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Accurate Low Complex Modulation Format and Symbol Rate Identification for Autonomous Lightpath Operation.

Diogo Sequeira1, Marc Ruiz1, Nelson Costa2

  • 1Optical Communications Group (GCO), Universitat Politècnica de Catalunya (UPC), 08034 Barcelona, Spain.

Sensors (Basel, Switzerland)
|December 11, 2022
PubMed
Summary

This study introduces a fast, low-complexity algorithm for identifying optical signal configurations, crucial for autonomous network operations in 5G/6G systems. The method accurately identifies modulation format and symbol rate, simplifying network management.

Keywords:
autonomous networkingoptical network operation

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Area of Science:

  • Optical networking
  • Telecommunications engineering
  • Signal processing

Background:

  • Network automation is essential for managing dynamic traffic in 5G/6G applications.
  • Autonomous lightpath operation in optical networks requires receivers to identify signal configurations independently.
  • This simplifies network controller operations, especially in multi-domain scenarios.

Purpose of the Study:

  • To propose a blind and low-complexity algorithm for identifying modulation format (MF) and symbol rate (SR).
  • To enable autonomous optical receiver configuration without network controller intervention.
  • To reduce the burden on network controllers and simplify multi-domain optical network management.

Main Methods:

  • Developed an algorithm based on analyzing the effects of decoding optical signals with various MFs and SRs.
  • Conducted extensive simulations using MATLAB.
  • Modeled a coherent wavelength division multiplexed system with 32 and 64 quadrature amplitude modulated signals up to 96 GBd.

Main Results:

  • Achieved remarkable identification accuracy for modulation format and symbol rate.
  • Demonstrated effectiveness in the presence of both linear and nonlinear noise.
  • Validated performance across a wide range of feasible optical signal configurations.

Conclusions:

  • The proposed algorithm enables autonomous optical signal identification.
  • It offers a low-complexity and highly accurate solution for network automation.
  • This technology is vital for the efficient operation of future high-capacity optical networks.