Least-squares longitudinal power profile estimation based on pilot symbols and training sequences in DSP frames

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Authors: Du Tang, Yingjie Jiang, Hao Ming Zhou, Fan Yang, Yutao Zhou, Baoxuan Quan, Yaojun Qiao, Hengying Xu, Chenglin Bai, Junjie Xie
Cited by: 1
References: 31

Abstract

Longitudinal power profile estimation (PPE) is an essential forward-sensing technique for optical network monitoring, enabling early detection of abnormal loss and supporting the reliable operation of coherent transmission systems. The conventional least-squares PPE (LS-PPE) method either relies on post-FEC reference symbols, which introduce considerable digital signal processing (DSP) overhead, or employs hard-decision (HD) symbols, which inevitably suffer from a systematic power offset that increases with the pre-FEC bit-error rate (BER). In this paper, we present a comprehensive study of a new, to our knowledge, LS-PPE framework that leverages the pilot symbols (PSs) and training sequence (TS) inherently defined in DSP super-frames. By selectively constructing perturbation matrices from known PS and TS positions while discarding error-prone HD data, the proposed scheme eliminates systematic offset without relying on post-FEC information. Extensive simulations with 130 GBaud signals across multiple modulation formats and transmission distances demonstrate the robustness of the proposed method under diverse system conditions. Experimental validation on an 80 GBaud dual-polarization 16QAM transmission over 250 km standard single-mode fiber confirms estimation accuracy comparable to post-FEC benchmarks and superior robustness over HD-based LS-PPE, highlighting the potential of the PS&TS-based framework for practical deployment.

Fields of Study & Subjects

Advanced Electrical Measurement Techniques Digital Filter Design and Implementation Wireless Signal Modulation Classification

Publication details

Journal / source
Journal of Optical Communications and Networking
Publisher
Optica Publishing Group
Volume
18
Issue
4
Pages
B60–B60
Publication date
17 February 2026
Language
EN