Exponential-Memory-Polynomial-Based Nonlinear Equalizer for C-Band IM/DD Systems

We propose a novel exponential memory polynomial decision-feedback equalizer (EMP-DFE) for nonlinear compensation in intensity modulation and direct detection (IM/DD) systems. Different structures of EMP are investigated and the proposed one achieves the best performance by including both self- and cross-beating terms of all nonlinear orders while balancing the complexity. Experiments of a 96-112Gbit/s PAM-4 system over 10-30km single-mode fiber show that the proposed EMP-DFE outperforms diagonally-pruned Volterra DFE, diagonally-pruned absolute-term Volterra DFE and trigonometric memory polynomial DFE in terms of both ultimate performance and the performance at the same complexity.

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Publication Details

Journal
IEEE Photonics Technology Letters
Published
2024-09-16
DOI
https://doi.org/10.1109/lpt.2024.3461752
Citations
1
Primary Topic
Advanced Data Compression Techniques
Type
article
Field-Weighted Citation Impact
0.25

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article

Exponential-Memory-Polynomial-Based Nonlinear Equalizer for C-Band IM/DD Systems

Jian Zhao, Yi Cai, Chengju Hu, Xing Liu
1 citations
IEEE Photonics Technology Letters
Advanced Data Compression Techniques
0.25
article

Exponential-Memory-Polynomial-Based Nonlinear Equalizer for C-Band IM/DD Systems

Jian Zhao, Yi Cai, Chengju Hu, Xing Liu
article en
1 citations

Abstract

We propose a novel exponential memory polynomial decision-feedback equalizer (EMP-DFE) for nonlinear compensation in intensity modulation and direct detection (IM/DD) systems. Different structures of EMP are investigated and the proposed one achieves the best performance by including both self- and cross-beating terms of all nonlinear orders while balancing the complexity. Experiments of a 96-112Gbit/s PAM-4 system over 10-30km single-mode fiber show that the proposed EMP-DFE outperforms diagonally-pruned Volterra DFE, diagonally-pruned absolute-term Volterra DFE and trigonometric memory polynomial DFE in terms of both ultimate performance and the performance at the same complexity.

IEEE Photonics Technology LettersVol. 36(21)
Soochow University (CN), South China University of Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong Province
Affordable and clean energy
Openalex Percentile: Top 47%
Advanced Data Compression Techniques
0.25
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