Joint Symbol Rate-Modulation Format Identification and OSNR Estimation Using Random Forest Based Ensemble Learning for Intermediate Nodes

被引：12

作者：

Chai, Jia ^{[1
]}

Chen, Xue ^{[1
]}

Zhao, Yan ^{[2
]}

Yang, Tao ^{[1
]}

Wang, Danshi ^{[1
]}

Shi, Sheping ^{[2
]}

机构：

[1] Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China

[2] ZTE Corp, Beijing 100191, Peoples R China

来源：

IEEE PHOTONICS JOURNAL | 2021年 / 13卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Symbol rate and modulation format identification; OSNR estimation; random forest; intermediate nodes; low bandwidth; SYSTEMS;

D O I：

10.1109/JPHOT.2021.3117984

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a novel joint symbol rate-modulation format identification (SR-MFI) and optical signal-to-noise ratio (OSNR) estimation scheme using the low-bandwidth coherent detecting and random forest (RF)-based ensemble learning is proposed for intermediate nodes in the flexible dense wavelength division multiplexing (F-DWDM) networks. By leveraging low-bandwidth coherent detecting with small bulk wavelength scanning, no chromatic dispersion compensation and low-complexity RF, the proposed scheme could serve as a reduced-complexity and cost-effective option to realize joint SR-MFI and OSNR estimation at intermediate nodes in F-DWDM networks. To verify the feasibility of the proposed scheme, the comprehensive simulations of 8/16 GBaud polarization division multiplexing (PDM)-4/16/32/64 quadrature amplitude modulation (QAM) systems are conducted. The simulation results show that the identification accuracy of SR-MFI reaches 100% and the mean absolute error of OSNR estimation is within 1 dB. Moreover, the proposedmonitoring scheme is verified by 8/16 GBaud PDM-4/16/32QAM coherent transmission experiments.

引用

页数：6

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