基于训练序列的光信道估计

大气信道的复杂性会引起信道状态参数的随机变化,这对通信系统性能有很大影响。为此,研究了基于训练序列的沙尘光信道估计,以m序列为训练序列,采用时分复用方式构建了一种基于训练序列的光信道估计方案。该方案利用训练序列中的0序列,构造了一种噪声方差的估计方法。在此基础之上,研究了最小均方误差(MMSE)准则下不同散射路径数和训练序列长度对估计均方误差(MSE)和系统误码性能的影响。研究结果表明,在小信噪比的大气信道中,MMSE准则下散射路径数不宜超过5,m序列长度选63为宜。

Optical channel estimation based on training sequence

The complexity of atmospheric channel will cause the random change of channel state parameters, which will have great influence on communication system performance.Thus, the dust optical channel estimation based on training sequence is researched in this paper.Choosing the m sequence as training sequence and adopting time division multiplexing (TDM) technology, an estimation scheme is constructed based on training sequence.Employing the 0 sequence of the training sequence, a noise variance estimation method is constructed in this scheme.On this basis, the impacts of the scattering path number and the training sequence length on the mean square error (MSE) of channel estimation and bit error performance under MMSE criterion are researched.The results show that the number of scattering path should not exceed 5, and 63 is an appropriate choice for m sequence length under MMSE criterion for the low signal to noise ratio atmospheric channel.