超低复杂度光纤非线性补偿基于梯度驱动的修剪科尔莫戈罗夫-阿诺德网络.
Optics letters
|December 15, 2025
概括
一个新的渐变驱动的修剪的科尔莫戈罗夫-阿诺德网络 (GDP-KAN) 有效地弥补了波长分割多重复合 (WDM) 系统中的光纤非线性. 这种超低复杂度的方法显著提高了传输距离和数据容量.
科学领域:
- 光学通信是指光学通信.
- 在工程领域的人工智能.
背景情况:
- 光纤非线性限制了WDM连贯光学系统的传输距离和数据容量.
- 传统的神经网络等分器存在很高的计算复杂性.
研究的目的:
- 为WDM系统提出一个高效的光纤非线性补偿方法.
- 为了减少计算复杂性,同时保持性能.
主要方法:
- 一个渐变驱动的修剪的科尔摩戈罗夫-阿诺德网络 (GDP-KAN) 使用可学习的spline激活函数.
- 基于网络散散的归因得分的梯度驱动的修剪策略.
- 使用8通道WDM传输在1600公里SSMF上使用64 GBaud PDM16-QAM信号进行实验验证.
主要成果:
- GDP-KAN 实现了超低复杂度 (300 RMPB).
- 在12%的复杂度下以0.63dB Q^2因子增益优于每跨度数字反向传播 (DBP) 的1步.
- 与基于MLP的均衡器相比,RMPB降低了68.75%,而没有性能下降.
结论:
- GDP-KAN为WDM系统中的光纤非线性补偿提供了高效的解决方案.
- 在显著降低计算复杂度的情况下实现卓越的性能.
- 能够提高光通信系统的传输距离和数据容量.
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