Equalization-Enhanced Phase Noise: Modeling and DSP-aware Analysis
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915201806237696 |
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| author | Jung, Sebastian Janz, Tim Aref, Vahid Brink, Stephan ten |
| author_facet | Jung, Sebastian Janz, Tim Aref, Vahid Brink, Stephan ten |
| contents | In coherent optical communication systems the laser phase noise is commonly modeled as a Wiener process. We propose a sliding-window based linearization of the phase noise, enabling a novel description. We show that, by stochastically modeling the residual error introduced by this approximation, equalization-enhanced phase noise (EEPN) can be described and decomposed into four different components. Furthermore, we analyze the four components separately and provide a stochastical model for each of them. This novel model allows to predict the impact of well-known algorithms in coherent digital signal processing (DSP) pipelines such as timing recovery (TR) and carrier phase recovery (CPR) on each of the terms. Thus, it enables to approximate the resulting signal affected by EEPN after each of these DSP steps and helps to derive appropriate ways of mitigating such effects. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_13199 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Equalization-Enhanced Phase Noise: Modeling and DSP-aware Analysis Jung, Sebastian Janz, Tim Aref, Vahid Brink, Stephan ten Signal Processing In coherent optical communication systems the laser phase noise is commonly modeled as a Wiener process. We propose a sliding-window based linearization of the phase noise, enabling a novel description. We show that, by stochastically modeling the residual error introduced by this approximation, equalization-enhanced phase noise (EEPN) can be described and decomposed into four different components. Furthermore, we analyze the four components separately and provide a stochastical model for each of them. This novel model allows to predict the impact of well-known algorithms in coherent digital signal processing (DSP) pipelines such as timing recovery (TR) and carrier phase recovery (CPR) on each of the terms. Thus, it enables to approximate the resulting signal affected by EEPN after each of these DSP steps and helps to derive appropriate ways of mitigating such effects. |
| title | Equalization-Enhanced Phase Noise: Modeling and DSP-aware Analysis |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2503.13199 |