4.7 Article

Autonomous and Energy Efficient Lightpath Operation Based on Digital Subcarrier Multiplexing

Journal

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Volume 39, Issue 9, Pages 2864-2877

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2021.3064698

Keywords

Transponders; Optical transmitters; Optical fiber networks; Multiplexing; Phase shift keying; Automation; Optical receivers; Network automation; digital subcarrier multiplexing; energy savings; intent-based networking; reinforcement learning

Funding

  1. European Community's through the Marie Sklodowska-Curie Action (MSCA) REAL-NET Project [G.A. 813144]
  2. Agencia Estatal de Investigacion (AEI)/Fondo Europeo de Desarrollo Regional (FEDER) through the TWINS Project [TEC2017-90097-R]
  3. ICREA Institution

Ask authors/readers for more resources

The massive deployment of 5G and beyond will require high capacity and low latency connectivity services, network operators can reduce operational costs and energy consumption by upgrading optical network controllers or adopting alternative methods.
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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