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High-speed SSB transmission with a silicon MZM and a soft combined artificial neural network-based equalization
Optics Letters ( IF 3.1 ) Pub Date : 2020-03-31 , DOI: 10.1364/ol.386181
Hao Ming , Lei Zhang , Fan Yang , Xiaoke Ruan , Fan Zhang

We experimentally demonstrate high-speed metro-scale optical transmission of a single sideband (SSB) 4-ary pulse amplitude modulation (PAM-4) signal based on a silicon photonic dual-drive Mach–Zehnder modulator (MZM). We propose a novel, to the best of our knowledge, artificial neural network (ANN) structure of soft combined ANN (SC-ANN) to compensate for both linear and nonlinear impairments of the signal. SC-ANN obtains the enhanced performance by averaging the outputs of conventional ANN with different sizes. With the help of the SC-ANN, we achieve a 320 km standard single-mode fiber (SSMF) transmission of 184 Gb/s (92Gbaud) PAM-4 with a bit-error rate (BER) below the 20% soft-decision forward error-correction (SD-FEC) threshold of ${2.4} \times {{10}^{ - 2}}$, and the optical signal-to-noise ratio (OSNR) penalty is only 0.3 dB compared to the back-to-back (BTB) results.

中文翻译:

带有硅MZM和基于软组合人工神经网络的均衡的高速SSB传输

我们实验证明了基于硅光子双驱动马赫曾德尔调制器(MZM)的单边带(SSB)四进制脉冲幅度调制(PAM-4)信号的高速城域规模光传输。据我们所知,我们提出了一种新颖的软组合人工神经网络(SC-ANN)的人工神经网络(ANN)结构,以补偿信号的线性和非线性损伤。SC-ANN通过平均具有不同大小的常规ANN的输出来获得增强的性能。借助SC-ANN,我们实现了184 Gb / s(92Gbaud)PAM-4的320 km标准单模光纤(SSMF)传输,且误码率(BER)低于20%的软判决前向纠错(SD-FEC)阈值$ {2.4} \ times {{10} ^ {-2}} $,与背对背(BTB)结果相比,光信噪比(OSNR)损失仅为0.3 dB。
更新日期:2020-04-01
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