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Combining IST-Based CFO Compensation and Neural Network-Based Demodulation for Eigenvalue-Modulated Signal
Journal of Lightwave Technology ( IF 4.1 ) Pub Date : 2021-09-22 , DOI: 10.1109/jlt.2021.3114427
Ken Mishina , Takaya Maeda , Daisuke Hisano , Yuki Yoshida , Akihiro Maruta

Eigenvalue-based communication technologies using inverse scattering transform (IST) have gained attention as a new transmission strategy in optical fiber communications. In recent years, several studies on artificial neural network (ANN)-based equalization and demodulation schemes for eigenvalue-modulated signal have been conducted to enhance the receiver sensitivity. However, in the case of a presence of a carrier frequency offset (CFO) at receiver, the effects of the CFO on ANN receiver of eigenvalue-modulated signal is yet to be reported. In this study, we numerically and experimentally investigated the generalization performances of eigenvalue domain ANN-based demodulator on CFO. Furthermore, we propose to combine an ANN-based demodulator with a CFO compensation method based on IST and a relation between frequency and eigenvalue shifts. The proposed method, based on an appropriate soliton pulse, achieves a high CFO estimation accuracy of submegahertz order even if the CFO reaches ±\pm2.5 GHz under the noiseless condition. In the presence of noise and a large CFO of 2.5 GHz, the method attains a CFO estimation accuracy below 60 MHz for OSNR = 10 dB with a low pilot pulse rate, such as 0.064%. We show the simulation results obtained after applying the proposed CFO compensation to the ANN demodulator, which is valid for 2.5 GHz CFO and long-haul transmission over 5000 km. Experiments performed in this study demonstrate successful demodulation of an eigenvalue-modulated signal with OSNR penalty << 1 dB in the presence of CFO within 1 GHz at 2.5 Gb/s.

中文翻译:


结合基于 IST 的 CFO 补偿和基于神经网络的特征值调制信号解调



使用逆散射变换(IST)的基于特征值的通信技术作为光纤通信中的新传输策略而受到关注。近年来,人们对基于人工神经网络(ANN)的特征值调制信号均衡和解调方案进行了一些研究,以提高接收器灵敏度。然而,在接收机处存在载波频率偏移(CFO)的情况下,CFO 对特征值调制信号的 ANN 接收机的影响尚未报告。在本研究中,我们通过数值和实验研究了基于特征值域 ANN 的解调器在 CFO 上的泛化性能。此外,我们建议将基于 ANN 的解调器与基于 IST 以及频率和特征值偏移之间的关系的 CFO 补偿方法相结合。所提出的方法基于适当的孤子脉冲,即使在无噪声条件下CFO达到±μm2.5 GHz,也能实现亚兆赫兹级的高CFO估计精度。在存在噪声和 2.5 GHz 的大 CFO 的情况下,该方法在 OSNR = 10 dB 和低导频脉冲率(例如 0.064%)的情况下获得低于 60 MHz 的 CFO 估计精度。我们展示了将所提出的 CFO 补偿应用于 ANN 解调器后获得的仿真结果,该结果对于 2.5 GHz CFO 和超过 5000 km 的长距离传输有效。本研究中进行的实验表明,在存在 CFO 的情况下,在 1 GHz、2.5 Gb/s 范围内成功解调特征值调制信号,OSNR 损失为 << 1 dB。
更新日期:2021-09-22
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