A Blind Nonlinearity Compensator Using DBSCAN Clustering for Coherent Optical Transmission Systems Article Swipe
Elias Giacoumidis
,
Yi Lin
,
Mutsam A. Jarajreh
,
Sean O’Dúill
,
Kevin McGuinness
,
Paul F. Whelan
,
Liam P. Barry
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/app9204398
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/app9204398
Coherent fiber-optic communication systems are limited by the Kerr-induced nonlinearity. Benchmark optical and digital nonlinearity compensation techniques are typically complex and tackle deterministic-induced nonlinearities. However, these techniques ignore the impact of stochastic nonlinear distortions in the network, such as the interaction of fiber nonlinearity with amplified spontaneous emission from optical amplification. Unsupervised machine learning clustering (e.g., K-means) has recently been proposed as a practical approach to the blind compensation of stochastic and deterministic nonlinear distortions. In this work, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is employed, for the first time, for blind nonlinearity compensation. DBSCAN is tested experimentally in a 40 Gb/s 16 quadrature amplitude-modulated system at 50 km of standard single-mode fiber transmission. It is shown that at high launched optical powers, DBSCAN can offer up to 0.83 and 8.84 dB enhancement in Q-factor when compared to conventional K-means clustering and linear equalisation, respectively.
Related Topics
Concepts
DBSCAN
Nonlinear system
Cluster analysis
Computer science
Compensation (psychology)
Benchmark (surveying)
Transmission (telecommunications)
Noise (video)
Artificial intelligence
Algorithm
Physics
Telecommunications
Image (mathematics)
Fuzzy clustering
Psychoanalysis
Canopy clustering algorithm
Geodesy
Psychology
Geography
Quantum mechanics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app9204398
- https://www.mdpi.com/2076-3417/9/20/4398/pdf?version=1571310263
- OA Status
- gold
- Cited By
- 23
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2971457893
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2971457893Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app9204398Digital Object Identifier
- Title
-
A Blind Nonlinearity Compensator Using DBSCAN Clustering for Coherent Optical Transmission SystemsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-10-17Full publication date if available
- Authors
-
Elias Giacoumidis, Yi Lin, Mutsam A. Jarajreh, Sean O’Dúill, Kevin McGuinness, Paul F. Whelan, Liam P. BarryList of authors in order
- Landing page
-
https://doi.org/10.3390/app9204398Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/9/20/4398/pdf?version=1571310263Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/2076-3417/9/20/4398/pdf?version=1571310263Direct OA link when available
- Concepts
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DBSCAN, Nonlinear system, Cluster analysis, Computer science, Compensation (psychology), Benchmark (surveying), Transmission (telecommunications), Noise (video), Artificial intelligence, Algorithm, Physics, Telecommunications, Image (mathematics), Fuzzy clustering, Psychoanalysis, Canopy clustering algorithm, Geodesy, Psychology, Geography, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
23Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 1, 2023: 3, 2022: 4, 2021: 8Per-year citation counts (last 5 years)
- References (count)
-
26Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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