基于人工免疫粒子滤波算法的MIMO-SCFDE系统信道估计方法

MIMO-SCFDE Channel Estimation Based on Artificial Immune Particle Filter

针对经典粒子滤波(PF)算法在MIMO-SCFDE系统时变信道估计中出现权值退化的问题,提出了基于人工免疫粒子滤波(AIPF)算法的MIMO-SCFDE系统时变信道估计方法。该方法将人工免疫的思想引入到PF算法中,有效缓解了PF算法权值退化的问题,提高了信道估计的精度。仿真结果表明,相比LS算法,Kalman滤波算法以及经典PF算法,AIPF算法在高斯分布噪声环境以及非高斯分布噪声信道环境下均可以得到较低误码率(BER)以及归一化均方误差(NMSE),而且在非高斯分布噪声环境下具有较好的顽健性,可以有效提高MIMO-SCFDE系统信道估计的性能。

Aiming at the degeneracy phenomenon occurred when particle filter(PF)was used in the channel estimation of MIMO-SCFDE,a channel estimation method based on the artificial Immune particle filter(AIPF)was proposed for the MIMO-SCFDE wireless communication system.Combining the method of artificial Immune with particle filter,it could ameliorate the degeneracy phenomenon effectively,the performance of channel estimation was improved.The simulation results showed that compared with the least squares(LS),the Kalman fiter and the particle filter(PF),the AIPF algorithm could effectively reduce the BER and NMSE of system in gauss channel either in non-gauss channel,and be strong in the enviroment of non-Gaussian distribution noise,the performance of the channel estimation of MIMO-SCFDE would be improved effictively.