Paper
24 November 2023 Modulation format identification based on the mean-shift algorithm
Yufan Hao, Qi Zhang, Qihan Zhao, Xiangjun Xin, Feng Tian, Qinghua Tian, Fu Wang, Yongjun Wang, Leijing Yang
Author Affiliations +
Proceedings Volume 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023); 129351X (2023) https://doi.org/10.1117/12.3007340
Event: Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 2023, Xi’an, China
Abstract
With the rapid development of global communications and exponential growth of network traffic, the flexibility and dynamism of the modulation format and the transmission rate have become important characteristics of the development of the next generation of optical networks. The optical network must be capable of dynamically transferring signals of different modulation formats and data rates to satisfy the requirements of flexible and high-capacity optical network transmission. In this work, we propose a modulation format identification method based on the mean-shift cluster algorithm to implement the reception of different modulation format signals in high-speed optical communication adaptively. The proposed MFI is a spatial cluster method based on density distribution, which can automatically extract the cluster number and density information of samples by estimating the density distribution of samples in the space. In this paper, we construct a 10 GBaud coherent optical simulation system, transmitting QPSK, 8QAM, 16QAM, 32QAM, and 64QAM, to verify the feasibility of this method. The transmission fiber length of the simulation system is set to 80 km. In the case of considering the CD dispersion parameter to 16 ps/(nm·km) and the linewidth is 100 kHz, the simulation results show that the proposed MFI method can achieve 100% identification accuracy when the OSNR values are lower than the 7% FEC limit corresponding to the lowest required OSNR values for five commonly used modulation formats (MFs). Among them, when the OSNR values of 16QAM and 32QAM signals respectively are 17 dB and 21 dB, the identification rate reaches 100%, which can effectively complete the high-precision classification of different modulation formats.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yufan Hao, Qi Zhang, Qihan Zhao, Xiangjun Xin, Feng Tian, Qinghua Tian, Fu Wang, Yongjun Wang, and Leijing Yang "Modulation format identification based on the mean-shift algorithm", Proc. SPIE 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 129351X (24 November 2023); https://doi.org/10.1117/12.3007340
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KEYWORDS
Modulation

Optical transmission

Optical communications

Data transmission

Optical networks

Telecommunications

Optical amplifiers

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