Rong Limin, Ni Weihao, Chen Zhiwei, Li Fan
Opt Lett. 2024 Aug 1;49(15):4138-4141. doi: 10.1364/OL.529539.
A neural network (NN)-based electrical dispersion pre-compensation (pre-EDC) scheme in intensity-modulation and direct-detection (IM/DD) systems is proposed and experimentally demonstrated in this Letter. The scheme enables 56 Gbit/s four-level pulse amplitude modulation (PAM-4) generation at a transmitter over an 80 km single-mode fiber (SMF) transmission in the C-band. The NN is utilized to better fit nonlinear phase-amplitude transformation due to the chromatic dispersion (CD) in IM/DD systems, in place of the existing Gerchberg-Saxton (GS) iterative algorithm and linear GS-based finite impulse response (GS-FIR) non-iterative compensation schemes. The experimental results show that the measured bit error ratio (BER) can be reduced to below the 7% hard-decision forward error correction (HD-FEC) threshold of 3.8 × 10 with 0 dBm receiver optical power (ROP) by the NN-based non-iterative pre-EDC scheme, which also saves up to 81% of computational complexity compared to the GS-based scheme. The results indicate that our proposed scheme is promising for the CD pre-compensation at the transmitter.
本文提出并通过实验验证了一种基于神经网络（NN）的强度调制与直接检测（IM/DD）系统中的电色散预补偿（pre-EDC）方案。该方案能够在发射端实现56 Gbit/s的四电平脉冲幅度调制（PAM-4）信号生成，并通过80 km的C波段单模光纤（SMF）进行传输。利用神经网络来更好地拟合IM/DD系统中由于色散（CD）导致的非线性相位-幅度变换，取代了现有的格尔奇贝格-萨克斯顿（GS）迭代算法和基于线性GS的有限脉冲响应（GS-FIR）非迭代补偿方案。实验结果表明，基于神经网络的非迭代预EDC方案在接收端光功率（ROP）为0 dBm时，可将测量的误码率（BER）降低到低于3.8×10⁻³的7%硬判决前向纠错（HD-FEC）阈值，与基于GS的方案相比，还可节省高达81%的计算复杂度。结果表明，我们提出的方案在发射端进行色散预补偿方面具有很大的潜力。
