In order to track a changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is a priority to estimate channel impulse response adaptively. In this paper, we propose an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weigh the past observations; thus, the cost function can be constructed via a weighted least squares criterion. The minimization of the cost function is equivalent to the decomposition of a third-order tensor, which consists of the weighted OFDM data symbols. By preserving the Khatri-Rao product, we used a recursive least squares solution to update the estimated subspace at each time instant, then the channel parameters can be estimated adaptively, and the algorithm achieves superior convergence performance. Simulation results validate the effectiveness of the proposed algorithm.

中文翻译：

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MIMO-OFDM系统的联合自适应盲信道估计和数据检测

为了在多输入多输出正交频分复用（MIMO-OFDM）系统中跟踪变化的信道，自适应地估计信道冲激响应是优先事项。本文提出了一种基于并行因子分析的自适应盲信道估计方法。我们使用指数窗口权衡了过去的观察结果；因此，可以通过加权最小二乘准则构造成本函数。代价函数的最小化等效于由加权OFDM数据符号组成的三阶张量的分解。通过保留Khatri-Rao乘积，我们使用递归最小二乘解在每个时刻更新估计的子空间，然后可以自适应地估计信道参数，该算法具有优越的收敛性能。仿真结果验证了所提算法的有效性。