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Real-time and ultrafast optical pulse quantization based on slicing the supercontinuum

Chinese Optics Letters 2021年第8期19卷 69-74页

作者： Ya Guo Qiang Cai Zhiwei Jia Bingjie Xu Zhensen Gao Qianwu Zhang Ruonan Zhang Adonis Bogris K.Alan Shore Yuncai Wang Pu Li Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710072China Science and Technology on Communication Security Laboratory Institute of Southwestern CommunicationChengdu 610041China Department of Informatics and Computer Engineering University of West AtticaAthens 12243Greece School of Electronic Engineering Bangor UniversityWales LL571UTUnited Kingdom

All-optical analog-to-digital conversion is a paramount issue in modern science. How to implement real-time and ultrafast quantization to optical pulses with different intensities in an all-optical domain is a central problem. Here, we report a realtime demonstration of an all-optical quantization scheme based on slicing the supercontinuum in a nonlinear fiber. In comparison with previous schemes through off-line analysis of the power of different optical spectral components in the supercontinuum, this, to the best of our knowledge, is the first demonstration of such functionality online in the time ***, the extinction ratio among the quantized outputs can exceed 10 d B, which further confirms the feasibility of the proposed quantization scheme. The current 3 bit resolution in the proof-of-principle experiment is limited by the current experimental condition, but it can be expected to be greatly enhanced through improving both the spectral width of the generated supercontinuum and the number of filtering channels used.

关键词： all-optical analog-to-digital conversion photonic quantization all-optical signal processing supercontinuum generation

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Dual Representation Learning for One-Step Clustering of Multi-View Data

arXiv

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arXiv 2022年

作者： Zhang, Wei Deng, Zhaohong Choi, Kup-Sze Wang, Jun Wang, Shitong The School of Artificial Intelligence and Computer Science Jiangnan University Jiangsu Key Laboratory of Media Design and Software Technology Wuxi214122 China The School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214122 China ZJLab Shanghai200433 China The Centre for Smart Health The Hong Kong Polytechnic University Hong Kong The Key laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University Shanghai200444 China

Multi-view data are commonly encountered in data mining applications. Effective extraction of information from multi-view data requires specific design of clustering methods to cater for data with multiple views, which is non-trivial and challenging. In this paper, we propose a novel one-step multi-view clustering method by exploiting the dual representation of both the common and specific information of different views. The motivation originates from the rationale that multi-view data contain not only the consistent knowledge between views but also the unique knowledge of each view. Meanwhile, to make the representation learning more specific to the clustering task, a one-step learning framework is proposed to integrate representation learning and clustering partition as a whole. With this framework, the representation learning and clustering partition mutually benefit each other, which effectively improves the clustering performance. Results from extensive experiments conducted on benchmark multi-view datasets clearly demonstrate the superiority of the proposed method. Copyright © 2022, The Authors. All rights reserved.

关键词： Cluster analysis

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Malus-metasurface-assisted polarization multiplexing

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Light(Science & Applications) 2020年第1期9卷 1038-1046页

作者： Liangui Deng Juan Deng Zhiqiang Guan Jin Tao Yang Chen Yan Yang Daxiao Zhang Jibo Tang Zhongyang Li Zile Li Shaohua Yu Guoxing Zheng Hongxing Xu Cheng-Wei Qiu Shuang Zhang Electronic Information School Wuhan University430072 WuhanChina NOEIC State Key Laboratory of Optical Communication Technologies and NetworksWuhan Research Institute of Posts&Telecommunications430074 WuhanChina School of Physics and Technology Wuhan University430072 WuhanChina Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore Integrated Circuit Advanced Process Center Institute of MicroelectronicsChinese Academy of Sciences100029 BeijingChina School of Physics&Astronomy University of BirminghamBirmingham B152TTUK

Polarization optics plays a pivotal role in diffractive,refractive,and emerging flat optics,and has been widely employed in contemporary optical industries and daily *** polarization manipulation leads to robust control of the polarization direction of ***,polarization control has been studied largely independent of the phase or intensity of ***,we propose and experimentally validate a Malus-metasurface-assisted paradigm to enable simultaneous and independent control of the intensity and phase properties of light simply by polarization *** orientation degeneracy of the classical Malus’s law implies a new degree of freedom and enables us to establish a one-to-many mapping strategy for designing anisotropic plasmonic nanostructures to engineer the Pancharatnam–Berry phase profile,while keeping the continuous intensity modulation *** proposed Malus metadevice can thus generate a near-field greyscale pattern,and project an independent far-field holographic image using an ultrathin and single-sized *** concept opens up distinct dimensions for conventional polarization optics,which allows one to merge the functionality of phase manipulation into an amplitudemanipulation-assisted optical component to form a multifunctional nano-optical device without increasing the complexity of the *** can empower advanced applications in information multiplexing and encryption,anti-counterfeiting,dual-channel display for virtual/augmented reality,and many other related fields.

关键词： optics enable unchanged

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Swarm of UAVs for Network Management in 6G: A Technical Review

arXiv

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arXiv 2022年

作者： Khan, Muhammad Asghar Kumar, Neeraj Mohsan, Syed Agha Hassnain Khan, Wali Ullah Nasralla, Moustafa M. Alsharif, Mohammed H. Zywiolek, Justyna Ullah, Insaf The Hamdard Institute of Engineering and Technology Islamabad45550 Pakistan Department of Computer Science and Information Engineering Asia University Taiwan School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India Optical Communication Laboratory Ocean College Zhejiang University Zheda Road 1 Zhoushan316021 China University of Luxembourg Luxembourg City1855 Luxembourg Communications and Networks Engineering Department Prince Sultan University Riyadh Saudi Arabia Sejong University Seoul05006 Korea Republic of Czestochowa University of Technology Czestochowa Poland

Fifth-generation (5G) cellular networks have led to the implementation of beyond 5G (B5G) networks, which are capable of incorporating autonomous services to swarm of unmanned aerial vehicles (UAVs). They provide capacity expansion strategies to address massive connectivity issues and guarantee ultra-high throughput and low latency, especially in extreme or emergency situations where network density, bandwidth, and traffic patterns fluctuate. On the one hand, 6G technology integrates AI/ML, IoT, and blockchain to establish ultra-reliable, intelligent, secure, and ubiquitous UAV networks. 6G networks, on the other hand, rely on new enabling technologies such as air interface and transmission technologies, as well as a unique network design, posing new challenges for the swarm of *** these challenges in mind, this article focuses on the security and privacy, intelligence, and energy-efficiency issues faced by swarms of UAVs operating in 6G mobile network. In this state-of-the-art review, we integrated blockchain and AI/ML with UAV networks utilizing the 6G ecosystem. The key findings are then presented, and potential research challenges are identified. We conclude the review by shedding light on future research in this emerging field of research. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy efficiency

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High sensitivity interferometric fiber optic gyroscopes for 6-component seismograph 27

High sensitivity interferometric fiber optic gyroscopes for ...

引用

27th International Conference on Optical Fiber Sensors, OFS 2020

作者： Cao, Yuwen He, Dong Zhang, Dingfan Zhang, Wentao Li, Li Li, Zhengbin State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing100871 China State Key Laboratory of Transducer Technology Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China Institute of Geophysics China Earthquake Administration Beijing100081 China

The principle of dual polarized fiber optic gyroscope insensitive to the temperature and magnetic field variance is presented, and several novel experiments have been demonstrated, including earthquake detection, envi... 详细信息

ISBN: (纸本)9781557523075

关键词： Fiber optics

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Dynamic Scheduling for Delay-Critical Packets in a Networked Control System Using WirelessHART

Dynamic Scheduling for Delay-Critical Packets in a Networked...

引用

IEEE International Conference on communications (ICC)

作者： Samuele Zoppi Jaya Prakash Champati James Gross Wolfgang Kellerer Chair of Communication Networks Technical University of Munich Germany School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

In future industrial scenarios, Wireless Sensor networks (WSN) are envisioned to support the traffic of Networked Control Systems (NCS). WirelessHART is a prevalent WSN protocol that uses the Time Slotted Channel Hopping (TSCH) medium access to cope with the delay and reliability requirements of NCS in the harsh industrial environment. In TSCH, time slots and frequencies can be scheduled by a network coordinator to provide Quality of Service (QoS). In contrast to previous works that consider the end-to-end delay requirement of a flow of packets, we focus on a finite sequence of time-critical packets. These packets may belong to a time-critical message whose latency could significantly impact the NCS. Given an end-to-end delay deadline, our objective is to minimize the Delay Violation Probability (DVP) for a finite sequence of packets by dynamically scheduling the time slots in each frame. This is a challenging task as DVP depends on the instantaneous state of the network and requires its transient analysis. In this work, we model the wireless NCS as a two-queue lossy wireless network and propose the first transient analysis of DVP for a finite sequence of time-critical packets. Noting that DVP cannot be directly used for dynamic resource allocation, we propose a heuristic algorithm by relating DVP with the network's throughput. The proposed heuristic maximizes the expected throughput, is computed by solving a finite-horizon Markov Decision Process (MDP), and can be implemented at the network coordinator. Using simulation we demonstrate that the MDP-based heuristic achieves lower DVP compared to the classical MaxWeight and Weighted-Fair Queuing.

关键词： Delays Wireless sensor networks Reliability Dynamic scheduling Time factors Time division multiple access Quality of service

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset

A Horizontal Federated Learning Approach to IoT Malware Traf...

引用

International Conference on Advanced communication Technology (ICACT)

作者： Phuc Hao Do Tran Duc Le Vladimir Vishnevsky Aleksandr Berezkin Ruslan Kirichek The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Saint-Petersburg Russia Danang Architecture University Da Nang Viet Nam Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State University of Telecommunications Russia University of Science and Technology - The University of Danang Da Nang Viet Nam Information Technology Faculty The University of Danang - University of Science and Technology Danang Vietnam V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Institute of Control Sciences of Russian Academy of Sciences Russia Department of Programming Engineering and Computer Science Bonch Bruevich Saint Petersburg State University of Telecommunications

The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simultaneously ensuring user data privacy and detecting botnet attacks. To address this issue, this study evaluates the efficacy of Federated Learning (FL) in detecting IoT malware traffic while preserving user privacy. The study employs N-BaIoT, a dataset of real-world IoT network traffic infected by malware, and compares the effectiveness of FL models using Convolutional Neural Network, Long Short-Term Memory, and Gated Recurrent Unit models with a centralized approach. The results indicate that FL can achieve high performance in detecting abnormal traffic in IoT networks, with the CNN model yielding the best results among the three models evaluated. The study recommends the use of FL for IoT malware traffic detection due to its ability to preserve data privacy.

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Correction to: Automatic COVID-19 detection mechanisms and approaches from medical images: a systematic review

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Multimedia tools and applications 2022年第20期81卷 28799-28800页

作者： Amir Masoud Rahmani Elham Azhir Morteza Naserbakht Mokhtar Mohammadi Adil Hussein Mohammed Aldalwie Mohammed Kamal Majeed Sarkhel H Taher Karim Mehdi Hosseinzadeh Future Technology Research Center National Yunlin University of Science and Technology Douliu Yunlin Taiwan. Research and Development Center Mobile Telecommunication Company of Iran Tehran Iran. Mental Health Research Center Psychosocial Health Research Institute Iran University of Medical Sciences Tehran Iran. Department of Information Technology College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq. Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq. Information Technology Department Faculty of Applied Science Tishk International University Erbil Iraq. Computer Department College of Science University of Halabja Halabja Iraq. Computer Networks Department Sulaimani Polytechnic University Technical College of Informatics Sulaymaniyah Iraq. Computer Science University of Human Development Sulaymaniyah Iraq.

[This corrects the article DOI: 10.1007/s11042-022-12952-7.].

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Customized slicing for 6G: Enforcing artificial intelligence on resource management

arXiv

引用

arXiv 2021年

作者： Guan, Wanqing Zhang, Haijun Leung, Victor C.M. Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Next generation wireless networks are expected to support diverse vertical industries and offer countless emerging use cases. To satisfy stringent requirements of diversified services, network slicing is developed, which enables service-oriented resource allocation by tailoring the infrastructure network into multiple logical networks. However, there are still some challenges in cross-domain multi-dimensional resource management for end-to-end (E2E) slices under the dynamic and uncertain environment. Trading off the revenue and cost of resource allocation while guaranteeing service quality is significant to tenants. Therefore, this article introduces a hierarchical resource management framework, utilizing deep reinforcement learning in admission control of resource requests from different tenants and resource adjustment within admitted slices for each tenant. Particularly, we first discuss the challenges in customized resource management of 6G. Second, the motivation and background are presented to explain why artificial intelligence (AI) is applied in resource customization of multi-tenant slicing. Third, E2E resource management is decomposed into two problems, multi-dimensional resource allocation decision based on slice-level feedback and real-time slice adaption aimed at avoiding service quality degradation. Simulation results demonstrate the effectiveness of AI-based customized slicing. Finally, several significant challenges that need to be addressed in practical implementation are investigated. Copyright © 2021, The Authors. All rights reserved.

关键词： Resource allocation

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1.3-μm 4×25-Gb/s hybrid integrated TOSA and ROSA

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Frontiers of Information Technology & Electronic engineering 2019年第4期20卷 490-497页

作者： Yu LIU Hao-tian BAO Yi-ming ZHANG Zhi-ke ZHANG Yun-shan ZHANG Xiang-fei CHEN Jun LU Yue-chun SHI Jia-shun ZHANG Liang-liang WANG Jun-ming AN Ning-hua ZHU State Key Laboratory on Integrated Optoelectronics Institute of Semiconductors Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Engineering and Computer Science Peking University Microwave-Photonics Technology Laboratory College of Engineering and Applied Sciences Nanjing University

The design and fabrication of a compact and low-cost 4×25-Gb/s transmitter optical sub-assembly(TOSA) and receiver optical sub-assembly(ROSA) using a hybrid integrated technique are reported. TOSA and ROSA are developed without thermoelectric cooler for coarse wavelength division multiplexing applications. Physical dimension of the packaged optical subassembly is limited to 11.5 mm×5.4 mm×5.4 mm. The design of TOSA and ROSA is employed using a silica-based arrayed waveguide grating chip to select the specific channel wavelength at O-band. In TOSA, the wavelength of four 1.3-μm discrete directly modulated laser chips is well controlled based on the reconstruction equivalent chirp technique. In the back-to-back transmission test, bit error rates for all lanes of cascade of the TOSA and ROSA are small. A clear opening eye diagram is obtained.

关键词： Reconstruction equivalent chirp Arrayed waveguide grating Transmitter optical subassembly Hybrid integrated

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