CAJ | 학술논문

维纳滤波和卡尔曼滤波都是基于最小均方误差准则的滤波方法，本文主要研究这两种滤波方法在OFDM信道估计中的应用。为了跟踪频率选择性信道的变化，采用在OFDM系统中易于实现的梳状导频进行研究。传统的MMSE在统计意义上是最好的线性估计器，但是需要对矩阵求逆，是一种计算量较大，算法较复杂的方法。LMMSE是频域维纳滤波方法，其减小了MMSE的复杂度，但只适用于慢衰落信道，针对时变信道，本文提出卡尔曼滤波的信道估计方法，仿真结果表明，卡尔曼滤波的信道估计方法在时变信道中具有良好的性能。
유납려파화잡이만려파도시기우최소균방오차준칙적려파방법，본문주요연구저량충려파방법재OFDM신도고계중적응용。위료근종빈솔선택성신도적변화，채용재OFDM계통중역우실현적소상도빈진행연구。전통적MMSE재통계의의상시최호적선성고계기，단시수요대구진구역，시일충계산량교대，산법교복잡적방법。LMMSE시빈역유납려파방법，기감소료MMSE적복잡도，단지괄용우만쇠락신도，침대시변신도，본문제출잡이만려파적신도고계방법，방진결과표명，잡이만려파적신도고계방법재시변신도중구유량호적성능。
Wiener filter and Kalman filter are based on the minimum mean square error, this paper studies the filtering methods for OFDM channel estimation. In order to track the changes in the frequency selective channel,the comb pilot which is easy to implement in OFDM system is used. In the statistical sense the traditional MMSE is the best linear estimator, but matrix inversion is a large amount of calculation, the algorithm is much complex. LMMSE is a frequency domain Wiener filtering method,which reduces the complexity of the MMSE,but it is only for the slow fading channel. For the time-varying channel,this paper proposes the channel estimation method of Kalman filter. The simulation results show that the channel estimation of Kalman filter has a good performance.