Nonlinear phase noise tolerance for coherent optical systems using soft-decision-aided ML carrier phase estimation enhanced with constellation partitioning

Nonlinear phase noise tolerance for coherent optical systems using soft-decision-aided ML carrier phase estimation enhanced with constellation partitioning
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使用通过星座划分增强的软决策辅助 ML 载波相位估计的相干光学系统的非线性相位噪声容限

DOI:
10.1016/j.optcom.2017.06.098
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发表时间:
2018-02
影响因子:
2.4
通讯作者:
Kam Pooi Yuen
Kam Pooi Yuen
中科院分区:
物理与天体物理3区
文献类型:
--
作者:
Li Yan;Wu Mingwei;Du Xinwei;Xu Zhuoran;Gurusamy Mohan;Yu Changyuan;Kam Pooi Yuen

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提出了一种新的软决策辅助最大似然(SDA-ML)载波相位估计方法及其简化版本,在非线性相位噪声占主导的信道中对决策辅助和软决策辅助最大似然(DA-SDA-ML)方法进行了测试。数值计算结果表明,在恒幅调制系统中,SDA-ML和DA-SDA-ML方法的性能都优于传统的DA-ML方法。此外,还提出了基于星座划分的改进算法。通过划分,改进的SDA-ML和DA-SDA-ML可用于补偿多电平调制系统中的非线性相位噪声。
A novel soft-decision-aided maximum likelihood (SDA-ML) carrier phase estimation method and its simplified version, the decision-aided and soft-decision-aided maximum likelihood (DA-SDA-ML) methods are tested in a nonlinear phase noise-dominant channel. The numerical performance results show that both the SDA-ML and DA-SDA-ML methods outperform the conventional DA-ML in systems with constant-amplitude modulation formats. In addition, modified algorithms based on constellation partitioning are proposed. With partitioning, the modified SDA-ML and DA-SDA-ML are shown to be useful for compensating the nonlinear phase noise in multi-level modulation systems.
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