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Fiber impairments mitigation in OFDM based cognitive optical networks

机译:基于DM的认知光网络中的光纤损伤减轻

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摘要

An adaptive impairments assessment is necessary to evaluate the impact of various linear and nonlinear effects in future generation cognitive optical transport links. In this paper, an Adaptive Fiber Impairment Mitigation (AFIM) algorithm is proposed to identify a suitable mitigation scheme for the cognitive environment. The AFIM algorithm will assess fiber impairments and adaptively select a suitable mitigation scheme with minimum complexity based on the present network conditions and user performance target. The performance of AFIM algorithm is compared with Fixed Fiber Impairment Mitigation approach in terms of outage probability and outage capacity analysis. An Orthogonal Frequency Division Multiplexing based Mode Division Multiplexing system with Few Mode Fiber (FMF) is suggested as a solution to increase the nonlinearity threshold limit of the system. The L_2-by-3 nonlinear transform based Peak to Average Power Ratio reduction technique is implemented to mitigate fiber nonlinear effects in FMF based backbone and backhaul links. The performance analysis of the FMF system has been evaluated and compared with that of Single Mode Fiber system. The proposed analytical model and mitigation schemes are integrated with the AFIM algorithm to realize the cognitive optical network. Further, the result shows that AFIM algorithm enhances the system capacity by more than 6-folds at an outage probability of 0.5 and reduces the outage probability to 0.6 at the capacity range of 20 Gbps.
机译:适应性障碍评估是评估在未来一代的认知光学传输链路中各种线性和非线性效应的影响。本文提出了一种自适应光纤损伤缓解(AFIM)算法,以确定认知环境的合适缓解方案。 AFIM算法将评估光纤损伤,并根据目前的网络条件和用户性能目标自适应地选择具有最小复杂性的合适的缓解方案。在停电概率和中断容量分析方面将AFIM算法的性能与固定光纤减值缓解方法进行比较。具有少量模式光纤(FMF)的基于正交频分复用的模式分割多路复用系统作为提高系统的非线性阈值极限的解决方案。基于L_2-BY-3非线性变换的峰值到平均功率比减少技术,以减轻基于FMF的骨干和回程链路中的光纤非线性效应。已经评估了FMF系统的性能分析,并与单模光纤系统进行了评估。所提出的分析模型和缓解方案与AFIM算法集成在一起实现认知光网络。此外,结果表明,AFIM算法在0.5的停电概率下通过6倍提高系统容量,并将停电概率降低到0.6的容量范围为20 Gbps。

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