Autonomous and energy efficient lightpath operation based on digital subcarrier multiplexing
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hdl:2117/345377
Document typeArticle
Defense date2021-09
Rights accessOpen Access
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ProjectREAL-NET - REAL-time monitoring and mitigation of nonlinear effects in optical NETworks (EC-H2020-813144)
COGNITIVE 5G APPLICATION-AWARE OPTICAL METRO NETWORKS INTEGRATING MONITORING, DATA ANALYTICS AND OPTIMIZATION (AEI-TEC2017-90097-R)
COGNITIVE 5G APPLICATION-AWARE OPTICAL METRO NETWORKS INTEGRATING MONITORING, DATA ANALYTICS AND OPTIMIZATION (AEI-TEC2017-90097-R)
Abstract
The massive deployment of 5G and beyond will require high capacity and low latency connectivity services, so network operators will have either to overprovision capacity in their transport networks or to upgrade the optical network controllers to make decisions nearly in real time; both solutions entail high capital and operational expenditures. A different approach could be to move the decision making toward the nodes and subsystems, so they can adapt dynamically the capacity to the actual needs and thus reduce operational costs in terms of energy consumption. To achieve this, several technological challenges need to be addressed. In this paper, we focus on the autonomous operation of Digital Subcarrier Multiplexing (DSCM) systems, which enable the transmission of multiple and independent subcarriers (SC). Herein, we present several solutions enabling the autonomous DSCM operation, including: i) SC quality of transmission estimation; ii) autonomous SC operation at the transmitter side and blind SC configuration recognition at the receiver side; and iii) intent-based capacity management implemented through Reinforcement Learning. We provide useful guidelines for the application of autonomous SC management supported by the extensive results presented.
CitationVelasco, L. [et al.]. Autonomous and energy efficient lightpath operation based on digital subcarrier multiplexing. "IEEE journal on selected areas in communications", Setembre 2021, vol. 39, núm. 9, p. 2864-2877.
ISSN0733-8716
Publisher versionhttps://ieeexplore.ieee.org/document/9373418
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