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Article

Dynamic Spectrum Assignment in Passive Optical Networks Based on Optical Integrated Microring Resonators Using Machine Learning and a Routing, Modulation Level, and Spectrum Assignment Method

by
Andrés F. Calvo-Salcedo
1,*,
Neil Guerrero González
2 and
Jose A. Jaramillo-Villegas
1,3
1
Faculty of Engineering, Universidad Tecnológica de Pereira, Pereira 660003, Colombia
2
Faculty of Engineering, Universidad Nacional de Colombia, Manizales 170002, Colombia
3
Laboratory for Research in Complex Systems, Menlo Park, CA 94104, USA
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(24), 13294; https://doi.org/10.3390/app132413294
Submission received: 4 September 2023 / Revised: 12 October 2023 / Accepted: 17 October 2023 / Published: 15 December 2023
(This article belongs to the Collection Optical Design and Engineering)

Abstract

The rising demand for bandwidth in optical communication networks has led to the need for more efficient solutions for spectrum allocation. This article presents a solution to enhance the capacity and efficiency of passive optical networks (PON) using optical microring resonators and dynamic spectrum allocation. The solution relies on wavelength division multiplexing (WDM). It proposes using a support vector machine (SVM) and a Routing, Modulation Level, and Spectrum Assignment (RMLSA) method to manage spectrum allocation based on the bandwidth and distance of multiple requests. The network employs a pulse shaper to physically allocate the spectrum, allowing for the separation of the spectrum generated by the microring resonators into different wavelengths or wavelength ranges (super-channel). Additionally, the SVM and RMLSA algorithms regulate the pulse shaper to execute the allocation. This photonic network achieves improved spectrum utilization and reduces the network blocking probability. Our proposal shows that we successfully addressed 1090 requests with a zero blocking probability, accounting for 81% of the total requests. These request scenarios can simultaneously accommodate up to 200 requests, with a maximum bandwidth of 31 THz. This highlights the efficacy of our approach in efficiently managing requests with substantial processing capacity.
Keywords: optical communications; passive optical networks; microring resonator; optical frequency comb; spectrum allocation optical communications; passive optical networks; microring resonator; optical frequency comb; spectrum allocation

Share and Cite

MDPI and ACS Style

Calvo-Salcedo, A.F.; González, N.G.; Jaramillo-Villegas, J.A. Dynamic Spectrum Assignment in Passive Optical Networks Based on Optical Integrated Microring Resonators Using Machine Learning and a Routing, Modulation Level, and Spectrum Assignment Method. Appl. Sci. 2023, 13, 13294. https://doi.org/10.3390/app132413294

AMA Style

Calvo-Salcedo AF, González NG, Jaramillo-Villegas JA. Dynamic Spectrum Assignment in Passive Optical Networks Based on Optical Integrated Microring Resonators Using Machine Learning and a Routing, Modulation Level, and Spectrum Assignment Method. Applied Sciences. 2023; 13(24):13294. https://doi.org/10.3390/app132413294

Chicago/Turabian Style

Calvo-Salcedo, Andrés F., Neil Guerrero González, and Jose A. Jaramillo-Villegas. 2023. "Dynamic Spectrum Assignment in Passive Optical Networks Based on Optical Integrated Microring Resonators Using Machine Learning and a Routing, Modulation Level, and Spectrum Assignment Method" Applied Sciences 13, no. 24: 13294. https://doi.org/10.3390/app132413294

APA Style

Calvo-Salcedo, A. F., González, N. G., & Jaramillo-Villegas, J. A. (2023). Dynamic Spectrum Assignment in Passive Optical Networks Based on Optical Integrated Microring Resonators Using Machine Learning and a Routing, Modulation Level, and Spectrum Assignment Method. Applied Sciences, 13(24), 13294. https://doi.org/10.3390/app132413294

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