发表机构
Karlsruhe Institute of Technology (KIT); Fraunhofer Institute for Integrated Circuits IIS（卡尔斯鲁厄理工学院; 弗劳恩霍夫集成电路研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文系统比较了IM/DD系统中SNN均衡器与解映射器的设计选择，评估其对误码率、脉冲活动和模型大小的影响，揭示了不同设计间的固有权衡。
AI 中文摘要
近年来，人工神经网络（ANNs）已成为解决通信工程中传统方法难以处理的挑战性问题的实际标准。然而，ANNs中采用的密集矩阵乘法往往导致高计算复杂度，进而产生高功耗系统。为克服这些限制，研究人员转向替代计算模型，如脉冲神经网络（SNNs），其承诺实现高能效计算。近期研究表明，基于SNN的均衡器和解映射器在受色散和非线性失真影响的非相干短距离光通信系统中取得了有前景的结果。然而，所提出的方法在设计选择上存在差异，例如决策反馈的纳入、SNN内部循环连接的使用、不同的神经编码以及正则化技术。文献中尚未报道对各种设计选择的系统性比较。本文对强度调制直接检测系统中基于SNN的均衡器和解映射器的设计选择进行了系统性比较，评估了它们对误码率、脉冲活动和模型大小的影响。结果表明，设计和编码选择对这些指标的影响不同，导致固有的权衡。
英文摘要
In recent years, artificial neural networks (ANNs) have emerged as the de facto standard for addressing challenging problems in communications engineering that are difficult to solve using traditional methods. However, the dense matrix multiplications employed in ANNs often result in high computational complexity and, consequently, power-hungry systems. To overcome these limitations, researchers are turning to alternative computational models, such as spiking neural networks (SNNs), which promise highly energy-efficient computation. Recent works have shown that SNN-based equalizers and demappers achieve promising results in non-coherent short-reach optical communication systems affected by chromatic dispersion and nonlinear distortion. However, the proposed approaches differ in several design choices, such as the incorporation of decision feedback, the use of recurrent connections inside the SNN, different neural encodings, and regularization techniques. A systematic comparison of the various design choices has not yet been reported in the literature. This article presents a systematic comparison of design choices for SNN-based equalizers and demappers in intensity modulation with direct detection systems, evaluating their impact on bit error rate, spike activity, and model size. The results reveal that design and encoding choices affect these metrics differently, leading to inherent trade-offs.
CommentsAccepted for publication in Journal of Lightwave Technology
