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Analog spatiotemporal feature extraction for cognitive radio-frequency sensing with integrated photonics

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Light(Science & Applications) 2024年第3期13卷 478-487页

作者： Shaofu Xu Binshuo Liu Sicheng Yi Jing Wang Weiwen Zou State Key Laboratory of Advanced Optical communication systems and networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina

Analog feature extraction(AFE)is an appealing strategy for low-latency and efficient cognitive sensing systems since key features are much sparser than the Nyquist-sampled ***,applying AFE to broadband radio-frequency(RF)scenarios is challenging due to the bandwidth and programmability bottlenecks of analog electronic ***,we introduce a photonics-based scheme that extracts spatiotemporal features from broadband RF signals in the analog *** feature extractor structure inspired by convolutional neural networks is implemented on integrated photonic circuits to process RF signals from multiple antennas,extracting valid features from both temporal and spatial *** of the tunability of the photonic devices,the photonic spatiotemporal feature extractor is trainable,which enhances the validity of the extracted ***,a digital-analog-hybrid transfer learning method is proposed for the effective and low-cost training of the photonic feature *** validate our scheme,we demonstrate a radar target recognition task with a 4-GHz instantaneous *** results indicate that the photonic analog feature extractor tackles broadband RF signals and reduces the sampling rate of analog-to-digital converters to 1/4 of the Nyquist sampling while maintaining a high target recognition accuracy of 97.5%.Our scheme offers a promising path for exploiting the AFE strategy in the realm of cognitive RF sensing,with the potential to contribute to the efficient signal processing involved in applications such as autonomous driving,robotics,and smart factories.

关键词： scheme driving smart

Integrated optical frequency transfer and optical physical layer key distribution with enhanced link reciprocity detection

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Science China(Information Sciences) 2024年第7期67卷 335-336页

作者： Kunfeng XIE Liang HU Jianping CHEN Guiling WU State Key Laboratory of Advanced Optical communication System and networks Department of Electronic EngineeringShanghai Jiao Tong University

Optical fiber transmission has been widely used in communications and metrology, wherein optical frequency transfer (OFT) and optical physical layer secure key distribution (OKD) have become research hotspots [1, 2]. Moreover,OFT can perform a comparison between state-of-the-art optical atomic clocks and implement coherent optical phase transfer over long distances to support geodesy [1, 3].

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Digital twin modeling and controlling of optical power evolution enabling autonomous-driving optical networks: a Bayesian approach

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Advanced Photonics 2024年第2期6卷 69-80页

作者： Xiaomin Liu Yihao Zhang Yuli Chen Yichen Liu Meng Cai Qizhi Qiu Mengfan Fu Lilin Yi Weisheng Hu Qunbi Zhuge Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and NetworksDepartment of Electronic Engineering

Optical networks are evolving toward ultrawide bandwidth and autonomous operation. In this scenario, it is crucial to accurately model and control optical power evolutions(OPEs) through optical amplifiers(OAs), as they directly affect the signal-to-noise ratio and fiber nonlinearities. However, a fundamental contradiction arises between the complex physical phenomena in optical transmission and the required precision in network control. Traditional theoretical methods underperform due to ideal assumptions, while data-driven approaches entail exorbitant costs associated with acquiring massive amounts of data to achieve the desired level of accuracy. In this work, we propose a Bayesian inference framework(BIF) to construct the digital twin of OAs and control OPE in a data-efficient manner. Only the informative data are collected to balance the exploration and exploitation of the data space, thus enabling efficient autonomous-driving optical networks(ADONs). Simulations and experiments demonstrate that the BIF can reduce the data size for modeling erbium-doped fiber amplifiers by 80% and Raman amplifiers by 60%. Within 30 iterations, the optimal controlling performance can be achieved to realize target signal/gain profiles in links with different types of OAs. The results show that the BIF paves the way to accurately model and control OPE for future ADONs.

关键词： optical fiber communications digital twin Bayesian inference optical amplifiers autonomous-driving optical networks

Broadband and fabrication-tolerant 3-dB couplers with topological valley edge modes

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Light(Science & Applications) 2024年第8期13卷 1623-1630页

作者： Guo-Jing Tang Xiao-Dong Chen Lu Sun Chao-Heng Guo Meng-Yu Li Zhong-Tao Tian Hou-Hong Chen Hong-Wei Wang Qi-Yao Sun Ying-Di Pan Xin-Tao He Yi-Kai Su Jian-Wen Dong School of Physics&State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen UniversityGuangzhou 510275China State Key Laboratory of Advanced Optical communication systems and networks Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

3-dB couplers,which are commonly used in photonic integrated circuits for on-chip information processing,precision measurement,and quantum computing,face challenges in achieving robust performance due to their limited 3-dB bandwidths and sensitivity to fabrication *** address this,we introduce topological physics to nanophotonics,developing a framework for topological 3-dB *** couplers exhibit broad working wavelength range and robustness against fabrication dimensional *** leveraging valley-Hall topology and mirror symmetry,the photonic-crystal-slab couplers achieve ideal 3-dB splitting characterized by a wavelength-insensitive scattering *** analysis confirms the superiority on broad bandwidth of 48 nm and robust splitting against dimensional errors of 20 *** further propose a topological interferometer for on-chip distance measurement,which also exhibits robustness against dimensional *** extension of topological principles to the fields of interferometers,may open up new possibilities for constructing robust wavelength division multiplexing,temperature-drift-insensitive sensing,and optical coherence tomography applications.

关键词： topological splitting insensitive

Low-modal-crosstalk doped-fiber amplifiers in few-mode-fiber-based systems

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Photonics Research 2024年第8期12卷 1768-1775页

作者： SHUAILUO HUANG LEI SHEN GANG QIAO YUANPENG DING YUYANG GAO JIAN CUI BAOLONG ZHU SIYUAN LIU MINGQING ZUO JINGLONG ZHU LEI ZHANG JIE LUO YONGQI HE ZHANGYUAN CHEN JUHAO LI State Key Laboratory of Advanced Optical communication systems and networks Peking UniversityBeijing 100871China State Key Laboratory of Optical Fiber and Cable Manufacture Technology Yangtze Optical Fibre and Cable Joint Stock Limited CompanyWuhan 430073China School of Computer and communication Engineering University of Science and Technology BeijingBeijing 100083China department of networks China Mobile Communications Group Co.Ltd.Beijing 100033China department of Fundamental Network Technology China Mobile Research InstituteBeijing 100053China Pengcheng Laboratory Shenzhen 518055China

Independent light propagation through one or multiple modes is commonly considered as a basic demand for mode manipulation in few-mode fiber(FMF)-or multimode fiber(MMF)-based optical systems such as transmission links,optical fiber lasers,or distributed optical fiber ***,the insertion of doped-fiber amplifiers always kills the entire effort by inducing significant modal *** this paper,we propose the design of doped-fiber amplifiers in FMF-based systems adopting identical multiple-ring-core(MRC)index profiles for both passive and doped fibers to achieve low modal *** develop the direct-glass-transition(DGT)modified chemical vapor deposition(MCVD)processing for precise fabrication of few-mode erbium-doped fibers(FM-EDFs)with MRC profiles of both refractive index and erbium-ion doping ***,a few-mode erbium-doped-fiber amplifier(FM-EDFA)with a maximum gain of 26.08 dB and differential modal gain(DMG)of 2.3 dB is realized based on fabricated FM-EDF matched with a transmission FMF supporting four linearly polarized(LP)*** the insertion of the FM-EDFA,60+60 km simultaneous LP_(01)∕LP_(11)∕LP_(21)∕LP_(02)transmission without inter-modal multiple-input multiple-output digital signal processing(MIMO-DSP)is successfully *** proposed design of low-modal-crosstalk doped-fiber amplifiers provides,to our knowledge,new insights into mode manipulation methods in various applications.

关键词： fiber crosstalk amplifiers

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AI/ML Enabled Automation System for Software Defined Disaggregated Open radio Access networks:Transforming Telecommunication Business

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Big Data Mining and Analytics 2024年第2期7卷 271-293页

作者： Sunil Kumar Institute for communication systems University of SurreyGuildfordGU27XHUK

Open Air Interface(OAI)alliance recently introduced a new disaggregated Open radio Access networks(O-RAN)framework for next generation telecommunications and *** disaggregated architecture is open,automated,software defined,virtual,and supports the latest advanced technologies like Artificial Intelligence(AI)Machine Learning(AI/ML).This novel intelligent architecture enables programmers to design and customize automated applications according to the business needs and to improve quality of service in fifth generation(5G)and Beyond 5G(B5G).Its disaggregated and multivendor nature gives the opportunity to new startups and small vendors to participate and provide cheap hardware software solutions to keep the market *** paper presents the disaggregated and programmable O-RAN architecture focused on automation,AI/ML services,and applications with Flexible radio access network Intelligent Controller(FRIC).We schematically demonstrate the reinforcement learning,external applications(xApps),and automation steps to implement this disaggregated O-RAN *** idea of this research paper is to implement an AI/ML enabled automation system for software defined disaggregated O-RAN,which monitors,manages,and performs AI/ML-related services,including the model deployment,optimization,inference,and training.

关键词： Artificial Intelligence(AI) Reinforcement Learning(RL) Open radio Access networks(O-RAN) Flexible radio access network Intelligent Controller(FRIC) external Applications(xApps) Machine Learning(ML),sixth generation(6G)

A Distributed Self-Tallying Electronic Voting System Using the Smart Contract

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Chinese Journal of Electronics 2024年第4期33卷 1063-1076页

作者： Jingyu YAO Bo YANG Tao WANG Wenzheng ZHANG School of Computer Science Shaanxi Normal University State Key Laboratory of Integrated Services networks Xidian University Science and Technology on communication Security Laboratory

For electronic voting(e-voting) with a trusted authority, the ballots may be discarded or tampered, so it is attractive to eliminate the dependence on the trusted party. An e-voting protocol, where the final voting result can be calculated by any entity, is known as self-tallying e-voting protocol. To the best of our knowledge, addressing both abortive issue and adaptive issue simultaneously is still an open problem in self-tallying e-voting *** Ethereum blockchain with cryptographic technologies, we present a decentralized self-tallying e-voting protocol. We solve the above problem efficiently by utilizing optimized Group Encryption Scheme and standard Exponential El Gamal Cryptosystem. We use zero-knowledge proof and homomorphic encryption to protect votes' secrecy and achieve self-tallying. All ballots can be verified by anyone and the final voting result can be calculated by any entity. In addition, using the paradigm of score voting and “1-out-of-k” proof, our e-voting system is suitable for a wide range of application scenarios. Experiments show that our protocol is more competitive and more suitable for large-scale voting.

关键词： Electronic voting systems Smart contracts Blockchains Cryptocurrency Electronic voting Homomorphic encryption Standards

Time and Space Efficient Multi-Model Convolution Vision Transformer for Tomato Disease Detection from Leaf Images with Varied Backgrounds

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Computers, Materials & Continua 2024年第4期79卷 117-142页

作者： Ankita Gangwar Vijaypal Singh Dhaka Geeta Rani Shrey Khandelwal Ester Zumpano Eugenio Vocaturo department of Computer and communication Engineering Manipal University JaipurJaipurIndia department of IoT and Intelligent systems Manipal University JaipurJaipurIndia department of Computer Engineering ModellingElectronics and Systems(DIMES)University of CalabriaRende(Cosenza)Italy National Research Council Institute of Nanotechnology(NANOTEC)Rende(Cosenza)Italy

A consumption of 46.9 million tons of processed tomatoes was reported in 2022 which is merely 20%of the total *** increase of 3.3%in consumption is predicted from 2024 to *** are also rich in iron,potassium,antioxidant lycopene,vitamins A,C and K which are important for preventing cancer,and maintaining blood pressure and glucose ***,tomatoes are globally important due to their widespread usage and nutritional *** face the high demand for tomatoes,it is mandatory to investigate the causes of crop loss and minimize *** are one of the major causes that adversely affect crop yield and degrade the quality of the tomato *** leads to financial losses and affects the livelihood of ***,automatic disease detection at any stage of the tomato plant is a critical *** learning models introduced in the literature show promising results,but the models are difficult to implement on handheld devices such as mobile phones due to high computational costs and a large number of ***,most of the models proposed so far work efficiently for images with plain backgrounds where a clear demarcation exists between the background and leaf ***,the existing techniques lack in recognizing multiple diseases on the same *** address these concerns,we introduce a customized deep learning-based convolution vision transformer *** achieves an accuracy of 93.51%for classifying tomato leaf images with plain as well as complex backgrounds into 13 *** requires a space storage of merely 5.8 MB which is 98.93%,98.33%,and 92.64%less than stateof-the-art visual geometry group,vision transformers,and convolution vision transformermodels,*** training time of 44 min is 51.12%,74.12%,and 57.7%lower than the above-mentioned ***,it can be deployed on(Internet of Things)IoT-enabled devices,drones,or mobile devices to assist farmers in the real-time monitoring of tomato *** p

关键词： Tomato disease transformer deep learning mobile devices

Survey of Indoor Localization Based on Deep Learning

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Computers, Materials & Continua 2024年第5期79卷 3261-3298页

作者： Khaldon Azzam Kordi Mardeni Roslee Mohamad Yusoff Alias Abdulraqeb Alhammadi Athar Waseem Anwar Faizd Osman Centre for Wireless Technology Faculty of EngineeringMultimedia UniversityCyberjaya63100Malaysia communication systems&networks Research Lab Malaysia-Japan International Institute of TechnologyUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia department of Electrical Engineering(DEE) International Islamic UniversityIslamabad44000Pakistan Rohde&Schwarz(M)Sdn Bhd Shah Alam40150Malaysia

This study comprehensively examines the current state of deep learning (DL) usage in indoor *** emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing *** deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

关键词： Deep learning indoor localization wireless-based localization