Acta Optica Sinica, Volume. 44, Issue 12, 1201001(2024)

Communication Performance of Underwater Wireless Optical Deep Autoencoder

Dan Chen*, Rui Wang, Feier Ai, and Linhai Tang
Author Affiliations
  • School of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, Shaanxi, China
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    Figures & Tables(13)
    Underwater autoencoder with deep neural network
    Adaptive transmission of UWOC autoencoder based on DL
    Comparison of BER between the autoencoder one-hot vector transmission and the traditional MPSK modulation system
    Loss of network training for the autoencoder under different marine environments and SNRs. (a) Clear ocean water; (b) costal ocean water
    BER performance of the autoencoder using adaptive transmission under different marine environments and SNRs. (a) Clear ocean water; (b) costal ocean water
    Adaptive selection of the optimal vector dimension Mopt under different marine environments and SNRs. (a) Clear ocean water; (b) costal ocean water
    Data rate performance of adaptive transmission with autoencoder under different marine environments and SNRs. (a) Clear ocean water; (b) costal ocean water
    Loss of network training for the autoencoder under different waters and turbulence intensity. (a) Clear ocean water; (b) costal ocean water
    BER performance of the autoencoder using adaptive transmission under different marine environments and turbulence intensity. (a) Clear ocean water; (b) costal ocean water
    Adaptive selection of the optimal vector dimension Mopt under different marine environments and turbulence intensities. (a) Clear ocean water; (b) costal ocean water
    Data rate performance of the autoencoder using adaptive transmission under different marine environments and training turbulence intensity. (a) Clear ocean water; (b) costal ocean water
    • Table 1. Absorption, scattering, and attenuation coefficients under different types of waters[18-20]

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      Table 1. Absorption, scattering, and attenuation coefficients under different types of waters[18-20]

      Water typea(λ) /m-1b(λ) /m-1c(λ) /m-1
      Pure sea water0.0530.0030.056
      Clear ocean water0.1140.0370.151
      Costal ocean water0.1790.2190.398
      Turbid harbor water0.2951.8752.170
    • Table 2. Parameter settings for the autoencoder in different marine environments

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      Table 2. Parameter settings for the autoencoder in different marine environments

      Water typeLink distance L /mAbsorptioncoefficient a /m-1Scatteringcoefficient b /m-1MSE thresholdEMS,thTrained sample numberTest samplenumberEpochBatchsize
      Clear ocean water150.1140.03710-61×1051×10620032
      Costal ocean water150.1790.21910-61×1051×10620032
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    Dan Chen, Rui Wang, Feier Ai, Linhai Tang. Communication Performance of Underwater Wireless Optical Deep Autoencoder[J]. Acta Optica Sinica, 2024, 44(12): 1201001

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Jun. 26, 2023

    Accepted: Aug. 22, 2023

    Published Online: Jun. 13, 2024

    The Author Email: Chen Dan (chdh@xaut.edu.cn)

    DOI:10.3788/AOS231188

    CSTR:32393.14.AOS231188

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