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arXiv 1705.01367cs.ITmath.IT
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无中继光纤传输中概率整形方法的实验比较

Experimental Comparison of Probabilistic Shaping Methods for Unrepeated Fiber Transmission

Julian Renner, Tobias Fehenberger, Metodi P. Yankov, Francesco Da Ros, Søren Forchhammer, Georg Böcherer, Norbert Hanik

摘要:

本文研究了概率整形对背靠背结构和非重复非线性光纤传输中有效信噪比(SNR)和可达信息速率(AIR)的影响。对于背靠背,各种形状的正交幅度调制(QAM)分布被发现具有相同的实现惩罚均匀输入。通过在传输实验中证明,在固定的平均发射功率下,整形QAM输入导致比均匀输入更低的有效SNR,我们在实验上证实了整形增强了光纤非线性。然而,最终发现整形增加了AIR,这是最相关的品质因数,因为它与频谱效率直接相关。在这些整形增益的非线性光纤信道的详细研究中,四种策略优化QAM输入分布进行了评估和实验比较波分复用(WDM)系统。第一整形方案基于线性加性高斯白噪声信道生成麦克斯韦-玻尔兹曼(MB)分布。第二种策略使用Blahut-Arimoto算法来优化基于分步傅立叶方法的信道模型的无约束QAM分布。在第三种和第四种方法中,MB形QAM和无约束QAM通过增强型高斯噪声(EGN)模型进行优化。虽然绝对整形增益被发现是相对较小的,EGN优化的无约束分布的线性AWGN优化的MB分布的相对改善高达59%。在9通道和满载WDM实验中观察到这种一般行为。

英文摘要:

This paper studies the impact of probabilistic shaping on effective signal-to-noise ratios (SNRs) and achievable information rates (AIRs) in a back-to-back configuration and in unrepeated nonlinear fiber transmissions. For back-to-back, various shaped quadrature amplitude modulation (QAM) distributions are found to have the same implementation penalty as uniform input. By demonstrating in transmission experiments that shaped QAM input leads to lower effective SNR than uniform input at a fixed average launch power, we experimentally confirm that shaping enhances the fiber nonlinearities. However, shaping is ultimately found to increase the AIR, which is the most relevant figure of merit as it is directly related to spectral efficiency. In a detailed study of these shaping gains for the nonlinear fiber channel, four strategies for optimizing QAM input distributions are evaluated and experimentally compared in wavelength division multiplexing (WDM) systems. The first shaping scheme generates a Maxwell-Boltzmann (MB) distribution based on a linear additive white Gaussian noise channel. The second strategy uses the Blahut-Arimoto algorithm to optimize an unconstrained QAM distribution for a split-step Fourier method based channel model. In the third and fourth approach, MB-shaped QAM and unconstrained QAM are optimized via the enhanced Gaussian noise (EGN) model. Although the absolute shaping gains are found to be relatively small, the relative improvements by EGN-optimized unconstrained distributions over linear AWGN optimized MB distributions are up to 59%. This general behavior is observed in 9-channel and fully loaded WDM experiments.

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