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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.
Aiming at the multipath interference of frequency-selective fast fading channel and large Doppler frequency spreading, a pilot-based low-dimensional Kalman filter algorithm is proposed for OFDM channel estimation The first-order autoregressive (AR) process is used to model the time-varying channel, and the one-dimensional Kalman filter with greatly reduced complexity is used to estimate the parallel channel of single subcarrier. The pilot-based Least Squares ) Algorithm to estimate the time-varying channel attenuation factor a. In order to track the channel frequency domain correlation at the same time, a minimum mean square error (MMSE) linear combiner is used to correct the Kalman channel estimation results. The simulation in the 5.5 GHz frequency band shows This pilot-based low-dimensional Kalman channel estimation method reduces the complexity of the traditional Kalman filter structure, tracks the time-frequency variation of the channel, and to a certain extent can be close to the bit error rate performance of the ideal channel estimation.