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All-optical polarization control and noise cleaning based on a nonlinear lossless polarizer

机译:基于非线性无损偏振器的全光偏振控制和噪声消除

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We propose an all-optical fiber-based device able to accomplish both polarization control and OSNR enhancement of an amplitude modulated optical signal, affected by unpolarized additive white Gaussian noise, at the same time. The proposed noise cleaning device is made of a nonlinear lossless polarizer (NLP), that performs polarization control, followed by an ideal polarizing filter, that removes the orthogonally polarized half of additive noise. The NLP transforms every input signal polarization into a unique, well denned output polarization (without any loss of signal energy) and its task is to impose a signal polarization aligned with the transparent eigenstate of the polarizing filter. In order to effectively control the polarization of the modulated signal, we show that two different NLP configurations (with counter- or co-propagating pump laser) are needed, as a function of the signal polarization coherence time. The NLP is designed so that polarization attraction is effective only on the "noiseless" (i.e., information-bearing) component of the signal and not on noise, that remains unpolarized at the NLP output. Hence, the proposed device is able to discriminate signal power (that is preserved) from in-band noise power (that is partly suppressed). Since signal repolarization is detrimental if applied to polarization-multiplexed formats, the noise cleaner application is limited here to "legacy" links, with 10 Gb/s OOK modulation, still representing the most common format in deployed networks. By employing the appropriate NLP configurations, we obtain an OSNR gain close to 3dB. Furthermore, we show how the achievable OSNR gain can be estimated theoretically.
机译:我们提出了一种基于全光纤的设备,该设备能够同时完成受非偏振加性高斯白噪声影响的调幅光信号的偏振控制和OSNR增强。所提出的噪声净化设备由非线性无偏振器(NLP)制成,该偏振器执行偏振控制,然后是理想的偏振滤波器,该滤波器消除了正交偏振的附加噪声的一半。 NLP将每个输入信号偏振转换为唯一的,确定好的输出偏振(不损失任何信号能量),NLP的任务是施加与偏振滤波器的透明本征态对齐的信号偏振。为了有效地控制调制信号的极化,我们表明需要两个不同的NLP配置(带有反向传播或共同传播的泵浦激光器),作为信号极化相干时间的函数。 NLP被设计为使得极化吸引仅对信号的“无噪声”(即,承载信息)分量有效,而对在NLP输出端保持非极化状态的噪声无效。因此,所提出的设备能够区分(保留的)信号功率与带内噪声的功率(被部分抑制)。由于如果将信号重新极化应用于极化多路复用格式,则是有害的,因此此处的噪声清除器应用仅限于具有10 Gb / s OOK调制的“旧式”链路,仍然代表已部署网络中最常见的格式。通过采用适当的NLP配置,我们可以获得接近3dB的OSNR增益。此外,我们展示了如何从理论上估计可实现的OSNR增益。

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