Inter-Channel Interference Characterization in a Nyquist-WDM gridless scenario with Nonlinear Impairments Compensation by using Digital Backpropagation

Serna, Juan Pablo; Torres, Jorge López; Cárdenas, Álvaro E. Márquez; González, Neil Guerrero

doi:10.1364/laop.2016.ltu2c.4

Cited by 2 publications

(3 citation statements)

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“…However, EON requires higher system costs and is more difficult to realize large-scale networks. This challenge becomes more pronounced with varying signal transmission speeds, dynamic connection demands, and the intensifying competition for spectrum resources [3]. To better adapt to the needs of diversified services, a variable-bandwidth gridless optical network (V-GON) is proposed, which adopts Nyquist WDM technology, dynamically adjusts the modulation format and bandwidth realizes the flexible allocation of spectral resources, and improves the bandwidth utilization.…”

Section: Introductionmentioning

confidence: 99%

“…Martins, et al investigated gridless spectrum allocation in WDM optical networks and showed that gridless transmission systems reduce spectrum consumption while providing acceptable QoT [1]. Martí nez et al evaluated the impact of interchannel interference in a Nyquist-WDM-based gridless scheme and showed that backpropagation reduces power penalties, but overlap effects lead to higher BER penalties [3]. Amar et al investigated traffic prediction in gridless networks to solve the problem of spectrum fragmentation [2].…”

Section: Introductionmentioning

confidence: 99%

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Deep reinforcement learning-based routing and spectrum allocation for variable-bandwidth gridless optical networks

Huaizhao,

Ju,

Yang

et al. 2024

Advanced Fiber Laser Conference (AFL2023)

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With the diversified development for network service in terms of quality of service, bandwidth, and noise tolerance, variable-bandwidth gridless optical networks (V-GON) have become a promising technology for future networking. Unlike traditional elastic optical networks, which use orthogonal frequency division multiplexing for flexible allocation of subcarriers, V-GON adopts wave division multiplexing with variable modulation format and adjustable bandwidth, which can provide a more convenient way of data transmission. One of the key issues for V-GON is routing and spectrum allocation (RSA) due to the complexity of multi-channels. With complex modulation formats and different center wavelengths, an RSA algorithm needs to assign center frequencies, bandwidths, and modulation formats for each connection and also needs to consider the noise tolerance of the path. In this paper, we focus on optimizing routing, modulation format, and spectrum allocation by deep reinforcement learning to meet the demands of noise tolerance at different speeds. We proposed a reinforcement learning model to realize the availability forecast. The model can predict the feasibility of a pre-allocated optical spectrum. We conduct a numerical simulation to validate the performance. The results show that the proposed Graph Neural Network-Optical Path Availability Prediction algorithm can improve network efficiency, and utilization of spectral resources, and reduce the blocking ratio, which can support dynamic connectivity and interference reduction. In NSFNET network topology our proposed GNN-OPAP algorithm model reduces the loss by 95.88% compared to the DNN model and 64.23% compared to the LSTM model. In 4*mesh network topology, our proposed GNN-OPAP algorithm model reduces the loss by 16.14% compared to the DNN model and 76.33% to the LSTM model. This research provides new insights into the RSA problems in V-GON and provides a powerful reference for designing and optimizing future optical communication networks.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deep reinforcement learning-based routing and spectrum allocation for variable-bandwidth gridless optical networks

Huaizhao,

Ju,

Yang

et al. 2024

Advanced Fiber Laser Conference (AFL2023)

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“…In this work, we analyze and characterize ici in a gridless Nyquist-wdm system with coherent detection, modeled in VPItransmissionMaker™ software, compensating dispersion and nonlinearities with asymmetrical digital backpropagation (dbp). This manuscript is an extension of the conference paper [20] that adds an extensive analysis of nonlinear impact, including new scenarios with 16qam modulation format, dual polarization and at 32 Gbaud. We evaluate the ici effects in terms of ber as functions of optical system parameters such as frequency channel spacing, roll-off factor of the digital Nyquist filter, launch power and laser linewidth.…”

Section: Introductionmentioning

confidence: 99%

Impact of InterChannel Interference in gridless nyquist-wdm systems with and without nonlinear impairments compensation

Torres

Martinez

Fernández

et al. 2019

Cien.Ing.Neogranadina

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This paper presents a characterization of interchannel interference (ICI) effects in gridless Nyquist-wdm systems due to two contributions, namely, overlapping among optical carriers and stimulation of nonlinear optical fiber impairments. ICI is assessed regarding bit error rate (BER) at 16 and 32 Gbaud, as a function of several system parameters. Nonlinear impairment compensation based on the digital back-propagation algorithm is implemented in the DSP-based coherent receiver. Results demonstrated that ICI due to channels overlapped has a higher impact concerning BER than nonlinear optical fiber impairments. Besides, the use of the back-propagation algorithm improves system performance, reducing up to 3 and 0.7 orders of magnitude of BER in QPSK and 16QAM cases, respectively. It means that this algorithm can minimize nonlinear effects under varying system parameters, but its performance is limited in sub-Nyquist cases.

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Inter-Channel Interference Characterization in a Nyquist-WDM gridless scenario with Nonlinear Impairments Compensation by using Digital Backpropagation

Cited by 2 publications

References 0 publications

Deep reinforcement learning-based routing and spectrum allocation for variable-bandwidth gridless optical networks

Deep reinforcement learning-based routing and spectrum allocation for variable-bandwidth gridless optical networks

Impact of InterChannel Interference in gridless nyquist-wdm systems with and without nonlinear impairments compensation

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