Optical Communication Technology, Volume. 48, Issue 3, 64(2024)

Estimation method of OSNR for high-order QAM signals based on lightweight RF algorithm

ZHANG Mingye1... OU Mingyu1, NI Qian2 and ZHU Hongna2 |Show fewer author(s)
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  • 2[in Chinese]
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    References(9)

    [3] [3] TUNZE G B, HUYNH T, LEE J M, et al. Sparsely connected CNN for efficient automatic modulation recognition[J]. IEEE Transactions on Vehicular Technology, 2020, 69(12): 15557-15568.

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    [5] [5] NADEEM F, KHAN, KANG P, et al. Joint OSNR monitoring and modulation format identification in digital coherent receivers using deep neural networks. [J]. Optics Express, 2017, 12(9): 1121-1125.

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    [7] [7] FU S, CHENG Y, ZHANG W, et al. Transfer learning simplified multitask deep neural network for optical performance monitoring[J]. Optics Express, 2020, 28(5): 273-277.

    [8] [8] LIANG Z, TAO M L, WANG L, et al. Automatic modulation recognition based on adaptive attention mechanism and ResNeXt WSL model [J].IEEE Communications Letters, 2021, 25(9): 2953-2957.

    [9] [9] HE P, ZHANG Y, YANG X, et al. Deep learning-based modulation recognition for low signal-to-noise ratio environments[J]. Electronics, 2022,11(23): 1-15.

    [10] [10] FAN X, FANG R, XIE Y, et al. Joint optical performance monitoring and modulation format/bit-rate identification by CNN-based multi-task learning[J]. IEEE Photonics Journal, 2018, 10(5): 1-7.

    [11] [11] CHANG X, LI Z, ZHANG Q, et al. Joint modulation format identification and OSNR monitoring based on LSTM[C]//IEEE. Proceedings of 2022 Asia Communications and Photonics Conference (ACP). Shanghai: IEEE,2022: 639-641.

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    ZHANG Mingye, OU Mingyu, NI Qian, ZHU Hongna. Estimation method of OSNR for high-order QAM signals based on lightweight RF algorithm[J]. Optical Communication Technology, 2024, 48(3): 64

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    Paper Information

    Received: Feb. 29, 2024

    Accepted: --

    Published Online: Aug. 2, 2024

    The Author Email:

    DOI:10.13921/j.cnki.issn1002-5561.2024.03.011

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