Title: Nonlinear Distortion Equalization in Multi-Span Optical Links Via a Feed-Forward Photonic Neural Network Show Chinese title

Title: 通过前馈光子神经网络在多段光纤链路中的非线性失真均衡

Abstract: Linear and nonlinear distortions in optical communication signals are equalized using an integrated feed-forward Photonic Neural Network (PNN). The PNN is based on a linear stage made of an 8-tap Finite Impulse Response (FIR) filter, featuring tunable amplitude and phase weights at each tap, and of a nonlinear stage achieved through the square modulus operation at the end-of-line photodetector. Within an Intensity Modulation/Direct Detection (IMDD) system, the PNN is applied to 2-level Pulse Amplitude Modulated (PAM2) optical signals undergoing multi-span propagation. Each 50 km segment includes fiber transmission, optical power restoration, and optional chromatic dispersion compensation via a Tunable Dispersion Compensator. Positioned at the receiver, the PNN enables fully optical signal processing with minimal latency and power consumption. Experimental validation is conducted using a Silicon-On-Insulator device operating on 10 Gbps signals. It demonstrates chromatic dispersion equalization over distances up to 200 km and self-phase modulation (with dispersion removed) up to 450 km. Simulations explore PNN adaptation for 100 Gbps modulations and its potential for cross-phase modulation equalization. Show Chinese abstract

Abstract: 使用集成前馈光子神经网络（PNN）对光通信信号中的线性和非线性失真进行均衡。 PNN 基于一个由 8 抽头有限脉冲响应（FIR）滤波器组成的线性阶段，每个抽头具有可调的幅度和相位权重，并通过线路末端光电探测器的平方模运算实现非线性阶段。 在强度调制/直接检测（IMDD）系统中，PNN 被应用于经过多段传输的 2 级脉冲幅度调制（PAM2）光信号。 每个 50 公里段包括光纤传输、光功率恢复以及通过可调色散补偿器进行的可选色散补偿。 位于接收端，PNN 实现了低延迟和低功耗的全光信号处理。 实验验证使用了一个在 10 Gbps 信号上运行的硅基绝缘体器件。 它展示了在长达 200 公里的距离上的色散均衡以及在去除色散后的自相位调制（450 公里）。 仿真研究了 PNN 在 100 Gbps 调制下的适应性及其在交叉相位调制均衡方面的潜力。