用于预测当前时刻的信道估计值。因此,指数平滑算法可以有效抑制LS信道估计算法中的加性高斯白噪声(AWGN),提升信道估计精度。仿真结果表明,与经典信道估计算法相比,本文提出的算法在时变以及低信噪比环境中,可有效提升信道估计精度,且改进算法的运算复杂度低。

In order to solve the problem that the estimation accuracy of least square (LS) channel estimation algorithm is low for multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system in time-varying channel,this paper puts forward an improved channel estimation method based on exponential smoothing algorithm (ESA),which combines LS channel estimation algorithm with ESA theory,fully exploits the change rule of time-varying channel and equivalent low-pass filtering speciality that ESA suppresses random jamming,adopts the predicted results of previous moment to predict the channel estimation value of this moment through iterative operation,thus the ESA can effectively suppress additive white Gaussian noise (AWGN) in the LS channel estimation algorithm,improve the estimation accuracy of the channel.Simulation results show that the proposed algorithm can effectively promote channel estimation accuracy with low computational complexity under time-varying channel and low signal to noise ratio (SNR) environment compared with classical channel estimation algorithms.