In this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) systems for mobile users. The signal model of the MIMO-OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. The computational complexity of the proposed algorithm is considerably lower than that of the maximum likelihood-based grid search method. In a simulation, the mean squared error performance of the proposed algorithm was close to the Cramer-Rao lower bound. The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. The results also suggest that the proposed method has reliable tracking performance in Jakes’ channel models.

在本文中，我们提出了一种针对移动用户的多输入多输出正交频分复用（MIMO-OFDM）系统的联合时变载波频率偏移（CFO）和频率选择性信道响应估计方案。介绍了MIMO-OFDM系统的信号模型，并根据最大似然准则推导了联合估计器。所提出的算法可以分为三个主要部分。在提出的算法的第一部分中，使用旋转估计了初始CFO，并将结果用于频域均衡器。在第二部分中，采用迭代方法来定位精细频率峰值，以实现更好的CFO估计。所提出算法的第三部分采用了自适应过程，以获取更新的CFO估计并跟踪参数时变，包括时变CFO和时变通道。所提出的算法的计算复杂度明显低于基于最大似然的网格搜索方法。在仿真中，所提出算法的均方误差性能接近于Cramer-Rao下界。仿真结果表明，所提出的新型联合估计算法提供的误码率性能接近理想信道估计条件。结果还表明，该方法在Jakes信道模型中具有可靠的跟踪性能。所提出的算法的计算复杂度明显低于基于最大似然的网格搜索方法。在仿真中，所提出算法的均方误差性能接近于Cramer-Rao下界。仿真结果表明，所提出的新型联合估计算法提供的误码率性能接近理想信道估计条件。结果还表明，该方法在Jakes信道模型中具有可靠的跟踪性能。所提出算法的计算复杂度明显低于基于最大似然的网格搜索方法。在仿真中，所提出算法的均方误差性能接近于Cramer-Rao下界。仿真结果表明，所提出的新型联合估计算法提供的误码率性能接近理想信道估计条件。结果还表明，该方法在Jakes信道模型中具有可靠的跟踪性能。仿真结果表明，所提出的新型联合估计算法提供的误码率性能接近理想信道估计条件。结果还表明，该方法在Jakes信道模型中具有可靠的跟踪性能。仿真结果表明，所提出的新型联合估计算法提供的误码率性能接近理想信道估计条件。结果还表明，该方法在Jakes信道模型中具有可靠的跟踪性能。