为应对概率整形场景下载波相位恢复的问题,提出了一种基于统计分析的自适应算法。利用核密度估计进行概率整形信号的参数估计,从而估计得到信息熵,以辅助后续的基于半径定向的4次方频偏估计算法。运用估计出的概率整形参量进行信号的针对性归一化,用于后续基于盲相位搜索的载波相位噪声恢复。对该算法的频偏估计范围、信噪比及激光线宽容忍度进行了仿真分析。结果表明,所提方案能够应对不同的概率整形强度,在较大的信噪比范围内均能实现良好的载波相位恢复。此外,相对于用于标准信号的载波相位恢复算法,该方案达到最优性能时所需的滑动窗口长度更短并且拥有更高的估计精度。

To deal with the problem of carrier phase recovery in the probabilistic shaping (PS) scenarios, this paper proposed an adaptive algorithm based on statistical analysis. First, kernel density estimation was used for parameter estimation of the PS signals, and thereby the information entropy was estimated to assist the subsequent fourth-power frequency offset estimation (FOE) algorithm based on radius orientation. Then the estimated PS parameters were adopted to carry out targeted normalization of the signals for carrier phase noise recovery based on blind phase search. Furthermore, the FOE range, signal-to-noise ratio (SNR), and laser linewidth tolerance of the algorithm were simulated and analyzed. The results show that the proposed scheme can cope with different PS intensities and achieve good carrier phase recovery in a wide SNR range. In addition, compared with the carrier phase recovery algorithm for standard signals, the proposed scheme requires a shorter sliding window and has higher estimation accuracy when achieving optimal performance.