Autonomous and energy efficient lightpath operation based on digital subcarrier multiplexing
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 en...
| Autores: | , , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/345377 |
| Acceso en línea: | https://hdl.handle.net/2117/345377 https://dx.doi.org/10.1109/JSAC.2021.3064698 |
| Access Level: | acceso abierto |
| Palabra clave: | Multiplexing Decision-making Telecommunication -- Traffic -- Management Network automation Digital subcarrier multiplexing Energy savings Intent-based networking Reinforcement learning Multiplexatge Decisió, Presa de Telecomunicació -- Tràfic -- Gestió Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica |
| Sumario: | 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. |
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