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A Positioning Method and Realization on Single Satellites in Different Orbits Using TDOA

China Communications 2023年第7期20卷 108-121页

作者： Laiding Zhao Xun Zhu Gengxin Zhang Zhaowen Wang College of Telecommunications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China “Telecommunication and Network”National Engineering Research Center Nanjing University of Posts and TelecommunicationsNanjing 210003China Shanghai Aerospace Electronic Technology Institute Shanghai 201109China

The main geolocation technology currently used in COSPAS-SARSAT system is TDOA/FDOA or three-star TDOA,the principle is to determine the location of the signal source by using the difference in arrival time and frequency of the wireless signal between different ***,ground monitoring stations need to be equipped with more than two antenna receiving stations,and multiple satellites should be able to simultaneously relay the distress signal from the target source in order to achieve the geolocation ***,when the ground receiving system has only one antenna receiving station,or the target source is in a heavily obscured environment,the ground side is unable to receive the forwarded signals from multiple satellites at the same time,which will make it impossible to *** address these problems,in this paper,a time-sharing single satellite geolocations method based on different orbits is proposed for the first *** method uses one or several low-earth orbit satellites(LEO)and mediumearth orbit satellites(MEO)in the visible area,and the receiving station only needs one pair of receiving antennas to complete the *** can effectively compensate for the shortcomings of the traditional TDOA using the same moment and have better positioning accuracy compared with the single satellite in the same *** to the limited experimental conditions,this paper tests the navigation satellite using different orbit time-sharing single satellite geolocations,and proves that the positioning method has high positioning accuracy and has certain promotion and application value.

关键词： different orbit time-sharing non-convex optimization single satellite TDOA

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Stochastic Dynamic Modeling of Rain Attenuation: A Survey

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China Communications 2018年第3期15卷 220-235页

作者： Zhicheng Qu Gengxin Zhang Haotong Cao Jidong Xie College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Satellite & Mobile communication Section Nanjing University of Posts and Telecommunications National Local Joint Engineering Research Center for communication and network technology Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technique of Ministry of Education Nanjing University of Posts and Telecommunications

Satellite communication systems(SCS) operating on frequency bands above 10 GHz are sensitive to atmosphere physical phenomena, especially rain attenuation. To evaluate impairments in satellite performance, stochastic dynamic modeling(SDM) is considered as an effective way to predict real-time satellite channel fading caused by rain. This article carries out a survey of SDM using stochastic differential equations(SDEs) currently in the literature. Special attention is given to the different input characteristics of each model to satisfy specific local conditions. Future research directions in SDM are also suggested in this paper.

关键词： stochastic dynamic modeling rainattenuation time-series synthesizer satellitecommunication satellite link stochastic dif-ferential equations

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Outsourced data modification algorithm with assistance of multi-assistants in cloud computing

Outsourced data modification algorithm with assistance of mu...

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作者： Shen, Jian Shen, Jun Li, Xiong Wei, Fushan Li, Jiguo Department of Jiangsu Engineering Center of Network Monitoring Jiangsu210044 China Technology and Engineering Center of Meteorological Sensor Network Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing Jiangsu210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Hunan University of Science and Technology Hunan410082 China PLA Information Engineering University Henan450002 China Hohai University Nanjing210098 China

The rapid development of cloud storage has caused a wave of research craze. To improve cloud user experience, a large number of schemes are proposed with various practical performances, like long-term correct ensurence and dynamic support. In most works, however, authors seem to completely ignore that data owner alone could not have enough energy to discover and correct all inappropriate data outsourced. Others considered it and gave more than one user both read and write permissions, leading to chaotic management of multiusers. In this paper, we propose a novel algorithm, where data owner and authenticated assistants form a team to support data dynamics. Assistants are in charge of detecting problems of data and discussing a corresponding modification suggestion, while data owner is responsible for the implementation of the modification. Additionally, our algorithm supports identity authentication, malicious assistant revocation, and lazy update. Sufficient numerical analysis validates the performance of our algorithm. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Cloud storage

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Improved decoy-state quantum key distribution with uncharacterized heralded single-photon sources

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Chinese Physics B 2024年第2期33卷 204-208页

作者：徐乐辰张春辉周星宇王琴 Institute of Quantum Information and Technology Nanjing 210003China Broadband Wireless Communication and Sensor Network Technology Key Laboratory of Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China Telecommunication and Networks National Engineering Research Center Nanjing University of Posts and TelecommunicationsNanjing 210003China

Encoding system plays a significant role in quantum key distribution(QKD).However,the security and performance of QKD systems can be compromised by encoding misalignment due to the inevitable defects in realistic *** alleviate the influence of misalignments,a method exploiting statistics from mismatched basis is proposed to enable uncharacterized sources to generate secure keys in *** this work,we propose a scheme on four-intensity decoy-state quantum key distribution with uncharacterized heralded single-photon *** only requires the source states are prepared in a two-dimensional Hilbert space,and can thus reduce the complexity of practical ***,we carry out corresponding numerical simulations and demonstrate that our present four-intensity decoy-state scheme can achieve a much higher key rate compared than a three-intensity decoy-state method,and meantime it can obtain a longer transmission distance compared than the one using weak coherent sources.

关键词： quantum key distribution heralded single-photon source decoy-state method

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Auxiliary guidance manufacture and revealing potential mechanism of perovskite solar cell using machine learning

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Journal of Energy Chemistry 2023年第11期86卷 146-157,I0004页

作者： Quan Zhang Jianqi Wang Guohua Liu College of Electronic Information and Optical Engineering Nankai UniversityTianjin 300350China Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology Nankai UniversityTianjin 300350China General Terminal IC Interdisciplinary Science Center of Nankai University Nankai UniversityTianjin 300350China Engineering Research Center of Thin Film Optoelectronics Technology Ministry of EducationNankai UniversityTianjin 300350China

To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related *** to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related *** some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the *** order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural *** model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary *** make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the *** with other classical ML methods,the proposed model achieved better overall *** analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing *** model exhibits great potential to discover complex laws that are difficult for humans to discover *** addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real ***,the model achieved acceptable *** work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.

关键词： Machine learning Carbon neutrality Photovoltaic Auxiliary experiment design

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A new combination prediction model for short-term wind farm output power based on meteorological data collected by WSN

International Journal of Control and Automation

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International Journal of Control and Automation 2014年第1期7卷 171-180页

作者： Ma, Li Li, Bo Yang, Zhen Bin Du, Jie Wang, Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science and Technology Nanjing 210044 China CMA Public Meteorological Service Centre Beijing 100081 China

The prediction of wind farm output power is considered as an effective way to increase the wind power capacity and improve the safety and economy of power system. It is one of the hot research topics on wind power. The wind farm output power is related to many factors such as wind speed, temperature, etc., which is difficult to be described by some mathematical expression. In this paper, Back Propagation (BP) neural network algorithm is respectively combined with genetic algorithm (GA) and particle swarm optimization (PSO) to establish the combination prediction model of the short-term wind farm output power based on meteorological data collected by Wireless sensor network (WSN). The meteorological data is used to determine the input variables of the BP neural network. Meanwhile, the GA and the PSO is respectively used to adjust the value of BP's connection weight and threshold dynamically. Then the trained GA-BP and PSO-BP neural network are used to predict the wind power by combination method. The experiment results show that our method has better prediction capability compared with that using BP neural network, GA-BP neural network and PSO-BP neural network alone. © 2014 SERSC.

关键词： Wireless sensor networks

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QoE-Driven Big Data Management in Pervasive Edge Computing Environment

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Big Data Mining and Analytics 2018年第3期1卷 222-233页

作者： Qianyu Meng Kun Wang Xiaoming He Minyi Guo Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunications Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai Jiao Tong University

In the age of big data, services in the pervasive edge environment are expected to offer end-users better Quality-of-Experience(QoE) than that in a normal edge environment. However, the combined impact of the storage, delivery, and sensors used in various types of edge devices in this environment is producing volumes of high-dimensional big data that are increasingly pervasive and redundant. Therefore, enhancing the QoE has become a major challenge in high-dimensional big data in the pervasive edge computing environment. In this paper, to achieve high QoE, we propose a QoE model for evaluating the qualities of services in the pervasive edge computing environment. The QoE is related to the accuracy of high-dimensional big data and the transmission rate of this accurate data. To realize high accuracy of high-dimensional big data and the transmission of accurate data through out the pervasive edge computing environment, in this study we focused on the following two ***, we formulate the issue as a high-dimensional big data management problem and test different transmission rates to acquire the best QoE. Then, with respect to accuracy, we propose a Tensor-Fast Convolutional Neural network(TF-CNN) algorithm based on deep learning, which is suitable for high-dimensional big data analysis in the pervasive edge computing environment. Our simulation results reveal that our proposed algorithm can achieve high QoE performance.

关键词： Quality-of-Experience(QoE) high-dimensional big data management deep learning pervasive edge computing

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Perovskite light-emitting/detecting bifunctional fibres for wearable LiFi communication

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Light(Science & Applications) 2020年第1期9卷 441-449页

作者： Qingsong Shan Changting Wei Yan Jiang Jizhong Song Yousheng Zou Leimeng Xu Tao Fang Tiantian Wang Yuhui Dong Jiaxin Liu Boning Han Fengjuan Zhang Jiawei Chen Yongjin Wang Haibo Zeng MIIT Key Laboratory of Advanced Display Materials and Devices Institute of Optoelectronics&NanomaterialsSchool of Materials Science and EngineeringNanjing University of Science and TechnologyNanjing 210094China Peter Grünberg Research Center Laboratory of Broadband Wireless Communication and Sensor Network TechnologyMinistry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China

Light fidelity(LiFi),which is emerging as a compelling technology paradigm shifting the common means of highcapacity wireless communication technologies,requires wearable and full-duplex compact design because of its great significance in smart wearables as well as the‘Internet of Things’.However,the construction of the key component of wearable full-duplex LiFi,light-emitting/detecting bifunctional fibres,is still challenging because of the conflicting process between carrier separation and recombination,as well as the highly dynamic film-forming ***,we demonstrate light-emitting/detecting bifunctional fibres enabled by perovskite QDs with hybrid *** hybrid perovskite inks endow fibres with super-smooth QD ***,combined with the small exciton binding energy and high carrier mobility of perovskite QDs,enables successful integration of electroluminescence and photodetection into *** bifunctional fibres possess the narrowest electroluminescence full width at half maximum of ~19 nm and,more importantly,the capability for simultaneously transmitting and receiving *** successful fabrication of narrow emission full-duplex LiFi fibres paves the way for the fabrication and integration of low crosstalk interoperable smart wearables.

关键词： process perovskite functional

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UWB autocorrelation receiver based on average differential transmitted reference

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Journal of networks 2012年第11期7卷 1868-1875页

作者： Wang, Feng Ji, Xuande Wang, Yuyan Jiangsu Technology and Engineering Center of Meteorological Sensor Network Nanjing University of Information Science and Technology Nanjing China Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology Luoyang China

There are strong noise components included in the reference signal and the received signal of the ultra- wideband (UWB) differential transmitted reference (DTR) autocorrelation receiver, which impact on the receiver's performance seriously. Therefore this paper proposes a autocorrelation receiver based on average differential transmitted reference (ADTR). This receiver averages the received signals within every frame of the previous symbol period to form the new reference signal. The received signals within each frame of the current symbol interval are also averaged to construct the new received signal, which is correlated with the new reference signal to restore the transmitted symbols. Theoretical analysis and simulation results confirm that BER performance of ADTR autocorrelation receiver is better than the DTR receiver. Compared with DTR receiver, the signal to noise ratio gains of the ADTR receiver are 1.1dB with Ns=3 and 2.1dB with Ns=6 respectively when BER=10-4. © 2012 ACADEMY PUBLISHER.

关键词： Signal to noise ratio

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Demonstration of Einstein–Podolsky–Rosen Steering with Multiple Observers via Sequential Measurements

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Chinese Physics Letters 2022年第11期39卷 1-5页

作者： Jian Li Yang Zhou Qin Wang Institute of Quantum Information and Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Lab of Broadband Wireless Communication and Sensor Network Technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China National Engineering Research Center of Telecommunication and Networks Nanjing University of Posts and TelecommunicationsNanjing 210003China

Quantum correlation is a fundamental property that distinguishes quantum systems from classical ones,and is also a fragile resource under projective ***,it has been shown that a subsystem in entangled pairs can share nonlocalities with multiple observers in *** we present a new steering scenario where both subsystems are accessible by multiple *** results show that the two qubits in a singlet state can be simultaneously steered separately by two sequential observers.

关键词： Einstein projective subsystem

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