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Design of a Maritime Autoencoder Communication System Based on Attention Mechanisms and DenseBlock

College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
College of Information Engineering, Zhejiang University of Technology, Hangzhou 310014, China
State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau 999078, China
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Abstract

As the maritime industry continues to thrive and maritime services diversify, the demand for highly reliable maritime communication systems has become increasingly prominent. However, harsh marine conditions pose significant challenges to communication systems. In this work, we propose a Maritime AutoEncoder (MAE) communication system based on Attention Mechanisms (AMs) and DenseBlock (namely AM-Dense-MAE). AM-Dense-MAE utilizes DenseBlock and long short-term memory to extract deep features and capture spatio-temporal relationships, addressing the issue of “long-term dependency”. Furthermore, the decoder incorporates spatial attention modules and convolutional block attention module to enhance the preservation of crucial information and suppress irrelevant data. We employ the Rician fading channel model to simulate maritime communication channels. A substantial volume of data is utilized for model training and parameter optimization. Simulation results demonstrate that, in comparison to the benchmarks, the proposed AM-Dense-MAE exhibits better block error rate performance under various signal-to-noise ratio conditions and showcases generalization capabilities across diverse parameter settings.

Keywords

maritime communication systemautoencoderDenseBlockAttention Mechanisms (AMs)

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Tsinghua Science and Technology
Volume 30 Issue 4,
August 2025
Pages 1496-1510
DOI: 10.26599/TST.2023.9010150
Cite this article:
Han X, Lin B, Shao S, et al. Design of a Maritime Autoencoder Communication System Based on Attention Mechanisms and DenseBlock. Tsinghua Science and Technology, 2025, 30(4): 1496-1510. https://doi.org/10.26599/TST.2023.9010150
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