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Multi-band transmission is a promising solution for capacity enhancement in optical networks. We propose a novel strategy, named C to C+L Upgrade (CLU), to gradually upgrade links from C to C+L bands. We develop a Recurrent Neural Network (RNN)-based model to efficiently predict links for upgrade, based on network state and resource utilization, to reduce blocking and upgrade cost. Our results show that CLU outperforms baseline strategies (which do not employ predictive decisions) by upgrading fewer links at appropriate times.
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C+L-band upgrade strategies to sustain traffic growth in optical backbone networks
We investigate cost-efficient upgrade strategies for capacity enhancement in optical backbone networks enabled by C+L-band optical line systems. A multi-period strategy for upgrading network links from the C band to the C+L band is proposed, ensuring physical-layer awareness, cost effectiveness, and less than 0.1% blocking. Results indicate that the performance of an upgrade strategy depends on efficient selection of the sequence of links to be upgraded and on the time instant to upgrade, which are either topology or traffic dependent. Given a network topology, a set of traffic demands, and growth projections, our illustrative numerical results show that a well-devised upgrade strategy can achieve superior cost efficiency during the capacity upgrade to C+L enhancement.
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- Award ID(s):
- 1716945
- PAR ID:
- 10251930
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Journal of Optical Communications and Networking
- Volume:
- 13
- Issue:
- 7
- ISSN:
- 1943-0620; JOCNBB
- Format(s):
- Medium: X Size: Article No. 193
- Size(s):
- Article No. 193
- Sponsoring Org:
- National Science Foundation
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