基于粒子滤波的MIMO-OFDM时变信道半盲估计

Particle filtering based semi-blind estimation for MIMO-OFDM time-varying channel

提出一种基于粒子滤波的MIMO-OFDM时变信道半盲估计方法。首先,对粒子滤波算法进行改进,通过对采样粒子分布进行局部优化调整,提出一种局部优化粒子滤波算法。然后,将该粒子滤波算法用于MIMO-OFDM时变信道估计。由于该信道估计过程在频域进行,因而无需已知(或估计)多径信道长度。与现有时变信道半盲估计方法相比,本方法具有估计误差低、对非高斯噪声顽健性强等特点,从而有效改善了接收端的符号检测性。计算机仿真结果证明了本方法的有效性。

A semi-blind channel estimation method based on the particle filtering was proposed for the MIMO-OFDM wireless communication system. By optimizing the particles distribution locally, the traditional particle filtering algorithm was modified, and a local optimized particle filtering was proposed. This local optimized particle filtering can achieve the low MSE, and improve the precision of the MIMO-OFDM time-varying channel estimation. Since this method was performed in frequency domain, it was not necessary to know （or estimate） the length of the channel. Compared with existing approaches, the proposed method was more robust to the non-gauss distribution noise and the detection performance is nearly optimal. The simulation results show the effectiveness of the proposed method.