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Main Authors: Zhang, Wei, Yu, Zhenming, Huang, Hongyu, Dong, Xiangyong, Ma, Yan, Zhao, Yongli, Huang, Shanguo, Xu, Kun
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2509.03835
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author Zhang, Wei
Yu, Zhenming
Huang, Hongyu
Dong, Xiangyong
Ma, Yan
Zhao, Yongli
Huang, Shanguo
Xu, Kun
author_facet Zhang, Wei
Yu, Zhenming
Huang, Hongyu
Dong, Xiangyong
Ma, Yan
Zhao, Yongli
Huang, Shanguo
Xu, Kun
contents Free space optical (FSO) communication is considered a promising solution in next_generation communication networks. However, its performance is significantly influenced by atmospheric turbulence. To enhance system robustness to turbulence, we propose a turbulence_robust end_to_end FSO communication system (TRFSO) that integrates a data-driven channel model with joint source_channel coding modulation (JSCCM). Specifically, a bidirectional long short-term memory (BiLSTM)_based channel model is developed and trained on data collected over a physical FSO link under varying turbulence conditions. This model accurately captures real_world channel distortions, achieving a minimum Kullback_Leibler (KL) divergence of 0.0019 in amplitude distribution matching. Experimental results show that the TRFSO system trained with the BiLSTM_based channel model outperforms the same architecture trained under the additive white Gaussian noise (AWGN) channel, achieving an average 3.5 dB improvement in multi-scale structural similarity (MS_SSIM) under strong atmospheric turbulence. These results demonstrate the effectiveness of the proposed TRFSO in achieving robust and reliable transmission under dynamic atmospheric turbulence.
format Preprint
id arxiv_https___arxiv_org_abs_2509_03835
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Robust End-to-End FSO Transmission with Joint Coding Modulation and BiLSTM-Based Channel Modeling under Atmospheric Turbulence
Zhang, Wei
Yu, Zhenming
Huang, Hongyu
Dong, Xiangyong
Ma, Yan
Zhao, Yongli
Huang, Shanguo
Xu, Kun
Optics
Free space optical (FSO) communication is considered a promising solution in next_generation communication networks. However, its performance is significantly influenced by atmospheric turbulence. To enhance system robustness to turbulence, we propose a turbulence_robust end_to_end FSO communication system (TRFSO) that integrates a data-driven channel model with joint source_channel coding modulation (JSCCM). Specifically, a bidirectional long short-term memory (BiLSTM)_based channel model is developed and trained on data collected over a physical FSO link under varying turbulence conditions. This model accurately captures real_world channel distortions, achieving a minimum Kullback_Leibler (KL) divergence of 0.0019 in amplitude distribution matching. Experimental results show that the TRFSO system trained with the BiLSTM_based channel model outperforms the same architecture trained under the additive white Gaussian noise (AWGN) channel, achieving an average 3.5 dB improvement in multi-scale structural similarity (MS_SSIM) under strong atmospheric turbulence. These results demonstrate the effectiveness of the proposed TRFSO in achieving robust and reliable transmission under dynamic atmospheric turbulence.
title Robust End-to-End FSO Transmission with Joint Coding Modulation and BiLSTM-Based Channel Modeling under Atmospheric Turbulence
topic Optics
url https://arxiv.org/abs/2509.03835