一种子空间分解的MIMO-OFDM半盲信道估计方法

Subspace-based semi-blind channel estimation for MIMO-OFDM systems

信道估计是MIMO-OFDM系统实现优良传输的一项重要环节。半盲信道估计算法是将MIMO-OFDM信道矩阵进行分解,分别利用未知数据和已知导频信息来完成信道估计。在利用未知数据进行估计时,提出一种利用频域子载波分组的子空间分解方法,不仅降低了计算复杂度,而且同时提高了信道估计的精度。利用已知的导频信息和未知数据估计出来的结果,可以求得最后的信道矩阵。相对于传统的频域子空间分解的半盲估计方法,算法可以减小计算复杂度80%,同时提高了估计精度平均1～2dB。仿真结果证明了算法具有良好的性能表现。

The channel estimation plays an important role in the MIMO-OFDM systems to achieve the high transmission performance. A new semi-blind channel estimation based on subspace for MIMO-OFDM systems is proposed. The channel matrix is decomposed by two parts. The first part is estimated by received data using the subspace method. By exploiting the frequency correlation among adjacent OFDM subearriers, the method can reduce the computational complexity by 80 percent and performance is improved by 1-2 dB, compared with the classical method. The second part is a rotation matrix, which is estimated by employing pilot symbols. The proposed method is validated through computer simulation-based experimentations, and simulation results show the effectiveness of the algorithm.