基于叠加训练序列快速信道辨识方法

Fast channel estimation using superimposed training

信道状态信息(CSI)对于无线通信来说至关重要,而叠加训练序列的信道估计方法由于不占用额外的信号带宽和具有较高的估计精度而受到人们的注意。本文从算法的复杂度入手,分析了不同的训练序列对算法复杂度的影响,并且在训练序列为PN序列下,利用循环Toeplitz矩阵的特性,得到了信道估计的快速算法。仿真实验的结果表明,这种算法不需要矩阵求逆、计算量小,估计精度高,有很大的实际应用前景。

Channel state information （CSI） is of great importance to wireless communications. Due to its virtue of not taking any extra signal spectral and having high accuracy, superimposed-pilot-based channel estimation method has received more attention. Proceeding with the algorithm＇s complexity, this paper analyzes the effects of different training sequences on the algorithm＇s complexity and deduced a fast channel estimation algorithm using the property of circulant Toeplitz matrix when using PN sequences as training sequences. Simulation results show that while the algorithm needs no matrix inverse and has little computation load it acquires high estimation accuracy.