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11th China Satellite Navigation Conference, CSNC 2020

作者： Yang, Menghuan Wu, Hong Peng, Hongzhao Chen, Zhuo College of Electronic Information and Optical Engineering Nankai University Tianjin China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin China

ISBN: (纸本)9789811537066

Location-based services have become an indispensable part of people’s daily lives. GNSS can provide favorable outdoor location services, but it cannot meet the needs of indoor positioning. This paper proposes an indoor localization fingerprint system using DTMB and FM signals, which consists of offline and online stages. In the offline stage, the Received Signal Strength of the Reference Points is measured in the experimental area, and the data acquisition amount is reduced by Compressive sensing theory. In the online stage, the coordinates of Test Points are reconstructed by using Compressive sensing algorithm. The experiments show that the average positioning accuracy of the DTMB and FM signal indoor positioning system based on Compressive sensing is about 2.14 m. The proposed system has larger coverage and lower cost, which can meet the actual indoor positioning requirements. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Compressed sensing

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FM and DTMB Signal Fingerprinting Positioning System Based on Multi-peak Gaussian Distribution Model 11th

FM and DTMB Signal Fingerprinting Positioning System Based o...

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11th China Satellite Navigation Conference, CSNC 2020

作者： Qiao, Hongyu Wu, Hong Yang, Menghuan Peng, Hongzhao Yang, Haixiao Zhao, Bin College of Electronic Information and Optical Engineering Nankai University Tianjin China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin China

ISBN: (纸本)9789811537066

With the rapid development of wireless communication technology and the popularization of smart devices, all walks of life are constantly exploring location-based services in recent years. This paper proposes a combination of Frequency Modulation (FM) signal and Digital Television Terrestrial Multimedia Broadcasting (DTMB) signal to improve the indoor positioning accuracy of the new method for the disadvantages of partial positioning technology. The signal intensity of FM and DTMB is taken as the position fingerprint. The multi-peak Gaussian distribution model is used to fit the signal intensity, and then the probabilistic positioning matching algorithm is used to achieve high-precision positioning in the room. We verified the feasibility of the method through actual measurements in the indoor environment. Compared with the existing positioning technology, this method has the advantages of large coverage, high stability, low cost and high precision. The accuracy of the joint positioning of two signals is higher than that of the FM signal alone. It is verified that the positioning error of this system can reach 1.20 m when the multi-peak Gaussian distribution model is used. Compared with the single-peak Gaussian distribution model, the positioning accuracy is improved by about 0.80 m, which has certain reference significance in the field of indoor positioning. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Digital television

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Transmit RRH Selection in User-Centric Cell-Free Massive MIMO Using Discrete Particle Swarm Optimization 1

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3rd International Conference on Artificial Intelligence, 2022

作者： Li, Jiaxiang Zhao, Yingxin Wu, Hong Liu, Zhiyang Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology College of Electronic Information and Optical Engineering Nankai University Tianjin300350 China

ISBN: (数字)9789811694233

ISBN: (纸本)9789811694226

Cell-free massive multiple input multiple output (MIMO) has been expected to improve the spectrum efficiency in future mobile communication systems. To reduce the fronthaul link burden, a user-centric structure is expected, where a subset of remote radio heads (RRHs) are expected to form a virtual cell and serve the user. However, how to select serving RRHs for each user so as to maximize the rate performance remains to be an open question. In this paper, by assuming that each RRH can only be selected by at most one user, an improved discrete particle swarm optimization (IDPSO) has been proposed to accelerate its convergency. To further reduce the fronthaul link burden, a large-scale-fading-based fitness function is also adopted. Numerical results reveal that the proposed algorithm is able to achieve a good tradeoff between sum rate performance and the computational complexity. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mobile telecommunication systems

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A label-free lateral offset spliced coreless fiber MZI biosensor based on hydrophobin HGFI for TNF-α detection

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optoelectronics Letters 2022年第5期18卷 263-268页

作者： WANG Bo DUAN Shaoxiang ZHANG Hao XU Haijin LIU Bo QIAO Mingqiang The Key Laboratory of Molecular Microbiology and Technology Ministry of EducationNankai UniversityTianjin 300071China Institute of Modern Optics Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network TechnologyNankai UniversityTianjin 300350China School of Life Science Shanxi UniversityTaiyuan 030006China1

A real-time label-free lateral offset spliced coreless fiber(CF)Mach-Zehnder interferometer(MZI)biosensor functionalized with hydrophobin Grifola frondosa I(HGFI)was proposed for the detection of cytokine tumour necrosis factor alpha(TNF-α).The nanolayer self-assembled on the optical fiber surfaces by HGFI rendered the immobilization of probe TNF-αantibody and recognition of antigen TNF-α.Trifluoroacetic acid was utilized to remove the HGFI layer from the glass surface,which was validated by field emission scanning electron microscopy(FESEM)and water contact angle(WCA).Results demonstrated that the processes of HGFI modification,antibody immobilization and specific antibody detection can be monitored in real *** proposed biosensor exhibited good specificity,repeatability and low detection limit for TNF-α,extending its application in inflammation and disease monitoring.

关键词： fiber interferometer offset

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Characteristic extraction of soliton dynamics based on convolutional autoencoder neural network

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Chinese Optics Letters 2023年第3期21卷 108-112页

作者：刘聪聪何江勇王攀邢登科李晋刘艳格王志 Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Institute of Modern OpticsNankai UniversityTianjin 300350China

In this article,we use a convolutional autoencoder neural network to reduce data dimensioning and rebuild soliton dynamics in a passively mode-locked fiber *** on the particle characteristic in double solitons and triple solitons interactions,we found that there is a strict correspondence between the number of minimum compression parameters and the number of independent parameters of soliton *** shows that our network effectively coarsens the high-dimensional data in nonlinear *** work not only introduces new prospects for the laser self-optimization algorithm,but also brings new insights into the modeling of nonlinear systems and description of soliton interactions.

关键词： fiber lasers optical solitons convolutional autoencoder neural network

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An on-line fiber cutting-welding method for the fabrication of Fabry-Perot micro-cavity

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optoelectronics Letters 2020年第4期16卷 248-251页

作者： WU Ji-xuan WANG Qian SONG Bin-bin CUI Guang-huan LIU Bo ZHANG Hao ZHANG Cheng ZHANG Shan-shan DUAN Shao-xiang BAI Hua Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems Tianjin Key Laboratory of Engineering Technologies for Cell PhamaceuticalCollege of Electronic and Information EngineeringTiangong UniversityTianjin 300387China Key Laboratory of Computer Vision and Systems Ministry of EducationSchool of Computer Science and EngineeringTianjin University of TechnologyTianjin 300384China Key Laboratory of Optoelectronic Sensor and Sensing Network Technology College of Electronic Information and Optical EngineeringNankai UniversityTianjin 300350China

A Fabry-Perot micro-cavity is fabricated by on-line fiber cutting-welding *** asymmetrical fiber Fabry-Perot micro-cavity is designed and produced by cutting a standard single-mode fiber and welding the fiber end with the core-offset *** length of the Fabry-Perot micro-cavity could be controlled within a certain range of accuracy based on the on-line fiber cutting-welding *** to this method,a micro-machined Fabry-Perot micro-cavity with a length of about 147μm is achieved and its spectral characteristic is also investigated in our *** proposed method is suitable to produce a micro-fiber-optic structure with improved and controlled precision,which is attractive for the fiber processing ***,the fabricated Fabry-Perot micro-cavity also has potential application in the microfluidic system and biochemical detection area.

关键词： fiber cavity welding

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Deep learning-based scattering removal of light field imaging

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Chinese Optics Letters 2022年第4期20卷 16-22页

作者： Weihao Wang Xing Zhao Zhixiang Jiang Ya Wen Institute of Modern Optics Nankai UniversityTianjin 300350China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Tianjin 300350China

Light field imaging has shown significance in research fields for its high-temporal-resolution 3D imaging ***,in scenes of light field imaging through scattering,such as biological imaging in vivo and imaging in fog,the quality of 3D reconstruction will be severely reduced due to the scattering of the light field *** this paper,we propose a deep learning-based method of scattering removal of light field *** this method,a neural network,trained by simulation samples that are generated by light field imaging forward models with and without scattering,is utilized to remove the effect of scattering on light fields captured *** the deblurred light field and the scattering-free forward model,3D reconstruction with high resolution and high contrast can be *** demonstrate the proposed method by using it to realize high-quality 3D reconstruction through a single scattering layer experimentally.

关键词： computational imaging light field imaging scattering imaging deep learning

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Co-electrolysis of ethylene glycol and carbon dioxide for formate synthesis

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Science China Chemistry 2024年第5期67卷 1539-1544页

作者： Dongfeng Du Fusong Kang Shiru Yang Bin Shao Jingshan Luo Institute of Photoelectronic Thin Film Devices and Technology State Key Laboratory of Photovoltaic Materials and CellsKey Laboratory of Photoelectronic Thin Film Devices and Technology of TianjinMinistry of Education Engineering Research Center of Thin Film Photoelectronic TechnologyNankai UniversityTianjin 300350China Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192China Frontiers Science Center for New Organic Matter Nankai UniversityTianjin 300071China College of Electronic Information and Optical Engineering Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network TechnologyNankai UniversityTianjin 300350China

Co-electrolysis of waste plastics and carbon dioxide(CO_(2)) into value-added chemicals or fuels is a promising pathway for a sustainable society, but efficient and selective conversion remains a challenge. Herein, a gold-mediated nickel hydroxide(Au/Ni(OH)_(2)) is developed to oxidize waste plastic-derived ethylene glycol(EG) into formate. In-situ electrochemical experiments and theoretical results reveal that the introduction of Au favors the redox properties and EG adsorption behavior of Ni(OH)_(2). The Au/Ni(OH)_(2) catalyst shows an excellent formate selectivity of >90% at high current densities of above 100 m A cm^(-2). When coupled with sputtered bismuth(Bi) cathode for CO_(2) reduction, a high formate Faradic efficiency(FE) of 188.2% at 200 m A cm^(-2)and a good formate productivity of 7.33 mmol m^(-2)s^(-1)at 10 A are obtained in a flow cell and a zero-gap membrane electrode assembly(MEA) cell, respectively. This work demonstrates a promising strategy to convert waste plastics and CO_(2) into valuable products.

关键词： waste plastic upcycling ethylene glycol oxidation carbon dioxide reduction electrocatalysis formate synthesis

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Whispering-gallery-mode tuning in a magnetic-fluid-infiltrated microbubble resonator based on laser-induced photo-thermal effect

Whispering-gallery-mode tuning in a magnetic-fluid-infiltrat...

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Asia-Pacific Optical sensors Conference, APOS 2016

作者： Li, Yuetao Zhang, Hao Liu, Bo Li, Yuhan Song, Binbin Key Laboratory of Optical Information Science and Technology Ministry of Education Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Institute of Modern Optics Nankai University Tianjin300071 China

A magnetic-fluids-infiltrated microbubble resonator is proposed and experimentally demonstrated. WGM tuning property of this microresonator under different pump laser power densities has been investigated, showing its... 详细信息

ISBN: (纸本)9780960038053

关键词： Pumping (laser)

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Adaptive Detection of Frequency-Hopping Spread Spectrum Signals Based on Compressed Measurements and Artificial Neural networks 5

Adaptive Detection of Frequency-Hopping Spread Spectrum Sign...

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5th IEEE Advanced Information technology, Electronic and Automation Control Conference, IAEAC 2021

作者： Huang, Yuang Meng, Xuedong Zhang, Shuang Liu, Feng Nankai University College of Electronic Information and Optical Engineering Tianjin China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Nankai University Tianjin China

In modern secure communications, the frequency-hopping spread spectrum (FHSS) technique has been widely implemented. In this technique, the signal carrier frequency hops in a pseudo-random manner, and the conventional non-cooperative receivers without the knowledge of the hopping sequence have to sample the signals with relatively expensive hardware to catch the entire spectrum. Thus, the FHSS signals usually get good performance against interception. In this paper, the authors propose a non-cooperative method to detect the FHSS signals from compressive measurements. In contrast to most of the existing literature on compressive sampling, which proposed to use random or recursively optimized measurement kernels, the proposed method enable efficient adaptive measurement kernel design based on task-specific information optimization and artificial neural networks. Simulation results demonstrate that the proposed method provides significantly improved detection accuracy over the compressive detection method with random kernels, as well as significantly improved measurement kernel designing efficiency over the recursive optimization method in the existing literature. © 2021 IEEE.

关键词： Neural networks

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