杨航

Hang yang

研究方向：基于人工智能的光纤信道快速精准建模技术
博士研究生（ 2018 —— 2023 ）

办公地址：上海市东川路800号交通大学电信群楼5-501室
邮政编码：200240
电子邮箱：hangyang@sjtu.edu.cn

2018年获湖南大学工学学士学位，同年9月加入上海交通大学区域光纤通信网与新型光通信系统国家重点实验室未来光网络研究组，进行基于人工智能的光纤信道快速精准建模方向的研究。在Journal of Lightwave Technology，Optics Express等重要期刊发表多篇论文，荣获光纤国重研究生优秀奖学金、全光光子技术论坛最佳论文奖等荣誉。

期刊

[1]Hang Yang, Zekun Niu, Shilin Xiao, Jiafei Fang, Zhiyang Liu, David Fainsin, Lilin Yi. Fast and Accurate Optical Fiber Channel Modeling Using Generative Adversarial Network[J], Journal of Lightwave Technology, 2021, 39(5):1322-1333, doi: 10.1109/JLT.2020.3037905.

[2]Hang Yang, Zekun Niu, Haochen Zhao, Shilin Xiao, Weisheng Hu and Lilin Yi. Fast and Accurate Waveform Modeling of Long-Haul Multi-Channel Optical Fiber Transmission Using a Hybrid Model-Data Driven Scheme[J]. Journal of Lightwave Technology, 2022, 40(14):4571-4580.

[3]Hang Yang, Haochen Zhao, Zekun Niu, Guoqing Pu, Shilin Xiao, Weisheng Hu, and Lilin Yi,. Low-complexity full-field ultrafast nonlinear dynamics prediction by a convolutional feature separation modeling method[J]. Optics Express, 2022, 30:43691-43705.

[4] Zekun Niu, Hang Yang, Haochen. Zhao, Chenhao. Dai, Weisheng Hu and Lilin Yi, End-to-End Deep Learning for Long-haul Fiber Transmission Using Differentiable Surrogate Channel[J]. Journal of Lightwave Technology, 2022, 40(9), 2807-2822.

[5] Niuyong Zhang, Hang Yang, Zekun Niu, Lizhuo Zheng, Cao Chen, Shilin Xiao and Lilin Yi, Transformer-Based Long Distance Fiber Channel Modeling for Optical OFDM Systems[J]. Journal of Lightwave Technology, 2022, 40(24): 7779-7789.

专利:

[1] 义理林，杨航，牛泽坤，“基于数据驱动的光纤通信实验系统端到端建模方法和系统”，专利号：CN202211281083.7

[2] 义理林，赵浩辰，杨航，“基于卷积特征提取的超快脉冲光纤传输建模方法及系统”，专利号：CN202210277959.4

[3] 义理林，杨航，牛泽坤，“基于特征解耦的分布式光纤信道快速精确建模方法和系统”，专利号：CN202111478750.6

[4] 义理林，牛泽坤，杨航，“基于可微辅助信道的端到端优化方法及系统”，专利号：CN202111405475.5

[5] 义理林，牛泽坤，戴辰昊，杨航，“基于深度学习的光纤通信传输系统互信息量计算方法及系统”，专利号：CN202210540923.0

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