Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 30 September 2024 / Approved: 1 October 2024 / Online: 1 October 2024 (11:55:27 CEST)

How to cite: 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. Preprints 2024, 2024100005. https://doi.org/10.20944/preprints202410.0005.v1 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. Preprints 2024, 2024100005. https://doi.org/10.20944/preprints202410.0005.v1

Abstract

Optical communication systems pose significant challenges, including the effects of nonlinear noises. The nonlinearities, including Kerr-induced phase noise, become more problematic in m-QAM as the orden of the format increases becoming a highly densed set of data-symbols and therefore, requiring advanced signal processing for successful separation of symbols at the demodulation stage. Machine learning techniques have recently been applied to improve signal integrity in such scenarios. 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. 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

Subject

Engineering, Electrical and Electronic Engineering

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.