Research Progress on Fiber Wireless Integrated Intelligent Transmission Systems

MAO Junkai; ZHANG Jiao; ZHU Min

doi:10.13756/j.gtxyj.2025.250261

您当前的位置：

首页 >

文章列表页 >

Research Progress on Fiber Wireless Integrated Intelligent Transmission Systems

更新时间：2025-10-15

- Research Progress on Fiber Wireless Integrated Intelligent Transmission Systems
- Study on Optical Communications Issue 5, (2025)
- 作者机构：
  
  1.东南大学　移动通信全国重点实验室，南京　210096
  2.紫金山实验室，南京　211111
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2025.250261
  CLC： TN929
- Received：25 July 2025，
  
  Revised：2025-08-19，
  
  Published：10 October 2025
- 稿件说明：
移动端阅览
毛军开，张教，朱敏. 光纤无线融合智能传输系统研究进展[J]. 光通信研究，2025(5): 250261.

Mao J K, Zhang J, Zhu M. Research Progress on Fiber Wireless Integrated Intelligent Transmission Systems[J]. Study on Optical Communications, 2025(5): 250261.
毛军开，张教，朱敏. 光纤无线融合智能传输系统研究进展[J]. 光通信研究，2025(5): 250261. DOI： 10.13756/j.gtxyj.2025.250261.

Mao J K, Zhang J, Zhu M. Research Progress on Fiber Wireless Integrated Intelligent Transmission Systems[J]. Study on Optical Communications, 2025(5): 250261. DOI： 10.13756/j.gtxyj.2025.250261.

摘要

太赫兹通信技术作为第6代移动通信（6G）的核心技术，可以实现更大的传输带宽，有效解决频谱资源稀缺的问题，以满足流量和连接数急剧增长的需求。光纤无线融合（FiWi）通信系统因其高带宽、低时延和灵活覆盖的优势，已成为实现6G太赫兹通信与全场景连接的关键技术。然而，FiWi系统依旧存在线性和非线性损伤、码间干扰（ISI）和相位噪声等一些关键技术挑战。近年来，依靠机器学习（ML）技术强大的数据和模型驱动建模能力的智能信号处理，成了FiWi系统优化的新途径。文章根据ML在FiWi系统的应用，分别从信道模型、后均衡和端到端（E2E）处理3个部分，介绍了较为经典的或是最新的应用于FiWi中的ML技术，并对未来FiWi智能通信系统进行了展望。

Abstract

Terahertz communication technology is at the heart of The 6th Generation Network (6G). It can increase the transmission bandwidth and solve the problem of limited spectrum resources

making it possible to keep up with the fast growth of traffic and contacts. Due to its high bandwidth

low latency

and variable coverage

the Fiber Wireless Integrated (FiWi) communication system is now an important part of 6G terahertz communication and full-scenario connection. However

the FiWi system still has to deal with some major technical problems

such as linear and nonlinear problems

Inter Symbol Interference (ISI)

phase noise

and etc. Smart signal processing using the strong data and model-driven modeling features of Machine Learning (ML) techniques has emerged as a new way to improve FiWi systems in recent years. Considering the application of ML in the FiWi system

this paper introduces classical and current ML technologies that are used in FiWi in three parts: channel model

post-equalization

and End to End (E2E) processing. It also looks forward to the future FiWi intelligent communication system.

关键词

Keywords

references

高爽 , 张教 , 朱敏 . 超100 Gbit/s光纤无线融合传输技术进展(特邀) [J ] . 光通信研究 , 2024 ( 1 ): 230160 .

Gao S , Zhang J , Zhu M . Advances in beyond 100 Gbit/s Fiber-wireless Integrated Transmission Technology [J ] . Study on Optical Communications , 2024 ( 1 ): 230160 .

王光健 , 顾欢欢 , 李先进 . 面向未来智能互联网络的太赫兹感知与通信 [DB/OL ] . ( 2022-12-01 ) [ 2025-07-25 ] . https://www.huawei.com/cn/huaweitech/future-technologies/terahertz-sensing-communication https://www.huawei.com/cn/huaweitech/future-technologies/terahertz-sensing-communication .

Wang G J , Gu H H , Li X J . Terahertz Sensing and Communication for Future Intelligent Interconnected Networks [DB/OL ] . ( 2022-12-01 ) [ 2025-07-25 ] . https://www.huawei.com/cn/huaweitech/future-technologies/terahertz-sensing-communication https://www.huawei.com/cn/huaweitech/future-technologies/terahertz-sensing-communication .

Li X , Yu J , Chang G K . Photonics-Aided Millimeter-wave Technologies for Extreme Mobile Broadband Communications in 5G [J ] . Journal of Lightwave Technology , 2020 , 38 ( 2 ): 366 - 378 .

Yu J . Photonics-Assisted Millimeter-Wave Wireless Communication [J ] . IEEE Journal of Quantum Electronics , 2017 , 53 ( 6 ): 8000517 .

Nagatsuma T , Ducournau G , Renaud C C . Advances in Terahertz Communications Accelerated by Photonics [J ] . Nature Photonics , 2016 , 10 ( 6 ): 371 - 379 .

Zhong K , Zhou X , Huo J , et al . Digital Signal Processing for Short-Reach Optical Communications: a Review of Current Technologies and Future Trends [J ] . Journal of Lightwave Technology , 2018 , 36 ( 2 ): 377 - 400 .

Li Z , Huang C , Jia J , et al . Deep Learning-based End-to-End Bit-Wise Autoencoder for G-band Fiber-Terahertz Integrated DFT-S-OFDM Communication System [C ] // 2023 Optical Fiber Communications Conference and Exhibition (OFC) . San Diego, CA, USA : IEEE , 2023 : W2B.26 .

Li Z , Dong B , Li G , et al . Attention-Assisted Autoencoder Neural Network for End-to-End Optimization of Multi-Access Fiber-Terahertz Communication Systems [J ] . Journal of Optical Communications and Networking , 2023 , 15 ( 9 ): 711 - 725 .

Li Z , Huang C , Jia J , et al . Two-dimensional End-to-End Deep Learning Autoencoder in G-band Fiber-Terahertz Integrated Transmission for 6G RAN [C ] // 2022 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC) . Toyama, Japan : IEEE , 2022 : 9850008 .

Shi J , Li Z , Jia J , et al . Waveform-to-Waveform End-to-End Learning Framework in a Seamless Fiber-Terahertz Integrated Communication System [J ] . Journal of Lightwave Technology , 2023 , 41 ( 8 ): 2381 - 2392 .

Zhu Y , Ye J , Yan L , et al . Data-Driven End-to-End Optimization of Radio over Fiber Transmission System based on Self-supervised Learning [J ] . Journal of Light-wave Technology , 2024 , 42 ( 21 ): 7532 - 7543 .

Liu X , Zhang J , Zhu M , et al . End-to-End Optimization of Constellation Shaping Robust to Semiconductor Laser Noise and Nonlinearity in Fiber-THz System [J ] . Journal of Lightwave Technology , 2025 , 43 ( 1 ): 101 - 111 .

Belghazi M I , Baratin A , Rajeswar S , et al . MINE: Mutual Information Neural Estimation [DB/OL ] . ( 2018-01-12 ) [ 2025-07-25 ] . https://arxiv.org/abs/1801.04062 https://arxiv.org/abs/1801.04062 .

Godard D . Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems [J ] . IEEE Transactions on Communications , 1980 , 28 ( 11 ): 1867 - 1875 .

Ready M J , Gooch R P . Blind Equalization based on Radius Directed Adaptation [C ] // International Conference on Acoustics, Speech, and Signal Processing . Albuquerque, NM, USA : IEEE , 1990 : 1699 - 1702 .

di Rosa G , Richter A . Likelihood-based Selection Radius Directed Equalizer with Time-Multiplexed Pilot Symbols for Probabilistically Shaped QAM [J ] . Journal of Lightwave Technology , 2021 , 39 ( 19 ): 6107 - 6119 .

di Rosa G , Richter A . Blind Radius Directed Equalizer with Likelihood-based Selection for Probabilistically Shaped and High Order QAM [C ] // 2020 European Conference on Optical Communications (ECOC) . Brussels, Belgium : IEEE , 2020 : 1 - 4 .

刘刚 , 庞翔云 , 陈镇涛 , 等 . SC-FDE散射通信系统MMSE-HDFE-RISIC均衡 [J ] . 西安电子科技大学学报 , 2022 , 49 ( 5 ): 18 - 24 .

Liu G , Pang X Y , Chen Z T , et al . MMSE-HDFE-RISIC Equalization for SC-FDE Scatter Communication Systems [J ] . Journal of Xidian University , 2022 , 49 ( 5 ): 18 - 24 .

何婷 , 李响 , 李婕 , 等 . 基于VDFE-RLS均衡器的单波长200 Gbit/s光接入系统 [J ] . 光通信研究 , 2024 ( 1 ): 230136 .

He T , Li X , Li J , et al . Single Wavelength 200 Gbit/s Downlink Optical Access System based on Volterra Decision Feedback Equalizer [J ] . Study on Optical Communications , 2024 ( 1 ): 230136 .

张一明 , 李杰 , 胡陈君 , 等 . 基于箕舌线的变步长LMS自适应滤波算法 [J ] . 舰船电子工程 , 2025 , 45 ( 6 ): 55 - 59 .

Zhang Y M , Li J , Hu C J , et al . Variable Step Size LMS Adaptive Filtering Algorithm based on Tongue Line [J ] . Ship Electronic Engineering , 2025 , 45 ( 6 ): 55 - 59 .

Liu S , Wang X , Zhang W , et al . An Adaptive Activated ANN Equalizer Applied in Millimeter-Wave RoF Transmission System [J ] . IEEE Photonics Technology Letters , 2017 , 29 ( 22 ): 1935 - 1938 .

Liu X , Zhang J , Zhu M , et al . Nonlinearity Mitigation in a Fiber-Wireless Integrated System based on Low-Complexity Autoencoder and BiLSTM-ANN Equalizer [J ] . Optics Express , 2023 , 31 ( 12 ): 20005 - 20018 .

Zhou W , Zhao L , Zhang J , et al . 135-GHz D-band 60-Gbps PAM-8 Wireless Transmission Employing a Joint DNN Equalizer with BP and CMMA [J ] . Journal of Lightwave Technology , 2020 , 38 ( 14 ): 3592 - 3601 .

Chen J , Dong B , Jia J , et al . Spectrally Efficient Non-orthogonal Multi-Band CAP UDWDM Fiber-mmW Integration for 6G RAN Employing NN-based Direct Waveform to Symbol Conversion [C ] // 2022 Optical Fiber Communications Conference and Exhibition (OFC) . San Diego, CA, USA : IEEE , 2022 : 9748780 .

Lauinger V , Buchali F , Schmalen L . Blind Equalization for Coherent Optical Communications based on Variational Inference [C ] // OSA Advanced Photonics Congress 2021 . Washington, DC, USA : Optica Publishing Group , 2021 : SpTh1D.6 .

Lauinger V , Buchali F , Schmalen L . Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational Autoencoders [J ] . IEEE Journal on Selected Areas in Communications , 2022 , 40 ( 9 ): 2529 - 2539 .

Liu X , Zhang J , Zhu M , et al . 366.4-Gbit/s PCS-64QAM THz Transmission Enhanced by Likelihood-aware Vector-Quantized Variational Autoencoders [C ] // 49th European Conference on Optical Communications (ECOC) . Glasgow, London, UK : IET , 2023 : 10484823 .

Liu X , Zhang J , Zhu M , et al . 466.4-Gbit/s PCS-64QAM Wireless Transmission Enhanced by Dual-Polarized SISO Link and Vector-Quantized Variational Autoencoders [J ] . Optics Express , 2024 , 32 ( 17 ): 29379 - 29393 .

Sun A , Li Z , Jia J , et al . End-to-End Deep-Learning-based Photonic-Assisted Multi-User Fiber-mmWave Integrated Communication System [J ] . Journal of Light-wave Technology , 2024 , 42 ( 1 ): 80 - 94 .

Huang C , Tao L , Li Z , et al . Neural-Network-based Carrier-Less Amplitude Phase Modulated Signal Generation and End-to-End Optimization for Fiber-Terahertz Integrated Communication System [J ] . Optics Express , 2024 , 32 ( 6 ): 8623 - 8637 .

Liu X , Zhang J , Zhu M , et al . Autoencoder Learning of Constellation Shaping Robust to Semiconductor Laser Noise and Nonlinearity in Fiber-THz System [C ] // Optical Fiber Communication Conference (OFC) 2024 . San Diego, California, USA : Optica Publishing Group , 2024 : M4K.5 .

Rode A , Geiger B , Chimmalgi S , et al . End-to-End Optimization of Constellation Shaping for Wiener Phase Noise Channels with a Differentiable Blind Phase Search [J ] . Journal of Lightwave Technology , 2023 , 41 ( 12 ): 3849 - 3859 .

Li Z , Wang C , Jia J , et al . Model-driven Deep-Learning for End-to-End Optimization in Fiber-Terahertz Communication Systems [J ] . Journal of Lightwave Technology , 2025 , 43 ( 7 ): 3099 - 3117 .

张伟 , 吴季航 , 杜雨鑫 , 等 . 基于光纤无线融合的监测通信一体化系统 [J ] . 测试技术学报 , 2025 , 39 ( 1 ): 1 - 6 .

Zhang W , Wu J H , Du Y X , et al . Integrated Monitoring and Communication System based on Fiber Wireless Fusion [J ] . Journal of Test and Measurement Technology , 2025 , 39 ( 1 ): 1 - 6 .

王慧颖 , 许强 . 基于专利分析的6G天地一体化网络调制技术发展研究 [DB/OL ] . ( 2025-07-18 ) [ 2025-07-25 ] . https://d.wanfangdata.com.cn/periodical/wx-dtxjs20250714002 https://d.wanfangdata.com.cn/periodical/wx-dtxjs20250714002 .

Wang H Y , Xu Q . Research on the Development of 6G Space-Air-Ground Integrated Network Modulation Technologies based on Patent Analysis [J ] . ( 2025-07-18 ) [ 2025-07-25 ] . https://d.wanfangdata.com.cn/periodical/wxdtxjs20250714102 https://d.wanfangdata.com.cn/periodical/wxdtxjs20250714102 .

韦丽兰 . 基于深度学习算法的光通信系统信道均衡方法 [J ] . 激光杂志 , 2023 , 44 ( 9 ): 155 - 160 .

Wei L L . Channel Equalization Method for Optical Communication System based on Deep Learning Algorithm [J ] . Laser Journal , 2023 , 44 ( 9 ): 155 - 160 .

Wang B , Dai H , Xu K , et al . A Signal Processing Method of OFDM Communication Receiver based on CNN [J ] . Physical Communication , 2023 , 59 : 102055 .

Liu X , Li C , Jiang Z , et al . Low-Complexity Pruned Convolutional Neural Network based Nonlinear Equalizer in Coherent Optical Communication Systems [J ] . Electronics , 2023 , 12 ( 14 ): 3120 .

Jiang X , Wang D , Fan Q , et al . Physics-Informed Neural Network for Nonlinear Dynamics in Fiber Optics [J ] . Laser & Photonics Reviews , 2022 , 16 ( 9 ): 2100483 .

Views

414

下载量

CSCD

CNKI被引量

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research Progress of Non-line-of-sight Underwater Wireless Optical Communication Technology

Constellation Geometrically-shaping and Artificial Intelligence Technology in Underwater Visible Light Communication

Modeling and Analysis of 5G Terminal Communication Channel in Substation

Modeling of UAV MIMO Channel Model based on 3D Geometry

Visible light communication-based channel modeling and encoding performance analysis

Related Author

YANG Qun-hui

ZHOU Hui

PAN Yan-yan

WANG Meng-qi

YUAN He-xiang

KONG Mei-wei

CHI Nan

LIN Xian-hao

Related Institution

State Key Laboratory of Marine Geology, Tongji University

The Ministry of Education Key Laboratory of Electromagnetic Wave Information Science, Department of Communication Science and Engineering, Fudan University

Peng Cheng Laboratory

Shanghai Engineering Research Center of Low-Earth-Orbit Satellite Communication and Applications

Shanghai Collaborative Innovation Center of Low-Earth-Orbit Satellite Communication Technology

Postal code：430205
Technical support is provided by Beijing Founder electronics co., LTD 鄂ICP备2022010197 鄂公网安备 42011202002092号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.
Total Visits：304943 Visits Today：552

⁰