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Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications

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A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Optical Communication and Network".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 33116

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Special Issue Editors

Dr. Jian Zhao

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Guest Editor

School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300000, China
Interests: linear optical communication systems; performance monitoring techniques for optical networks; integrated fiber devices for optical communication; novel fiber design; digital signal processing techniques in fiber-optic communication systems; few-mode microwave photonics
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Prof. Dr. Jiangbing Du

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State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: optical communications; optical signal processing; photonic integration
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Prof. Dr. Yang Yue

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School of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: intelligent photonics; optical communications; optical perception; optical chip
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Prof. Dr. Jianguo Liu

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Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
Interests: optical communication; microwave photonics; lasers for information and modular integration technology
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Special Issue Information

Dear Colleagues,

With the emergence of various applications, higher requirements are put forward for optical communication systems and network capacity. Especially since the COVID-19 epidemic this year, the whole world has been seriously affected. New types of businesses such as remote work and online teaching have led to a blowout growth in global network traffic and instantaneous traffic keeps refreshing records. With the development of DSP technology, the coherent optical communication system with complex modulation has greatly improved the capacity of single-mode fiber by improving the spectral efficiency. As the optical communication system and network become more and more complex and huge, novel effective methods need to be proposed to meet the new challenges. Artificial intelligence (AI) technology has made great progress in recent years and has been the focus of broad interest. The increasing complexity of optical communication systems and networks has stimulated the application of AI, covering performance monitoring, equipment and network control, and management. Although the application of AI in optical communication is still in its infancy, it has great potential in the future.

This Special Issue will explore advanced analytical tools and novel technologies for next-generation optical fiber communication systems and networks. It will focus on state-of-the-art advances and future perspectives from fundamental theories to applications and also including devices, subsystems, and networks. Topics of interest include, but are not limited to, the following areas:

Nonlinear fiber optics
Advanced devices
DSP for direct detection and coherent detection technique
Advanced modulation format and pulse shaping technology
Ultra-wideband optical fiber communication system
AI and deep learning application in optical fiber communication
Optical network control and management

Dr. Jian Zhao
Dr. Jiangbing Du
Prof. Dr. Yang Yue
Prof. Dr. Jianguo Liu
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Fiber nonlinearities
Artificial intelligence (AI)
Machine learning (ML)
Deep learning (DL)
Ultra-wideband fiber communication
Coherent communications
Digital signal processing (DSP)
MIMO technique
Direct-detection system
Optical fiber and device
High-order modulations
Pulse shaping
Probabilistic shaping
Silicon photonics
Photonic integrated circuit
Wavelength division multiplexing
Passive optical network
Optical access network
Metro and core networks
Data center network
Software-defined network

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Published Papers (9 papers)

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Editorial

Jump to: Research

3 pages, 176 KiB

Open AccessEditorial

Special Issue on Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications

by Jian Zhao, Jiangbing Du, Yang Yue and Jianguo Liu

Photonics 2022, 9(5), 280; https://doi.org/10.3390/photonics9050280 - 20 Apr 2022

Cited by 3 | Viewed by 2558

Abstract

Optical communication refers to the communication mode with optical signal as a carrier [...] Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

Research

Jump to: Editorial

17 pages, 4477 KiB

Open AccessCommunication

Performance Enhancement of DWDM-FSO Optical Fiber Communication Systems Based on Hybrid Modulation Techniques under Atmospheric Turbulence Channel

by Mohammed R. Hayal, Bedir B. Yousif and Mohamed A. Azim

Photonics 2021, 8(11), 464; https://doi.org/10.3390/photonics8110464 - 22 Oct 2021

Cited by 28 | Viewed by 3569

Abstract

In this paper, we enhance the performance efficiency of the free-space optical (FSO) communication link using the hybrid on-off keying (OOK) modulation, M-ary digital pulse position modulation (M-ary DPPM), and M-pulse amplitude and position modulation (M-PAPM). This work analyzes and enhances the bit error rate (BER) performance of the moment generating function, modified Chernoff bound, and Gaussian approximation techniques. In the existence of both an amplified spontaneous emission (ASE) noise, atmospheric turbulence (AT) channels, and interchannel crosstalk (ICC), we propose a system model of the passive optical network (PON) wavelength division multiplexing (WDM) technique for a dense WDM (DWDM) based on the hybrid fiber FSO (HFFSO) link. We use eight wavelength channels that have been transmitted at a data rate of 2.5 Gbps over a turbulent HFFSO-DWDM system and PON-FSO optical fiber start from 1550 nm channel spacing in the C-band of 100 GHz. The results demonstrate (2.5 Gbps × 8 channels) 20 Gbit/s-4000 m transmission with favorable performance. In this design, M-ary DPPM-M-PAPM modulation is used to provide extra information bits to increase performance. We also propose to incorporate adaptive optics to mitigate the AT effect and improve the modulation efficiency. We investigate the impact of the turbulence effect on the proposed system performance based on OOK-M-ary PAPM-DPPM modulation as a function of M-ary DPPM-PAPM and other atmospheric parameters. The proposed M-ary hybrid DPPM-M-PAPM solution increases the receiver sensitivity compared to OOK, improves the reliability and achieves a lower power penalty of 0.2–3.0 dB at low coding level (M) 2 in the WDM-FSO systems for the weak turbulence. The OOK/M-ary hybrid DPPM-M-PAPM provides an optical signal-to-noise ratio of about 4–8 dB of the DWDM-HFFSO link for the strong turbulence at a target BER of 10⁻¹². The numerical results indicate that the proposed design can be enhanced with the hybrid OOK/M-DPPM and M-PAPM for DWDM-HFFSO systems. The calculation results show that PAPM-DPPM has increased about 10–11 dB at BER of 10⁻¹² more than the OOK-NRZ approach. The simulation results show that the proposed hybrid optical modulation technique can be used in the DWDM-FSO hybrid links for optical-wireless and fiber-optic communication systems, significantly increasing their efficiency. Finally, the use of the hybrid OOK/M-ary DPPM-M-PAPM modulation schemes is a new technique to reduce the AT, ICC, ASE noise for the DWDM-FSO optical fiber communication systems. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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10 pages, 2306 KiB

Open AccessArticle

Design of a Free Space Optical Communication System for an Unmanned Aerial Vehicle Command and Control Link

by Yiqing Zhang, Yuehui Wang, Yangyang Deng, Axin Du and Jianguo Liu

Photonics 2021, 8(5), 163; https://doi.org/10.3390/photonics8050163 - 14 May 2021

Cited by 11 | Viewed by 3895

Abstract

An electromagnetic immune Free Space Optical Communication (FSOC) system for an Unmanned Aerial Vehicle (UAV) command and control link is introduced in this paper. The system uses the scheme of omnidirectional receiving and ground scanning transmitting. It has a strong anti-turbulence ability by using a large area detector and short-focus lens. The design of omnidirectional communication improves the ability of anti-vibration and link establishment. Pure static reception has no momentum effect on the platform. The receiver is miniaturized under no use of a gimbal mirror system, beacon camera system, Four-Quadrant Photodetector (QPD) and multi-level lens system. The system can realize omnidirectional reception and the communication probability in 1 s is greater than 99.99%. This design strengthens the ability of the FSOC system, so it can be applied in the UAV command and control, the satellite submarine communication and other occasions where the size of the platform is restricted. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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22 pages, 23899 KiB

Open AccessArticle

A QoS-Aware Dynamic Bandwidth Allocation Algorithm for Passive Optical Networks with Non-Zero Laser Tuning Time

by Mohammad Zehri, Adebanjo Haastrup, David Rincón, José Ramón Piney, Sebastià Sallent and Ali Bazzi

Photonics 2021, 8(5), 159; https://doi.org/10.3390/photonics8050159 - 10 May 2021

Cited by 7 | Viewed by 2891

Abstract

The deployment of new 5G services and future demands for 6G make it necessary to increase the performance of access networks. This challenge has prompted the development of new standardization proposals for Passive Optical access Networks (PONs) that offer greater bandwidth, greater reach and a higher rate of aggregation of users per fiber, being Time- and Wavelength-Division Multiplexing (TWDM) a promising technological solution for increasing the capacity by up to 40 Gbps by using several wavelengths. This solution introduces tunable transceivers into the Optical Network Units (ONUs) for switching from one wavelength to the other, thus addressing the ever-increasing bandwidth demands in residential broadband and mobile fronthaul networks based on Fiber to the Home (FTTH) technology. This adds complexity and sources of inefficiency, such as the laser tuning time (LTT) delay, which is often ignored when evaluating the performance of Dynamic Bandwidth Allocation (DBA) mechanisms. We present a novel DBA algorithm that dynamically handles the allocation of bandwidth and switches the ONUs’ lasers from one wavelength to the other while taking LTT into consideration. To optimize the packet delay, we introduce a scheduling mechanism that follows the Longest Processing Time first (LPT) scheduling discipline, which is implemented over the Interleaved Polling with Adaptive Cycle Time (IPACT) DBA. We also provide quality of service (QoS) differentiation by introducing the Max-Min Weighted Fair Share Queuing principle (WFQ) into the algorithm. The performance of our algorithm is evaluated through simulations against the original IPACT algorithm, which we have extended to support multi-wavelengths. With the introduction of LPT, we obtain an improved performance of up to 73% reduction in queue delay over IPACT while achieving QoS differentiation with WFQ. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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14 pages, 1744 KiB

Open AccessEditor’s ChoiceArticle

Optical Machine Learning Using Time-Lens Deep Neural NetWorks

by Luhe Zhang, Caiyun Li, Jiangyong He, Yange Liu, Jian Zhao, Huiyi Guo, Longfei Zhu, Mengjie Zhou, Kaiyan Zhu, Congcong Liu and Zhi Wang

Photonics 2021, 8(3), 78; https://doi.org/10.3390/photonics8030078 - 15 Mar 2021

Cited by 8 | Viewed by 5895

Abstract

As a high-throughput data analysis technique, photon time stretching (PTS) is widely used in the monitoring of rare events such as cancer cells, rough waves, and the study of electronic and optical transient dynamics. The PTS technology relies on high-speed data collection, and the large amount of data generated poses a challenge to data storage and real-time processing. Therefore, how to use compatible optical methods to filter and process data in advance is particularly important. The time-lens proposed, based on the duality of time and space as an important data processing method derived from PTS, achieves imaging of time signals by controlling the phase information of the timing signals. In this paper, an optical neural network based on the time-lens (TL-ONN) is proposed, which applies the time-lens to the layer algorithm of the neural network to realize the forward transmission of one-dimensional data. The recognition function of this optical neural network for speech information is verified by simulation, and the test recognition accuracy reaches 95.35%. This architecture can be applied to feature extraction and classification, and is expected to be a breakthrough in detecting rare events such as cancer cell identification and screening. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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18 pages, 5621 KiB

Open AccessArticle

Peak-to-Average Power Ratio Reduction of Carrier-Suppressed Optical SSB Modulation: Performance Comparison of Three Methods

by K. I. Amila Sampath, Katsumi Takano and Joji Maeda

Photonics 2021, 8(3), 67; https://doi.org/10.3390/photonics8030067 - 26 Feb 2021

Cited by 6 | Viewed by 3249

Abstract

We compare the performances of three previously proposed methods to reduce the peak-to-average power ratio (PAPR) of the carrier-suppressed optical single-sideband (OSSB-SC) signal. PAPR of OSSB-SC signal becomes high due to the peaky Hilbert-transformed signal which is used for spectral suppression. Nonlinear phase shifts induced by high PAPR degrade OSSB-SC signal during fiber transmission. Previously, we proposed peak folding, peak clipping, and high-pass Hilbert transform methods to reduce the PAPR of OSSB-SC modulation. In this study, we numerically compare the effectiveness of proposed methods in a 10 Gbit/s non-return-to-zero (NRZ)-coded 100-km single-channel transmission link. Due to the reduced PAPR, peak folding and peak clipping can increase the self-phase modulation (SPM) threshold of the studied system by 2.40 dB and 2.63 dB respectively. The high-pass Hilbert transform method improves the SPM threshold by more than 9 dB. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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10 pages, 12533 KiB

Open AccessArticle

Comparing Performance of Deep Convolution Networks in Reconstructing Soliton Molecules Dynamics from Real-Time Spectral Interference

by Caiyun Li, Jiangyong He, Yange Liu, Yang Yue, Luhe Zhang, Longfei Zhu, Mengjie Zhou, Congcong Liu, Kaiyan Zhu and Zhi Wang

Photonics 2021, 8(2), 51; https://doi.org/10.3390/photonics8020051 - 13 Feb 2021

Cited by 3 | Viewed by 3089

Abstract

Deep neural networks have enabled the reconstruction of optical soliton molecules with more complex structures using the real-time spectral interferences obtained by photonic time-stretch dispersive Fourier transformation (TS-DFT) technology. In this paper, we propose to use three kinds of deep convolution networks (DCNs), including VGG, ResNets, and DenseNets, for revealing internal dynamics evolution of soliton molecules based on the real-time spectral interferences. When analyzing soliton molecules with equidistant composite structures, all three models are effective. The DenseNets with layers of 48 perform the best for extracting the dynamic information of complex five-soliton molecules from TS-DFT data. The mean Pearson correlation coefficient (MPCC) between the predicted results and the real results is about 0.9975. Further, the ResNets in which the MPCC achieves 0.9906 also has the better ability of phase extraction than VGG which the MPCC is about 0.9739. The general applicability is demonstrated for extracting internal information from complex soliton molecule structures with high accuracy. The presented DCNs-based techniques can be employed to explore undiscovered mechanisms underlying the distribution and evolution of large numbers of solitons in dissipative systems in experimental research. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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15 pages, 1804 KiB

Open AccessArticle

Patent Technology Network Analysis of Machine-Learning Technologies and Applications in Optical Communications

by Shu-Hao Chang

Photonics 2020, 7(4), 131; https://doi.org/10.3390/photonics7040131 - 15 Dec 2020

Cited by 2 | Viewed by 2744

Abstract

As the Internet of Things (IoT) develops, applying machine learning on optical communications has become a prospective field of research. Scholars have mostly concentrated on algorithmic techniques or specific applications but have been unable to address the distribution of machine-learning technologies and the development of its applications in optical communications from a macro perspective. Therefore, in this paper, machine-learning patents in optical communications are taken as the analytical basis for constructing a patent technology network. The study results revealed that key technologies were primarily in data input and output devices, data-processing methods, wireless communication networks, and the transmission of digital information in optical communications. Such technologies were also applied to perform measurement for diagnostic purposes and medical diagnoses. The technology network model proposed in this paper explores the technological development trends of machine learning in optical communications and serves as a reference for allocating research and development resources. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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11 pages, 8226 KiB

Open AccessArticle

A Novel Data-Aided Frame Synchronization Method Based on Hough Transform for Optical Communications

by Huiwen Yin, Sida Li, Zhiping Huang and Jie Chen

Photonics 2020, 7(3), 65; https://doi.org/10.3390/photonics7030065 - 27 Aug 2020

Cited by 3 | Viewed by 3439

Abstract

In optical communication systems, frame synchronization is essential for subsequent operations, such as error correction and payload extraction. Various methods, so far, have been proposed in the published literature, but the performance is unsatisfactory under high bit error rate (BER) conditions. We present, in this work, a novel data-aided frame synchronization technique for optical packet transmission systems, in which the transmitter sends a sequence of packets with a specific synchronization word periodically inserted, and the receiver blindly recognizes the synchronization word to attain frame synchronization. The proposed algorithm detects the synchronization word based on Hough transform (HT), a classic method for line detection in digital image processing. The core principle of the algorithm is to exploit the periodicity of the frame synchronization word, which appears as black-and-white spaced stripes on a binary image when the frames are all aligned. Simulations are conducted over a 56Gbps optical QPSK transmission system, and the results show that our algorithm is still effective in attaining frame synchronization at a BER of 0.3. A comparison is also made between our algorithm and existed autocorrelation (AC)-based algorithm. The results demonstrate that our algorithm has a better error resilience performance. When the BER is higher than 0.03, our algorithm outperforms an AC-based algorithm significantly. Full article

(This article belongs to the Special Issue Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications)

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