A traditional wavelength-division multiplexed (WDM) backbone network with its rigid features is unsuitable for emerging diverse and high bitrate (400 Gb/s, 1 Tb/s) traffic needs. Flexible solutions employ new technologies such as bandwidth-variable optical cross connects (BV-OXC) with liquid crystal (LCoS) wavelength-selective switches (WSS), sliceable bandwidth-variable transponders (SBVT), etc. in a flex-grid network. Flex-grid network operates on variable spectral granularities (e.g., 12.5 GHz), and higher modulation formats (quadrature amplitude modulation). However, a greenfield deployment of flex-grid technologies may not be practical, due to cost of technology and usability. This leads to a brown-field network where both fixed-grid and flex-grid technologies co-exist with seamless interoperability. Thus traditional traffic routing and resource allocation techniques need to evolve in a mixed-grid infrastructure. Our study considers the dynamic routing and spectrum assignment (RSA) problem in a fixed/flex-grid co-existing optical network. It provisions routes for dynamic, heterogeneous traffic, ensuring maximum spectrum utilization and minimum blocking.
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Exploration of Optical Signal QoT Margin with Intelligent WSS Filtering Penalty Estimator Using Neural Network
Deployment of 5G requires increased data trans-mission capacity in the metro fiber network. Besides deploying new dark fiber operators are also looking into solutions that improve fiber spectrum utilization by means of high-order modulation formats, flexible grid, and subcarrier multiplexing (SCM) technologies. An important factor that limits fiber spectrum utilization in metro network is the penalty inflicted on the optical signals that are routed by wavelength selective switches (WSS). In this paper, an intelligent WSS filtering penalty estimator is proposed based on neural network. With the achieved accuracy of 0.34 dB of mean absolute error in estimating the optical signal-to-noise ratio penalties caused by WSS filtering, the trained neural network is applied to estimate the fiber throughput gains that can be obtained by optimally selecting the signal symbol rate in a number of use cases.
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- Award ID(s):
- 1956357
- NSF-PAR ID:
- 10292080
- Date Published:
- Journal Name:
- 2021 International Conference on Optical Network Design and Modeling (ONDM)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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- The DOI is not currently available.
