m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise

Solarte-Sanchez, Miguel; Marquez-Viloria, David; Castro-Ospina, Andrés E.; Reyes-Vera, Erick; Guerrero-Gonzalez, Neil; Botero-Valencia, Juan

doi:10.3390/a17120553

Open AccessArticle

m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise

by

Miguel Solarte-Sanchez

¹

,

David Marquez-Viloria

¹

,

Andrés E. Castro-Ospina

¹

,

Erick Reyes-Vera

¹

,

Neil Guerrero-Gonzalez

²

and

Juan Botero-Valencia

^1,*

¹

Faculty of Engineering, Instituto Tecnológico Metropolitano, Medellín 050013, Colombia

²

Department of Electrical, Electronic and Computer Engineering, Universidad Nacional de Colombia, Manizales 170004, Colombia

^*

Author to whom correspondence should be addressed.

Algorithms 2024, 17(12), 553; https://doi.org/10.3390/a17120553

Submission received: 26 September 2024 / Revised: 16 November 2024 / Accepted: 19 November 2024 / Published: 3 December 2024

(This article belongs to the Section Algorithms for Multidisciplinary Applications)

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Abstract

Optical communication systems face challenges like nonlinear noises, particularly Kerr-induced phase noise, which worsens with higher-order m-QAM formats due to their dense data-symbol sets. Advanced signal processing, including machine learning, is increasingly used to enhance signal integrity during demodulation. This paper explores the application of a spectral clustering algorithm adapted to deal with data streaming to mitigate nonlinear noise in long-haul optical channels dominated by nonlinear phase noise, offering a promising solution to a pressing issue. The spectral clustering algorithm was adapted to handle data streams, enabling potential real-time applications. Additionally, it was combined with a demapping process for m-QAM to resolve labeling inconsistencies when processing windowed data. We demonstrate that the spectral clustering algorithm outperforms the k-means algorithm in the face of nonlinear phase noise in −90, −100, and −110 dBc/Hz scenarios at 1 MHz in a simulated 10 GHz symbol rate channel.

Keywords: spectral clustering; data streaming; optical communications; nonlinear phase noise

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MDPI and ACS Style

Solarte-Sanchez, M.; Marquez-Viloria, D.; Castro-Ospina, A.E.; Reyes-Vera, E.; Guerrero-Gonzalez, N.; Botero-Valencia, J. m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise. Algorithms 2024, 17, 553. https://doi.org/10.3390/a17120553

AMA Style

Solarte-Sanchez M, Marquez-Viloria D, Castro-Ospina AE, Reyes-Vera E, Guerrero-Gonzalez N, Botero-Valencia J. m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise. Algorithms. 2024; 17(12):553. https://doi.org/10.3390/a17120553

Chicago/Turabian Style

Solarte-Sanchez, Miguel, David Marquez-Viloria, Andrés E. Castro-Ospina, Erick Reyes-Vera, Neil Guerrero-Gonzalez, and Juan Botero-Valencia. 2024. "m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise" Algorithms 17, no. 12: 553. https://doi.org/10.3390/a17120553

APA Style

Solarte-Sanchez, M., Marquez-Viloria, D., Castro-Ospina, A. E., Reyes-Vera, E., Guerrero-Gonzalez, N., & Botero-Valencia, J. (2024). m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise. Algorithms, 17(12), 553. https://doi.org/10.3390/a17120553

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m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise

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