基于人工神经网络均衡器的高容量相干光OFDM信号光纤损伤补偿

2014 9th International Symposium on Communication Systems, Networks & Digital Sign (CSNDSP) Pub Date : 2014-07-23 DOI:10.1109/CSNDSP.2014.6923996

M. Jarajreh, S. Rajbhandari, E. Giacoumidis, N. Doran, Zabih Ghassemlooy

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引用次数: 5

摘要

针对相干光OFDM (C-OOFDM)信号的传输性能增强，提出了一种人工神经网络均衡器。与最小均方(LMS)相比，ANN均衡器在对抗色散(CD)和单模光纤(SMF)引起的非线性方面表现出更高的效率。在仅考虑CD的情况下，该均衡器在40 Gbit/s C-OOFDM信号的光信噪比(OSNR)比LMS算法提高1.5 dB。研究还表明，与LMS相比，ANN算法可以将SMF的传输距离提高一倍，最高可达320 km，非线性容差提高约0.7 dB OSNR。

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Fibre impairment compensation using artificial neural network equalizer for high-capacity coherent optical OFDM signals

We propose an artificial neural network (ANN) equalizer for transmission performance enhancement of coherent optical OFDM (C-OOFDM) signals. The ANN equalizer showed more efficiency in combating both chromatic dispersion (CD) and single-mode fibre (SMF)-induced non-linearities compared to the least mean square (LMS). The equalizer can offer a 1.5 dB improvement in optical signal-to-noise ratio (OSNR) compared to LMS algorithm for 40 Gbit/s C-OOFDM signals when considering only CD. It is also revealed that ANN can double the transmission distance up to 320 km of SMF compared to the case of LMS, providing a nonlinearity tolerance improvement of ~0.7 dB OSNR.

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2014 9th International Symposium on Communication Systems, Networks & Digital Sign (CSNDSP)

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