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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Bai, Bijie Wei, Heming Yang, Xilin Gan, Tianyi Mengu, Deniz Jarrahi, Mona Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los Angeles90095 United States Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai200444 China University of California Los AngelesCA United States

We present a framework for all-optical image encryption that is class-specific, performing a distinct image transformation function for each data class. Experimental validation of this method was conducted using both ... 详细信息

ISBN: (纸本)9781957171395

关键词： Optical depth

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Transmit Power Minimization for IRS-Assisted NOMA-UAV networks

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China communications 2024年第5期21卷 137-152页

作者： Zhao Chen Pang Xiaowei Tang Jie Liu Mingqian Zhao Nan Zhang Xiuyin Wang Xianbin School of Information and Communication Engineering Dalian University of TechnologyDalian 116024China School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510641China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China Department of Electrical and Computer Engineering Western UniversityLondonON N6A 5B9Canada

The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground *** reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific *** by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with *** to their distance to the UAV,the users are divided into the close users and remote *** UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received *** aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding ***,the problem is ***,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,*** propose an iterative algorithm to solve the two sub-problems *** results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.

关键词： intelligent reflecting surface nonorthogonal multiple access phase shift optimization transmit beamforming optimization unmanned aerial vehicle

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Glucose Sensing Utilizing Complex-Valued Neural networks 23

Glucose Sensing Utilizing Complex-Valued Neural Networks

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4th International Conference on Computing, networks and Internet of Things, CNIOT 2023

作者： Lv, Yiqi Meng, Xiang Luo, Yong Pei, Yan The Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University China and Jt. International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai China Doctoral Program Grad. Sch. of Comp. Science and Engineering Graduate Department of Computer and Information Systems University of Aizu Aizuwakamatsu Japan Computer Science Division University of Aizu Aizuwakamatsu Japan

ISBN: (纸本)9798400700705

This paper proposes a Complex-Valued Neural Network (CVNN) for glucose sensing in milli-meter wave (mmWave). Based on the propagation characteristics of millimeter wave in glucose medium, we obtain the S21 parameter of glucose with the concentration range of 0-300mg/dL in the 60-80 GHz frequency band by High Frequency Structure Simulator (HFSS) simulations. Then we combine the sensing model with a neural network to detect and predict the glucose concentration relying on the learning ability of the neural network. In the prediction of the concentration of unknown samples, the absolute error between the predicted value and the true value is within 5mg/dL, which confirms the ability of the proposed CVNN model. © 2023 ACM.

关键词： Millimeter waves

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GUEST EDITORIAL

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China communications 2023年第3期 4-6页

作者： Shanzhi Chen F.Richard Yu Weisong Shi Changle Li China Information and Communication Technology Group Co. Ltd.(CICT) State Key Laboratory of Wireless Mobile Communications SMIC IEEE VTS Mobile World newsletter IEEE Canadian Academy of Engineering(CAE) Engineering Institute of Canada(EIC) IET Department of Computer and Information Sciences at the University of Delaware(UD) State Key Laboratory of Integrated Services Networks of Xidian University

With the development of new generation of information and communication technology, the Internet of Vehicles(Io V)/Vehicle-to-Everything(V2X), which realizes the connection between vehicle and X(i.e., vehicles, pedestrians, infrastructures, clouds, etc.), is playing an increasingly important role in improving traffic operation efficiency and driving safety as well as enhancing the intelligence level of social traffic services.

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Towards an intelligent photonic system

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Science China(Information Sciences) 2020年第6期63卷 80-96页

作者： Weiwen ZOU Bowen MA Shaofu XU Xiuting ZOU Xingjun WANG State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center (iMLic) Department of Electronic EngineeringShanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University

The emerging intelligence technologies represented by deep learning have broadened their applications to various fields. Beyond the conventional electronics-based processing systems, the convergence of photonics and artificial intelligence(AI) technology enhances the performance and learning ability of AI. In this review, we propose the concept of an intelligent photonic system(IPS), illustrating it as a developing architecture with three different versions. For each version of IPS, we review several representative *** we discuss the challenges towards an IPS and provide some prospects for the future development.

关键词： intelligent photonic system deep learning artificial intelligence optical neural network neuromorphic photonics

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In-situ manipulation of wireless link with reinforcement-learningdriven programmable metasurface in indoor environment

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Journal of Information and Intelligence 2023年第3期1卷 217-227页

作者： Jiawen Xu Rong Zhang Jie Ma Hanting Zhao Lianlin Li School of Electronic Engineering and Computer Science Peking UniversityBeijing 100871China State Key Laboratory of Advanced Optical Communication Systems and Networks School of ElectronicsPeking UniversityBeijing 100871China

It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and ***,we have witnessed that programmable metasurface(PM)or reconfigurable intelligent surface(RIS)has become a key enabling technology for manipulating flexibly the wireless link;however,one fundamental but challenging issue is to online design the PM's control sequence in a complicated wireless environment,such as the real-world indoor ***,we propose a reinforcement learning(RL)approach to online control of the PM and thus in-situ improve the quality of the underline wireless *** designed an inexpensive one-bit PM working at around 2.442 GHz and developed associated RL algorithms,and demonstrated experimentally that it is capable of enhancing the quality of commodity wireless link by a factor of about 10 dB and beyond in multiple scenarios,even if the wireless transmitter is in the glancing angle of the PM in the realworld indoor ***,we also prove that our RL algorithm can be extended to improve the wireless signals of receivers in dual-receiver *** faithfully expect that the presented technique could hold important potentials in future wireless communication,smart homes,and many other fields.

关键词： Programmable metasurface Reconfigurable intelligent surface Reinforcement learning Wireless link

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A Six Components Seismic Detection Method Based on Rotation and Motion 13th

A Six Components Seismic Detection Method Based on Rotation ...

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13th International Field Exploration and Development Conference, IFEDC 2023

作者： Feng, Hai-Xin Li, You-Ming Si, Jie-Ge Li, Zheng-Bin Cao, Yu The 3rd Research Institute of CETC Beijing China Key Laboratory of Petroleum Resources Research Institute of Geology and Geophysics Chinese Academy of Sciences Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Institute of Acoustics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819704828

This paper is based on elastic wave propagation and six component seismic detection methods to detect underwater targets, which makes up for the shortcomings of traditional underwater acoustic passive detection methods that cannot effectively detect targets in near shallow water. The implementation of this article requires four steps: firstly, using a self-developed six component seismometer to collect seismic signals excited by the target;Secondly, screen out abnormal six component seismic signals;Step 3: Data preprocessing such as denoising and azimuth correction;Finally, the target direction finding is achieved by comprehensively utilizing rotational and translational seismic signals. Through multiple experiments, it can be concluded that: (1) using a six component seismic sensor can detect the six component seismic signal excited by the target, and the lower the detection frequency band, the easier it is to detect the low-frequency signal excited by the target;(2) It can be clearly observed in the time-frequency domain that moving targets have a close far passing characteristic;(3) The energy of the six component seismic signal has a certain proportional relationship with the target distance. The closer the target distance is, the greater the energy of the excited six component seismic signal;(4) Six component seismic signals can be used to achieve target detection and positioning. Compared to traditional seismic detection, six component seismic detection has a higher ability and is an important supplement to traditional underwater acoustic detection methods. This article first discovered that underwater moving targets not only generate seismic translational signals, but also contain low-frequency rotational seismic signals. The accurate direction finding of the target was achieved using the six component seismic direction finding method proposed for the first time in this article. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 20

关键词： Underwater acoustics

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Neighbor Load Rank Based Load Balancing Routing in LEO Satellite networks

Neighbor Load Rank Based Load Balancing Routing in LEO Satel...

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IEEE Conference on Global communications (GLOBECOM)

作者： Xueyu Lu Wenting Wei Kun Wang Liying Fu Chenxi Li Celimuge Wu State Key Laboratory of Integrated Service Networks Xidian University Xi’an China National Key Laboratory of Advanced Communication Networks Shijiazhuang China School of Computer Science and Technology Xidian University Xi’an China Graduate School of Informatics and Engineering University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The emerging space-terrestrial integrated networks (STIN) are envisioned to provide seamless connectivity for global coverage. As a promising key component for STIN, the Low Earth Orbiting (LEO) satellite network still faces significant technological challenges in routing for ensuring both reachability and efficiency, due to frequent topology changes and uneven load distribution. Load-balancing routing is a feasible solution to improve efficiency by alleviating regional overload, however, it may encounter either slow convergences or local perceptions. In this paper, we propose a Neighbor Load Rank (NLR) based load-balancing routing for LEO satellite networks, where potential congestion at the queue buffer of a satellite node is characterized by load scores of its neighboring satellites, so as to reduce the perspective limitation of local load-balancing routing. To accelerate routing convergence and reduce computational complexity, we design region delineation, boundary penalty and directional incentive strategies to obtain the approximate minimum hop count path. Meanwhile, we employ the topology-stabilizing model (TSM) to convert the frequent satellite-ground interconnection changes into traffic fluctuations. Simulations demonstrate that NLR can maintain low-latency capacity with lower transmission overhead and effectively balance the overloaded traffic.

关键词： Satellites Network topology Computational modeling Simulation Low earth orbit satellites Routing Load management Topology Load modeling Propagation delay

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Coalition game-based clustering algorithm for LEO satellite networks

Coalition game-based clustering algorithm for LEO satellite ...

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IEEE Conference on Global communications (GLOBECOM)

作者： Peixin Zhang Wenting Wei Kun Wang Lizhe Liu Liang Qin Celimuge Wu State Key Laboratory of Integrated Service Networks Xidian University Xi’an China National Key Laboratory of Advanced Communication Networks Shijiazhuang China School of Computer Science and Technology Xidian University Xian China Graduate School of Informatics and Engineering University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Low Earth Orbit (LEO) satellites are gradually developing towards to a large scale, in order to achieve a desired vision of ubiquitous connectivity and broadband access at anytime and anywhere. However, the increasing scale and highly dynamic nature of LEO constellation pose challenges to network management on its flexibility and scalability. Clustering is introduced as an effective approach to manage LEO satellite networks in a flexible manner. Unfortunately, satellite clusters encounter instability and high communication load due to frequent topology changes and traffic growth. In this paper, we design LEO satellites clustering models that jointly optimize cluster reliability and network communication load in the GEO/LEO network architecture. The coalition game framework is introduced to obtain a stable cluster structure by adopting an automated and centralized approach. A coalition formation algorithm based on the optimization of reliability and communication load is developed for the clustering problem. Finally, numerical simulations are carried out to evaluate the superiority and effectiveness of the proposed grouping and clustering scheme.

关键词： Satellites Heuristic algorithms Low earth orbit satellites Clustering algorithms Games Reliability engineering Throughput Topology Delays Optimization

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Optical coherent dot-product chip for sophisticated deep learning regression

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Light(Science & Applications) 2021年第12期10卷 2330-2341页

作者： Shaofu Xu Jing Wang Haowen Shu Zhike Zhang Sicheng Yi Bowen Bai Xingjun Wang Jianguo Liu 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 University800 Dongchuan RoadShanghai 200240China State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Institution of Semiconductors Chinese Academy of SciencesBeijing 100083China

Optical implementations of neural networks(ONNs)herald the next-generation high-speed and energy-efficient deep learning computing by harnessing the technical advantages of large bandwidth and high parallelism of ***,due to the problems of the incomplete numerical domain,limited hardware scale,or inadequate numerical accuracy,the majority of existing ONNs were studied for basic classification *** that regression is a fundamental form of deep learning and accounts for a large part of current artificial intelligence applications,it is necessary to master deep learning regression for further development and deployment of ***,we demonstrate a silicon-based optical coherent dot-product chip(OCDC)capable of completing deep learning regression *** OCDC adopts optical fields to carry out operations in the complete real-value domain instead of in only the positive *** reusing,a single chip conducts matrix multiplications and convolutions in neural networks of any ***,hardware deviations are compensated via in-situ backpropagation control provided the simplicity of chip ***,the OCDC meets the requirements for sophisticated regression tasks and we successfully demonstrate a representative neural network,the AUTOMAP(a cutting-edge neural network model for image reconstruction).The quality of reconstructed images by the OCDC and a 32-bit digital computer is *** the best of our knowledge,there is no precedent of performing such state-of-the-art regression tasks on ONN *** is anticipated that the OCDC can promote the novel accomplishment of ONNs in modern AI applications including autonomous driving,natural language processing,and scientific study.

关键词： neural hardware coherent

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