【作者】 张博；

【导师】 张茹；

【作者基本信息】 北京邮电大学 ， 电子科学与技术， 2019， 博士

【摘要】 下一代灵活光网络正在朝着大容量、智能化、可编程的方向不断演进,为满足光网络扩容的要求,光纤传输速率不断提高,从单波10G发展到100G,再到如今200G系统已经成熟商用,400G系统开始少量商用。但是随着传输速率的提高,光纤非线性效应对链路产生的损伤日益明显,极大地限制着光网络链路的最大传输距离。另一方面,最大传输距离受限则意味着对中继站点的需求增加,不仅直接导致网络建设成本大幅度增加,还会引入额外的滤波损伤。随着光网络节点的增多,级联ROADM的滤波效应增强,对链路性能的损伤变大,成为限制光网络扩容的难点之一。因此,对下一代灵活光网络中非线性效应和级联ROADM窄带滤波效应引起的非线性损伤进行建模、预测和补偿已成为国内外研究热点,是进一步提高光网络容量的关键技术,也是目前光网络研究的重点和难点。本文针对下一代灵活光网络中非线性噪声对传输距离和网络容量的限制问题,研究了非线性噪声的建模和补偿问题;针对灵活光网络中ROADM节点的增加带来的窄带滤波级联效应,研究了光网络中级联ROADM滤波损伤建模问题,主要研究工作和创新点如下:(1)基于高斯噪声模型提出全场景非线性噪声估计模型和敏捷估计模型本文研究了高斯噪声模型估计误差产生的原因,对SCI、XCI和MCI三种非线性噪声的误差项进行了分析和仿真。提出了适用于全场景的非线性噪声估计模型,去除了高斯噪声模型中的高斯分布假设限制,通过仿真分析验证了模型的准确性;进一步提出了适用于动态变化光网络的全场景非线性噪声敏捷估计模型,将多种光纤参数和光网络ROADM节点处的上下路动态变化考虑在内,并通过仿真分析验证了模型的准确性。(2)基于时域ISI(Inter-symbol interference)模型提出多参数盲均衡非线性补偿方案本文基于非线性噪声时域ISI模型,研究了非线性噪声干扰系数和非线性噪声的时间相关特性。提出了多参数盲均衡非线性补偿方案,通过自适应算法实现抽头系数和算法步长的同时更新,使得该方案能够实现快速收敛和准确建模。通过仿真验证与对比分析,多参数盲均衡非线性补偿方案能够获得较好的补偿增益。(3)基于人工神经网络的ROADM级联滤波损伤预测建模本文基于ROADM等效传输模型,研究了 ROADM节点位置分布和带宽分布对级联ROADM滤波效应的影响,提出了基于人工神经网络的ROADM级联滤波损伤预测模型,利用ROADM级联数目、输入端OSNR、ROADM位置分布和ROADM带宽分布等参数作为输入,对光链路滤波损伤实现了较为准确的估计。更多还原

【Abstract】 The next-generation elastic optical networks(EONs)are evolving towards the desired features including large capacity,intelligence and programmability.To meet the requirement of large capacity,the transmission rate of the single wavelength in optical networks has been continuously improved from 10G to 100G.Now the 200G-system has been widely used commercialy while the 400G-system has been small amount of commercial.However,the impairements induced by the" nonlinear effects are increasingly obvious with the increase of transmission rate,limiting the maximum transmission distance.Therefore,modeling,prediction and mitigation of nonlinear penalties have been the key techniques for the capacity expansion of the next-geneartion EONs.Additionaly,the limited maximum transmission distance means the increasing demand of relay nodes.It not only directly leads to the capital expenditures(CAPEX)for construction of infrastructure,but also introduces additional filtering impairments.Since the relay nodes are mainly based on the reconfigurable of optical add-drop multiplexing(ROADM),the filtering effect is strengthened with node numbers.Consequently,the filtering penalty has been one of the obstacles for upgrading the existing networks to the next-generation EONs.This dissertation focus on two aspects:the first one is modeling and compensation of the nonlinear noise induced by the cross-phase modulation(XPM),and the other is estimating the filtering penalty in elastic optical networks within cascased ROADMs.Several technical schemes are proposed.The main innovations for this dissertation are as follows:Firstly,two kinds of estimation models based on the Gaussian noise(GN)model are proposed,including the full-scenario estimation model and the agile estimation model.The full-scenario estimator removes the assumption that the transmitted signals behaves as Gaussian noise.The agile estimation model takes the add/drop at the ROADM node into consideration.Different form the GN model,the two proposed models can be applied to the dynamic optical networks.Simulations show that both models have good accuracy and can be good tools to help planning the networks.Secondly,the multi-parameter blind equalization based on the time varying ISI model is proposed to mitigate the nonlinear noise in the optical networks.The time varying ISI model shows that the nonlinear noise has time-dependent characteristics and their autocorrelation function have long temporal correlation.Based on this time-dependent feature,the adaptive tap coefficients and step size are used at the same time to update the qualization,enabled to converge faster and predict the filtering penalty with more accurary.Simulations show that the proposed equalization can achieve better mitigation gain compared with RLS filter.Thirdly,focusing on the filtering penalty induced by cascaded ROADMs,an optical filtering penalty estimation using artificial neural networks(ANN)in EONs is proposed.We first investigate the impact of ROADM location distribution and bandwidth allocation on the narrow filtering effect.Afterwords,an approach based on ANN is proposed to estimate the filtering penalty under various link conditions.Extensive simulations with 9600 links are implemented to demonstrate the superior performance of the proposed scheme.更多还原