Improved Kalman filter channel estimation method for OFDM systems in fast time-varying environment  

一种快衰落信道中OFDM系统的Kalman信道估计方法(英文)

作　　者：宋晓晋[1] 宋铁成[1] 沈连丰[1] 陆苏[1] 

机构地区：[1]东南大学移动通信国家重点实验室,南京210096

出　　处：《Journal of Southeast University(English Edition)》2005年第4期389-392,共4页东南大学学报（英文版）

基　　金：TheNationalNaturalScienceFoundationofChina(No.60472053),theNationalHighTechnologyResearchandDevelopmentProgramofChina(863Program)(No.2003AA1Z1110),theHighTechnologyResearchandDevelopmentProgramofJiangsuProvince(No.BG2003004),theKeyProjectofChineseMinistryofEducation(No.02171).

摘　　要：Under analyzing several characteristics of frequency-selective fast fading channels, such as large Doppler spread and multi-path interference, a low-dimensional Kalman filter method based on pilot signals is presented for the channel estimation of orthogonal frequency division multiplexing （OFDM） systems. For simplicity, a one-dimensional autoregressive （AR） process is used to model the time-varying channel, and the least square （LS） algorithm based on pilot signals is adopted to track the time-varying channel fading factor a. The low-dimensional Kalman filter estimator greatly reduces the complexity of the high-dimensional Kalman filter. To utilize the relationship of fading channel in frequency domain, a minimum mean-square-error （MMSE） combiner is used to refine the estimation results. The simulation results in the frequency band of 5.5 GHz show that the proposed method achieves a good symbol error rate （SER） performance close to the theoretical bound of ideal channel estimation.针对频率选择性快衰落信道的多径干扰和较大的多普勒频率扩展,提出了一种基于导频的低维Kalman滤波算法用于正交频分复用(OFDM)系统信道估计.为了简化计算,采用一阶自回归(AR)过程对时变信道进行建模.利用复杂度大大降低的一维Kalman滤波算法进行单个子载波的并行信道估计,并采用基于导频的最小平方(LS)算法估计时变的信道衰减因子a.为了同时跟踪信道的频域相关性,采用了最小均方误差(MMSE)线性合并器对Kalman信道估计结果进行修正.在5.5GHz频段上的仿真表明了这种基于导频的低维Kalman信道估计方法,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,并且在一定程度上可以接近于理想信道估计的误码率性能.

关 键 词：channel estimation orthogonal frequency division multiplexing （OFDM） least square （LS） minimum mean-square-error （MMSE） 

分 类 号：TN914.3[电子电信—通信与信息系统]