Optical Communication Technology, Volume. 49, Issue 3, 108(2025)
Modulation format identification based on Stokes space and Stacking model
[1] [1] PU Z, JIANG L, YAN L, et al. Joint modulation format identification and OSNR monitoring based on Stokes vector distribution features for digital coherent optical receivers[J]. Chinese Optics Letters, 2024, 22(5): 27-33.
[2] [2] WANG M, LIU J, ZHANG J, et al. Modulation format identification based on phase statistics in Stokes space[J]. Optics Communications, 2021, 480: 126481-1-126481-7.
[3] [3] XIANG Q, YANG Y, ZHANG Q, et al. Joint, accurate and robust optical signal to noise ratio and modulation format monitoring scheme using single Stokes-parameter-based artificial neural network[J]. Optics Express, 2021, 29(5): 7276-7287.
[4] [4] XU H, YANG L, YU X, et al. Blind and low-complexity modulation format identification scheme using principal component analysis of Stokes parameters for elastic optical networks [J]. Optics Express, 2020, 28(14): 20249-20263.
[5] [5] LV H, ZHOU X, HUO J, et al. Joint OSNR monitoring and modulation format identification on signal amplitude histo grams using convolutional neural network[J]. Optical Fiber Technology, 2021, 61: 102455-1-102455-6.
[6] [6] LEE I, LEE W. UniQGAN: unified generative adversarial networks for augmented modulation classification[J]. IEEE Communications Letters, 2021, 26(2): 355-358.
[7] [7] LI J, MA J, LIU J, et al. Modulation format identification and OSNR monitoring based on multi-feature fusion network[J]. Photonics, 2023, 10(4): 373-388.
[8] [8] ZHAO R, XU H, BAI C, et al. A modulation format identification scheme based on modified PSO clustering in Stokes space[C]//IEEE. Proceedings of 2020 Asia Communications and Photonics Conference(ACP) and International Conference on Information Photonics and Optical Communications (IPOC). Beijing: IEEE, 2020: 1-3.
[9] [9] ZHANG W, ZHU D, HE Z, et al. Identifying modulation formats through 2D Stokes planes with deep neural networks[J]. Optics Express, 2018, 26 (18): 23507-23517.
[10] [10] GUO Z, LIU B, REN J, et al. Modulation format recognition with transfer learning assisted convolutional neural network using multiple Stokes sectional plane image in multi-core fibers[J]. Optics Express, 2022, 30 (12): 21990-22005.
[11] [11] ZHANG Q, YANG Y, GUO C, et al. Accurate BER estimation scheme based on K-means clustering assisted Gaussian approach for arbitrary modulation format[J]. Journal of Lightwave Technology, 2019, 38(8): 2152-2157.
[12] [12] YI A, YAN L, LIU H, et al. Modulation format identification and OSNR monitoring using density distributions in Stokes axes for digital coherent receivers[J]. Optics Express, 2019, 27(4): 4471-4479.
[13] [13] ARIK S, PFISTER T. Tabnet: attentive interpretable tabular learning[[EB/OL]. https://arxiv.org/abs/1908.07442.
[14] [14] HAO M, HE W, JIANG X, et al. Modulation format identification based on multi-dimensional amplitude features for elastic optical networks[J]. Photonics, 2024, 11(5): 390-404.
[15] [15] SILVERMAN BW. Density estimation for statistics and data analysis[M]. London: Routledge, 2018.
[16] [16] GANAIE M A, HU M, MALIK A K, et al. Ensemble deep learning: a review [J]. Engineering Applications of Artificial Intelligence, 2022, 115: 105151-1-105151-18.
[17] [17] YANG L, XU H, BAI C, et al. Modulation format identification using graph-based 2D Stokes plane analysis for elastic optical network[J]. IEEE Photonics Journal, 2021, 13(1): 1-15.
Get Citation
Copy Citation Text
LIU Yu, LIU Zhansheng. Modulation format identification based on Stokes space and Stacking model[J]. Optical Communication Technology, 2025, 49(3): 108
Category:
Received: Oct. 21, 2024
Accepted: Jun. 27, 2025
Published Online: Jun. 27, 2025
The Author Email: