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Deterministic and Stochastic Simulators for Non-Isotropic V2V-MIMO Wideband Channels

China Communications 2018年第7期15卷 18-29页

作者： Yiran Li Xiang Cheng Nan Zhang State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Wireless Algorithm Department Product Research and Development System ZTE Corporation

In this paper, we consider a novel two-dimensional(2D) geometry-based stochastic model(GBSM) for multiple-input multiple-output(MIMO) vehicle-to-vehicle(V2V) wideband fading channels. The proposed model employs the combination of a two-ring model and a multiple confocal ellipses model, where the signal is sum of the line-of-sight(Lo S) component, single-bounced(SB) rays, and double-bounced(DB) rays. Based on the reference model, we derive some expressions of channel statistical properties, including space-time correlation function(STCF), Doppler spectral power density(DPSD), envelope level crossing rate(LCR) and average fade duration(AFD). In addition, corresponding deterministic and stochastic simulation models are developed based on the reference model. Moreover, we compare the statistical properties of the reference model and the two simulation models in different scenarios and investigate the impact of different vehicular traffic densities(VTDs) on the channel statistical properties of the proposed model. Finally, the great agreement between simulation models and the reference model demonstrates not only the utility of simulation models, but also the correctness of theoretical derivations and simulations.

关键词： vehicle-to-vehicle wideband channels simulation model statistical properties

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High-specific-power flexible transition metal dichalcogenide solar cells

arXiv

引用

arXiv 2021年

作者： Nazif, Koosha Nassiri Daus, Alwin Hong, Jiho Lee, Nayeun Vaziri, Sam Kumar, Aravindh Nitta, Frederick Chen, Michelle Kananian, Siavash Islam, Raisul Kim, Kwan-Ho Park, Jin-Hong Poon, Ada Brongersma, Mark L. Pop, Eric Saraswat, Krishna C. Dept. of Electrical Engineering Stanford University StanfordCA94305 United States Geballe Laboratory for Advanced Materials Stanford University StanfordCA94305 United States Dept. of Materials Science and Engineering Stanford University StanfordCA94305 United States Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Dept. of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Sungkyunkwan University Suwon16419 Korea Republic of Dept. of Applied Physics Stanford University StanfordCA94305 United States

Semiconducting transition metal dichalcogenides (TMDs) are promising for flexible high-specific-power photovoltaics due to their ultrahigh optical absorption coefficients, desirable band gaps and self-passivated surfaces. However, challenges such as Fermi-level pinning at the metal contact-TMD interface and the inapplicability of traditional doping schemes have prevented most TMD solar cells from exceeding 2% power conversion efficiency (PCE). In addition, fabrication on flexible substrates tends to contaminate or damage TMD interfaces, further reducing performance. Here, we address these fundamental issues by employing: 1) transparent graphene contacts to mitigate Fermi-level pinning, 2) MoOx capping for doping, passivation and anti-reflection, and 3) a clean, non-damaging direct transfer method to realize devices on lightweight flexible polyimide substrates. These lead to record PCE of 5.1% and record specific power of 4.4 W g-1 for flexible TMD (WSe2) solar cells, the latter on par with prevailing thin-film solar technologies cadmium telluride, copper indium gallium selenide, amorphous silicon and III-Vs. We further project that TMD solar cells could achieve specific power up to 46 W g-1, creating unprecedented opportunities in a broad range of industries from aerospace to wearable and implantable electronics. Copyright © 2021, The Authors. All rights reserved.

关键词： Transition metals

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Hardware-aware in situ Boltzmann machine learning using stochastic magnetic tunnel junctions

arXiv

引用

arXiv 2021年

作者： Kaiser, Jan Borders, William A. Camsari, Kerem Y. Fukami, Shunsuke Ohno, Hideo Datta, Supriyo Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47906 United States Laboratory for Nanoelectronics and Spintronics Research Institute of Electrical Communication Tohoku University Sendai Japan Department of Electrical and Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Center for Innovative Integrated Electronic Systems Tohoku University Sendai Japan Center for Spintronics Research Network Tohoku University Sendai Japan Center for Science and Innovation in Spintronics Tohoku University Sendai Japan WPI-Advanced Institute for Materials Research Tohoku University Sendai Japan

One of the big challenges of current electronics is the design and implementation of hardware neural networks that perform fast and energy-efficient machine learning. Spintronics is a promising catalyst for this field with the capabilities of nanosecond operation and compatibility with existing microelectronics. Considering large-scale, viable neuromorphic systems however, variability of device properties is a serious concern. In this paper, we show an autonomously operating circuit that performs hardware-aware machine learning utilizing probabilistic neurons built with stochastic magnetic tunnel junctions. We show that in situ learning of weights and biases in a Boltzmann machine can counter device-to-device variations and learn the probability distribution of meaningful operations such as a full adder. This scalable autonomously operating learning circuit using spintronics-based neurons could be especially of interest for standalone artificial-intelligence devices capable of fast and efficient learning at the edge. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

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Was Wuhan the early epicenter of the COVID-19 pandemic?——a critique

引用

National Science Review 2023年第4期10卷 19-21页

作者： Yanan Cao Lingling Chen Hua Chen Yupeng Cun Xiaofeng Dai Hongli Du Feng Gao Fengbiao Guo Yalong Guo Pei Hao Shunmin He Shunping He XiongLei He Zheng Hu Boon-Peng Hoh Xin Jin Qian Jiang Qinghua Jiang Asifullah Khan Hong-Zhi Kong Jinchen Li Shuai Cheng Li Ying Li Qiang Lin Jianquan Liu Qi Liu Jian Lu Xuemei Lu Shujin Luo Qinghua Nie Zilong Qiu Tieliu Shi Xiaofeng Song Jianzhong Su Sheng-ce Tao Chaolong Wang Chuan-Chao Wang Guo-Dong Wang Jiguang Wang Qi Wu Shaoyuan Wu Shuhua Xu Yu Xue Wenjun Yang Zhaohui Yang Kai Ye Yuan-Nong Ye Li Yu Fangqing Zhao Yiqiang Zhao Weiwei Zhai Dandan Zhang Liye Zhang Houfeng Zheng Qi Zhou Tianqi Zhu Ya-ping Zhang Ruijin Hospital Shanghai Jiao Tong University College of Life Science and Technology Guangxi University Beijing Institute of Genomics Chinese Academy of Sciences Children's Hospital of Chongqing Medical University Wuxi School of Medicine Jiangnan University School of Biology and Biological Engineering South China University of Technology Department of Physics School of ScienceTianjin University School of Pharmaceutical Sciences Wuhan University Institute of Botany Chinese Academy of Sciences Institut Pasteur of Shanghai Chinese Academy of Sciences Institute of Biophysics Chinese Academy of Sciences Institute of Hydrobiology Chinese Academy of Sciences School of Life Sciences Sun Yat-sen University Institute of Synthetic Biology Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Faculty of Medicine and Health Sciences University College Sedaya International School of Medicine South China University of Technology Department of Medical Genetics Capital Institute of Pediatrics School of Life Science and Technology Harbin Institute of Technology Department of Biochemistry Abdul Wali Khan University Xiangya Hospital Central South University Department of Computer Science City University of Hong Kong College of Life Science and Technology Foshan University South China Sea Institute of Oceanology Chinese Academy of Sciences College of Ecology Lanzhou University School of Life Sciences and Technology Tongji University School of Life Sciences Peking University Kunming Institute of Zoology Chinese Academy of Sciences College of Animal Science South China Agricultural University Institute of Neuroscience Chinese Academy of Sciences School of Life Sciences East China Normal University Nanjing University of Aeronautics and Astronautics Wenzhou Institute University of Chinese Academy of Sciences Institute of Systems Biomedicine Shanghai Jiao Tong University Tongji Medical College Huazhong University of Science and Technology School of Life Sciences Xiamen University Division of Life Science and Department of

Recently, Worobey et al.(2022) published a report entitled ‘The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic' that succinctly summarizes their study [1]. A pre-print version of this study had earlier elicited a series of highprofile media coverages [2,3]. All these reports deliver a social-political message that the Huanan market is the epicenter of COVID-19.

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Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

引用

computers, Materials & Continua 2019年第9期61卷 1117-1128页

作者： Xuting Duan Jingyi Wei Daxin Tian Jianshan Zhou Haiying Xia Xin Li Kunxian Zheng Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&SafetyControl Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry Transport Beijing100088China Department of Computer Science and Technology Tsinghua UniversityHaidian DistrictBeijing100088China

In vehicle ad-hoc networks(VANETs),the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes *** by the self-adaptive paradigm of cellular attractors,this paper regards an individual communication as a cell,so that we can apply the revised attractor selection model to induce each connected *** at improving the Quality of Service(QoS),we presented the bio-inspired handover decision-making *** addition,we employ the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)for any vehicle to choose an access *** paper proposes a novel framework where the bio-inspired mechanism is combined with *** a dynamic and random mobility environment,our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global *** experimental results confirm that the proposed method performs better when compared with conventional schemes.

关键词： Revised attraction selection model TOPSIS VANETs QoS

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An Ultra-compact Broadband TE-pass Nanofocusing Structure

An Ultra-compact Broadband TE-pass Nanofocusing Structure

引用

Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Kejian Zhu Xu Pengfei Pengfei Sun Xingpeng Liu Haiou Li Zhiping Zhou Nano-optoelectronics Frontier Center of Ministry of Education Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin China

We propose a broadband structure which integrates polarization and nanofocusing functions into a single device with 3.8x4 μm 2 footprint. The bandwidth is over 200 nm with insert loss (IL) smaller than 1.68 dB. ... 详细信息

ISBN: (数字)9781943580828

ISBN: (纸本)9781728176567

关键词： Bandwidth Nanoscale devices Optical fiber communication Broadband communication System-on-chip Photonics Periodic structures

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A few-shot learning graph multi-trajectory evolution network for forecasting multimodal baby connectivity development from a baseline timepoint

arXiv

引用

arXiv 2021年

作者： Bessadok, Alaa Nebli, Ahmed Mahjoub, Mohamed Ali Li, Gang Lin, Weili Shen, Dinggang Rekik, Islem BASIRA Lab Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey Higher Institute of Informatics and Communication Technologies University of Sousse 4011 Tunisia National Engineering School of Sousse University of Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Mannouba Tunisia Department of Radiology and BRIC University of North Carolina Chapel HillNC United States School of Biomedical Engineering ShanghaiTech University Shanghai China Department of Research and Development United Imaging Intelligence Co. Ltd. Shanghai China

Charting the baby connectome evolution trajectory during the first year after birth plays a vital role in understanding dynamic connectivity development of baby brains. Such analysis requires acquisition of longitudinal connectomic datasets. However, both neonatal and postnatal scans are rarely acquired due to various difficulties. A small body of works has focused on predicting baby brain evolution trajectory from a neonatal brain connectome derived from a single modality. Although promising, large training datasets are essential to boost model learning and to generalize to a multi-trajectory prediction from different modalities (i.e., functional and morphological connectomes). Here, we unprecedentedly explore the question: "Can we design a few-shot learning-based framework for predicting brain graph trajectories across different modalities?" To this aim, we propose a Graph Multi-Trajectory Evolution Network (GmTE-Net), which adopts a teacher-student paradigm where the teacher network learns on pure neonatal brain graphs and the student network learns on simulated brain graphs given a set of different timepoints. To the best of our knowledge, this is the first teacher-student architecture tailored for brain graph multi-trajectory growth prediction that is based on few-shot learning and generalized to graph neural networks (GNNs). To boost the performance of the student network, we introduce a local topology-aware distillation loss that forces the predicted graph topology of the student network to be consistent with the teacher network. Experimental results demonstrate substantial performance gains over benchmark methods. Hence, our GmTE-Net can be leveraged to predict atypical brain connectivity trajectory evolution across various modalities. Our code is available at https://***/basiralab/GmTE-Net. © 2021, CC BY-NC-ND.

关键词： Trajectories

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Reducing motion blur in ghost imaging with Hessian enhancement filter

Reducing motion blur in ghost imaging with Hessian enhanceme...

引用

Computational Optical Sensing and Imaging, COSI 2019

作者： Chang, Chen Yang, Dongyue Li, Junhui Wu, Guohua Luo, Bin Yin, Longfei Guo, Hong School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing100876 China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Center for Quantum Information Technology Peking University Beijing100871 China

In ghost imaging with pseudo-thermal light, Hessian enhancement filter is applied in reference measurements to improve the image quality by reducing the motion blur caused by improper exposure settings at short cohere... 详细信息

ISBN: (纸本)9781943580637

关键词： Image enhancement

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Selective excitation of a three-dimensionally oriented single plasmonic dipole

引用

Photonics Research 2019年第6期7卷 693-698页

作者： FAJUN XIAO GUANGLIN WANG XUETAO GAN WUYUN SHANG SHIYIN CAO WEIREN ZHU TING MEI MALIN PREMARATNE JIANLIN ZHAO MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions and Shaanxi Key Laboratory of Optical Information Technology School of Science Northwestern Polytechnical University Xi'an 710129 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai 200240 China Advanced Computing and Simulation Laboratory (AXL) Department of Electrical and Computer Systems Engineering Monash University Clayton VIC 3800 Australia

We experimentally demonstrate a scheme to deterministically excite a three-dimensionally oriented electric dipole in a single Au nanosphere by using a tightly focused radially polarized beam whose focal field possesses polarization states along three-dimensional(3D) orientations owing to the spatial overlap between longitudinal and radial electric field components. Experiment observations indicate that the orientation of an excited dipole moment gradually changes from out-of-plane to in-plane when the nanosphere is moved away from the beam center, which is reconfirmed by full-wave simulations. Moreover, rigorous calculation based on Mie theory reveals that a reduced effective ambient permittivity accompanies the rotation of the dipole moment, leading to a blue-shifted and narrowed resonance peak. We envision that our results could find applications in detecting the 3D orientation of isolated molecules and benefit the fine manipulation of light–matter interactions at the single-molecule level.

关键词： Selective excitation plasmonic dipole

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100 kHz SiC-MOSFET SAPF with Simple PI Regulator for Selective Harmonic Suppression

100 kHz SiC-MOSFET SAPF with Simple PI Regulator for Selecti...

引用

International Conference on Power Electronics and Motion Control (IPEMC)

作者： Hongwei Xu Ke Dai Yuxiao Zhang Haitao Lin Ying He Bingyuan Yang Ziwei Dai Weiping Zhang State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan China Computer and Systems Engineering Rensselaer Polytechnic Institute Troy USA Hubei Surpass Sun Electric Company Ltd Xiangyang China

ISBN: (数字)9781728153018

ISBN: (纸本)9781728153025

This paper presents a 100 kHz switching frequency shunt active power filter (SAPF), which is based on SiC-MOSFET and DSP TMS320F28377D. Compared to the mostly about 10kHz switching frequency SAPF, 100kHz switching frequency makes it easy to design the current loop controller and achieve higher control bandwidth. By adopting the simple PI regulator to design the current loop, appropriate parameters of PI regulator and current loop bandwidth are given. Recursive discrete Fourier transform (RDFT) is used to extract harmonics selectively. By analyzing the relationship between different switching frequencies and harmonic extraction accuracy, harmonic suppression characteristics are improved at 100 kHz switching frequency. Meanwhile, due to the use of SiC-MOSFET, SAPF can operate stably with a low loss. A 10kVA prototype using CREE SiC power module CCS050M12CM2 is set up to verify the validity of the design method.

关键词： Harmonics suppression Regulators Silicon carbide Switching frequency Prototypes Bandwidth Control systems

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