Saved in:
Bibliographic Details
Main Authors: Tang, Du, Jiang, Yingjie, Luo, Ji, Chen, Yu, Zheng, Bofang, Qiao, Yaojun
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2503.20323
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866913759654576128
author Tang, Du
Jiang, Yingjie
Luo, Ji
Chen, Yu
Zheng, Bofang
Qiao, Yaojun
author_facet Tang, Du
Jiang, Yingjie
Luo, Ji
Chen, Yu
Zheng, Bofang
Qiao, Yaojun
contents Utilizing the precise reference waveform regenerated by post-forward error correction (FEC) data, the fiber-longitudinal power profile estimation based on the minimum-mean-square-error method (MMSE-PPE) has been validated as an effective tool for absolute power monitoring. However, when post-FEC data is unavailable, it becomes necessary to rely on pre-FEC hard-decision data, which inevitably introduces hard-decision errors. These hard-decision errors will result in a power offset that undermines the accuracy of absolute power monitoring. In this paper, we present the first analytical expression for power offset in MMSE-PPE when using pre-FEC hard-decision data, achieved by introducing a virtual hard-decision nonlinear perturbation term. Based on this analytical expression, we also establish the first nonlinear relationship between the power offset and the symbol error rate (SER) of M-ary quadrature amplitude modulation (M-QAM) formats based on Gaussian assumptions. Verified in a numerical 130-GBaud single-wavelength coherent optical fiber transmission system, the correctness of the analytical expression of power offset has been confirmed with 4-QAM, 16-QAM, and 64-QAM formats under different SER situations. Furthermore, the nonlinear relationship between the power offset and SER of $M$-QAM formats has also been thoroughly validated under both linear scale (measured in mW) and logarithmic scale (measured in dB). These theoretical insights offer significant contributions to the design of potential power offset mitigation strategies in MMSE-PPE, thereby enhancing its real-time application.
format Preprint
id arxiv_https___arxiv_org_abs_2503_20323
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Derivation and analysis of power offset in fiber-longitudinal power profile estimation using pre-FEC hard-decision data
Tang, Du
Jiang, Yingjie
Luo, Ji
Chen, Yu
Zheng, Bofang
Qiao, Yaojun
Signal Processing
Utilizing the precise reference waveform regenerated by post-forward error correction (FEC) data, the fiber-longitudinal power profile estimation based on the minimum-mean-square-error method (MMSE-PPE) has been validated as an effective tool for absolute power monitoring. However, when post-FEC data is unavailable, it becomes necessary to rely on pre-FEC hard-decision data, which inevitably introduces hard-decision errors. These hard-decision errors will result in a power offset that undermines the accuracy of absolute power monitoring. In this paper, we present the first analytical expression for power offset in MMSE-PPE when using pre-FEC hard-decision data, achieved by introducing a virtual hard-decision nonlinear perturbation term. Based on this analytical expression, we also establish the first nonlinear relationship between the power offset and the symbol error rate (SER) of M-ary quadrature amplitude modulation (M-QAM) formats based on Gaussian assumptions. Verified in a numerical 130-GBaud single-wavelength coherent optical fiber transmission system, the correctness of the analytical expression of power offset has been confirmed with 4-QAM, 16-QAM, and 64-QAM formats under different SER situations. Furthermore, the nonlinear relationship between the power offset and SER of $M$-QAM formats has also been thoroughly validated under both linear scale (measured in mW) and logarithmic scale (measured in dB). These theoretical insights offer significant contributions to the design of potential power offset mitigation strategies in MMSE-PPE, thereby enhancing its real-time application.
title Derivation and analysis of power offset in fiber-longitudinal power profile estimation using pre-FEC hard-decision data
topic Signal Processing
url https://arxiv.org/abs/2503.20323