摘要
In this paper, a conditional generative adversarial network (CGAN) aided channel modeling technique is proposed for few-mode fiber (FMF) optical communication. Simulation results demonstrate the proposed CGAN-aided FMF modeling technique achieve an attractive effect on modelling accuracy.
源语言 | 英语 |
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主期刊名 | 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023 |
出版商 | Institute of Electrical and Electronics Engineers Inc. |
ISBN(电子版) | 9798350343502 |
DOI | |
出版状态 | 已出版 - 2023 |
活动 | 21st International Conference on Optical Communications and Networks, ICOCN 2023 - Qufu, 中国 期限: 31 7月 2023 → 3 8月 2023 |
出版系列
姓名 | 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023 |
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会议
会议 | 21st International Conference on Optical Communications and Networks, ICOCN 2023 |
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国家/地区 | 中国 |
市 | Qufu |
时期 | 31/07/23 → 3/08/23 |
指纹
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Yuan, M., Chang, H., Ma, M., Gao, R., Wang, F., Zhang, Q., Guo, D., Li, Z., Wang, F., & Huang, X. (2023). A Conditional Generative Adversarial Network aided Few-mode Fiber Channel Modeling for large-capacity optical fiber communication. 在 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023 (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOCN59242.2023.10236403