Mode Pilot-Tone (MPT)-based High-precision Crosstalk Monitoring for Mode-Division Multiplexing Systems

Abstract

Efficient and precise monitoring on mode-coupling-induced crosstalk (XT) is crucial for the operation of mode-division multiplexing (MDM) systems, particularly for optimizing digital signal processing (DSP) parameter configurations and maintaining stable transmission performance. In this paper, we propose a mode pilot-tone (MPT) monitoring scheme and investigate its performance for XT (MPT-XT) monitoring in a three-mode MDM transmission system. By deploying a photodiode (PD) with a 1 GHz bandwidth for each mode to extract the MPT responses, the complete XT information from 21 GBaud 16-QAM signals is obtained by the proposed scheme. In the experiment, the root-mean-square-error (RMSE) for XT-prediction achieves 0.11 dB, with a coefficient of determination R2 of 0.9992 across the OSNR range from 15dB to 25dB. By applying the transfer learning-based crosstalk neural network (TL-XT-NN) scheme, which transfers the NN model trained exclusively with simulation data to experimental XT monitoring scenarios, the training overhead required by the NN is reduced more than 48.3%. Moreover, we further evaluate the monitoring performance of the proposed scheme on the multiplexing density, the chromatic dispersion (CD), the differential mode group delay (DMGD), and the mode differential loss (MDL). Simulation results confirm its exceptional and consistent performance across all conditions. Finally, we investigate the impact of MPT modulation on the compensation behavior of multi-input multi-output (MIMO) equalizer and propose an inverse mapping label erasure (IMLE) scheme to mitigate the resulting signal degradation. Through the MPT erasure procedure, the error vector magnitude (EVM) penalty of transmitted signals caused by MPT operation is reduced from 2.92% to 0.19%.

Publication DOI: https://doi.org/10.1109/JLT.2025.3550498
Divisions: College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
Funding Information: This work was supported in part by the Sichuan Science and Technology Program (2024YFHZ0319), National Key R&D Program of China (2018YFB1801001), and Royal Society International Exchange Grant (IEC\NSFC\211244).
Additional Information: Copyright © 2025, IEEE. All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Monitoring,Feature extraction,Optical attenuators,Optical noise,Optical fibers,Training,Crosstalk,Optical signal processing,Optical polarization,Modulation
Publication ISSN: 1558-2213
Last Modified: 31 Mar 2025 16:01
Date Deposited: 20 Mar 2025 18:06
Full Text Link:
Related URLs: https://ieeexpl ... ument/10924400/ (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2025-03-12
Published Online Date: 2025-03-12
Accepted Date: 2025-03-01
Authors: Zhao, Tianfeng
Wen, Feng
Feng, Bianxia
Wei, Jinlong
Liang, Junpeng
Tan, Mingming (ORCID Profile 0000-0002-0822-8160)
Wu, Baojian
Xu, Bo
Qiu, Kun

Download

[img]

Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 12 March 2026.

License: ["licenses_description_unspecified" not defined]


Export / Share Citation


Statistics

Additional statistics for this record