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4th IEEE International Conference on Electronic information and Communication Technology, ICEICT 2021

作者： He, Xiaoyuan Deng, Li Feng, Botao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781665432030

In this paper, a general scheme is proposed for dual-band orbital angular momentum (OAM) multiplexing based on a single-layer reflective geometric metasurface. As an OAM multiplexer, the proposed metasurface can distinguish different incidences featuring different incident angles, transform them into OAM waves with different topological charges (TCs) and control their reflection angle by modifying the k-space of the incidences simultaneously. In this way, the incidences can be combined into a coaxial beam without mutual interference because of the inherent orthogonality of different OAM modes. To achieve dual-band OAM multiplexing, a single-layer metal-insulator-metal (MIM) meta-atom that can independently impose arbitrary phase profiles on incidences at two different frequencies is designed. Based on it, a geometric metasurface is proposed for multiplexing OAM waves at 7 GHz and 14 GHz simultaneously. The simulated results show that eight independent data channels are created in a broadside beam when eight off-axis incidences carrying different information impinge on the proposed metasurface. This phenomenon indicates that the proposed metasurface can effectively achieve multiplexing by combining frequency and OAM domains to boost the channel capacity in wireless communications. © 2021 IEEE

关键词： Angular momentum

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Sparse Channel Reconstruction: A Generative Adversarial Network-Based Approach

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IEEE Transactions on Cognitive Communications and Networking 2024年

作者： Zhang, Yuxin He, Ruisi Yang, Mi Wang, Chenlong Qiu, Zhicheng Lu, Yang Ai, Bo Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation The Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Beijing Jiaotong University School of Computer and Information Technology Beijing100044 China

Wireless channels typically exhibit a sparse structure, with sparsity regarded as an inherent characteristics. A deeper understanding and accurate representation of channel sparsity contribute to a more comprehensive revelation of channel features and structure, thereby enhancing the performance of communication systems. However, current research on channel sparsity remains limited to the measurement, and traditional channel models have not sufficiently incorporated this critical characteristic. In this paper, considering channel deep sparse characteristics, a generative adversarial network (GAN)-based channel sparsity-tunable framework is proposed to reconstruct channel samples with various levels of sparsity. Specifically, continuous sparsity factors and a sparsity measurement module are introduced to manipulate and predict the sparsity of the reconstructed channel in the framework design. Channel power and delay are employed for model training to better consider the channel behavior of sparsity. Furthermore, the mutual information between input sparsity factors and reconstructed channels is enhanced to ensure that the sparsity factor has an actual impact on the level of reconstructed channel sparsity, thereby enabling the flexible and continuous reconstruction of channels with varying levels of sparsity. Simulation results prove that the proposed framework can effectively and accurately reconstruct channels with different levels of sparsity by changing sparsity factor, as well as providing good performance in measuring the sparsity of wireless channel. Finally, sparse manipulation performance is further validated using channel capacity simulation. © 2024 IEEE.

关键词： Signal reconstruction

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Measurement-Based Non-Stationary Markov Tapped Delay Line Channel Model for 5G-Railways

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Zhang, Xuejian He, Ruisi Yang, Mi Ding, Jianwen Chen, Ruifeng Gao, Shuaiqi Qi, Ziyi Zhang, Zhengyu Ai, Bo Zhong, Zhangdui Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation The School of Electronics and Information Engineering The Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China Henan High Speed Railway Operation and Maintenance Engineering Research Center Zhengzhou451460 China China Academy of Railway Sciences Corporation Ltd. Institute of Computing Technology Beijing100081 China

5 G for Railways (5G-R) is globally recognized as a promising next-generation railway communication system designed to meet increasing demands. Channel modeling serves as foundation for communication system design, with tapped delay line (TDL) models widely utilized in system simulations due to their simplicity and practicality and serves as a crucial component of various standards like 3GPP. However, existing TDL models applicable to 5G-R systems are limited. Most fail to capture non-stationarity, a critical characteristic of railway communications, while others are unsuitable for the specific frequency bands and bandwidths of 5G-R. In this paper, a channel measurement campaign for 5G-R dedicated network is carried out, resulting in a measurement-based 5-tap TDL model utilizing a first-order two-state Markov chain to represent channel non-stationarity. Key model parameters, including number of taps, statistical distribution of amplitude, phase and Doppler shift, and state transition probability matrix, are extracted. The correlation between tap amplitudes is also obtained. Finally, the accuracy of model is validated through comparisons with measurement data and 3GPP model. These findings are expected to offer valuable insights for design and link-level simulation of 5G-R systems. © 2025 IEEE.

关键词： Markov chains

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Insb/Janus Mosse Van Der Waals Heterostructure: First-Principles Calculation Study of Electronic Structure and Optical Properties

SSRN

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SSRN 2025年

作者： Qin, Xuebing Wang, Xuewen Zhao, Yingying Ye, Shengyun Hilal, Muhammad Zhang, Weibin Guo, Jie College of Physics and Electronics Information Yunnan Key Laboratory of Opto-Electronic Information Technology Key Laboratory of Advanced Technique & Preparation for Renewable Energy Materials-Ministry of Education Yunnan Normal University Kunming650500 China Department of Semiconductor System Engineering Sejong University Seoul05006 Korea Republic of

Highlights● The proposal of the InSb/Janus MoSSe van der Waals heterojunction and the investigation of its electronic structure and optical properties have been conducted.● The InSb/Janus MoSSe van der Waals heterojunction has a bandgap of 0.56 eV, is a direct bandgap semiconductor, and is classified as a Type II heterojunction.● The InSb/Janus MoSSe van der Waals heterojunction exhibits a broad spectral absorption range, spanning from the ultraviolet to the infrared regions.● The InSb/Janus MoSSe van der Waals heterojunction possesses strong light-harvesting capabilities. © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

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Graph Optimization Based Localization Algorithm by Fusing VLP and VO

Graph Optimization Based Localization Algorithm by Fusing VL...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Minan Guo Bowen Jia Chunyan Feng Zhiyu Zhu Yang Yang Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China China Electronics Standardization Institute Beijing China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Visible light positioning (VLP) has attracted considerable interest due to its high accuracy and low cost. However, VLP typically requires several light emitting diodes (LEDs) for positioning, which may lead to positioning failure in sparse LED layout or parts of the links are blocked. To address this challenge, we propose a novel graph optimization-based localization algorithm by fusing VLP and visual odometry (VO), termed GO-VLO. In the considered model, a few LEDs are deployed on the ceiling and broadcast positioning information, while a receiver equipped with a camera conducts GO-VLO to achieve precise positioning with limited LEDs. GO-VLO consists of a front end to process positioning information and a back end to further optimize the positioning results. In particular, VLP and VO are first used separately at the front end, thus obtaining two respective positioning results. Then, a visible-light visual odometry fusion mechanism is proposed to fuse the positioning results of VLP and VO preliminarily. To strengthen the constraints between frames and prevent location failure when VLP is unavailable, a novel graph optimization framework is further proposed in the back end, which notably takes the covisible feature points of two successive frames into consideration. Experimental results show that our proposed method attains a positioning accuracy of 4.93 cm in two dimension and 6.20 cm in three dimension under dense LED layout.

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Fully integrated hybrid microwave photonic receiver

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Photonics Research 2022年第6期10卷 1472-1483页

作者： JIACHEN LI SIGANG YANG HONGWEI CHEN XINGJUN WANG MINGHUA CHEN WEIWEN ZOU Beijing National Research Center for Information Science and Technology(BNRist) Department of Electronic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Microwave photonic receivers are a promising candidate in breaking the bandwidth limitation of traditional radio-frequency(RF)*** further balance the performance superiority with the requirements regarding size,weight,and power consumption(SWa P),the implementation of integrated microwave photonic microsystems has been considered an upgrade ***,up to now,to the best of our knowledge,chip-scale fully integrated microwave photonic receivers have not been reported due to the limitation of material *** this paper,we report a fully integrated hybrid microwave photonic receiver(FIH-MWPR)obtained by comprising the indium phosphide(In P)laser chip and the monolithic silicon-on-insulator(SOI)photonic circuit into the same substrate based on the low-coupling-loss micro-optics *** from the integration of all optoelectronic components,the packaged FIH-MWPR exhibits a compact volume of 6 cmand low power consumption of 1.2 *** FIH-MWPR supports a wide operation bandwidth from 2 to 18 ***,its RF-link performance to down-convert the RF signals to the intermediate frequency is experimentally characterized by measuring the link gain,the noise figure,and the spurious-free dynamic range metrics across the whole operation frequency ***,we have utilized it as a de-chirp receiver to process the broadband linear frequencymodulated(LFM)radar echo signals at different frequency bands(S-,C-,X-,and Ku-bands)and successfully demonstrated its high-resolution-ranging *** the best of our knowledge,this is the first realization of a chip-scale broadband fully integrated microwave photonic receiver,which is expected to be an important step in demonstrating the feasibility of all-integrated microwave photonic microsystems oriented to miniaturized application scenarios.

关键词： method microwave bands

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Neural-LAFC: A Neural Learning Adaptive Flight Controller for Tailless Flapping-Wing Robots Under Uncertain Wind Disturbance Conditions

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Guo, Qingcheng Zhang, Yichen Mou, Jiawang Liu, Wu Wu, Xiaosheng Lu, Jun-Guo Shanghai Jiao Tong University Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai200240 China Shanghai Jiao Tong University National Key Laboratory of Advanced Micro and Nano Manufacture Technology China Shanghai Jiao Tong University Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai200240 China Designing Institute of Hubei Space Technology Academy Wuhan China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

Enabling bio-inspired flapping-wing robots (FWRs) to maintain stable flight in windy environments, similar to real flying creatures, is of significant importance. In this work, a neural learning-based adaptive flight controller (Neural-LAFC) is proposed for the attitude and position control of a tailless FWR under uncertain wind conditions. The key approach involves employing a deep neural network (DNN) that incorporates not only attitude information but also instantaneous flapping angles of the wings to learn the aerodynamic torques that cannot be accurately modeled. The training data are obtained from flight experiments conducted with the FWR in a wind tunnel environment. Subsequently, a composite adaptive law is presented to update a set of linear coefficients. These linear coefficients are utilized to blend the pre-trained basis functions to represent the aerodynamic torques. The tracking errors are shown to exponentially converge to a bounded region, as guaranteed by a Lyapunov function. Based on the learning-based attitude controller, we also develop an adaptive controller for position control. Notably, apart from the training phase, the FWR operates without prior knowledge of wind speed. Experimental results demonstrate that the Neural-LAFC successfully achieves the desired attitude stabilization, target point tracking, and path tracking of the FWR in windy conditions. The proposed control scheme also outperforms baseline controllers in wind disturbance suppression, reducing the root mean square position errors by more than 40% when the FWR is subjected to a horizontal wind within the speed of 180 {cm s{-1}}. © 1965-2011 IEEE.

关键词： Wind tunnels

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Joint Angle-Delay Sparse Structured Compressed Sensing for ISAC Channel Estimation

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IEEE Transactions on Vehicular Technology 2025年

作者： He, Zeqian He, Ruisi Ai, Bo Zhang, Haoxiang Zhong, Zhangdui Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China Beijing Jiaotong University Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Ministry of Industry and Information Technology China Academy of Industrial Internet Beijing100102 China

In the upcoming 6 G communications, radar sensing will be integrated with communication to support a wide range of application scenarios. However, in complex Integrated Sensing and Communication (ISAC) channels, radar targets and communication scatterers may overlap, leading to similar sparse distributions of the sensing and communication channels in both the angle and delay domains. Additionally, the increasing use of compressed sensing (CS) for estimating communication parameters has given rise to numerous CS algorithms based on the expectation maximization (EM) method. However, due to the unique characteristics of the channel in specific scenarios, designing the channel sparse structure has become a crucial aspect of EM-base algorithm. Therefore, there is an urgent need to develop an appropriate channel sparse structure and design a CS algorithm specifically for the ISAC scenario. In this paper, we address the problem of channel estimation in a time-division duplex multi-input multi-output ISAC system using a bi-static model. We introduce a Joint Angle-Delay Sparse Structure (JADSS) to capture the sparsity characteristics of the ISAC channel in both the angle and delay domains. Furthermore, we design a message passing estimator within the framework of an EM-based double-loop algorithm to estimate the ISAC channel. Through simulations, we demonstrate that the proposed CS algorithm utilizing JADSS achieves competitive error performance. © 1967-2012 IEEE.

关键词： Channel estimation

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Design and implementation of GPS RTK positioning using carrier phase measurement on an embedded board

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IEIE Transactions on Smart Processing and Computing 2020年第6期9卷 477-484页

作者： Khanal, Jhabindra Vista, Felipe Patino Chul, Kim Young Chong, Kil To Department of Electronics and Information Engineering Jeonbuk National University Jeonju54896 Korea Republic of School of Mechanical System Engineering Kunsan National University Gunsan54150 Korea Republic of Advanced Electronics and Information Research Center Jeonbuk National University Jeonju54896 Korea Republic of

The Global Positioning system (GPS) is currently used in many geodetic applications to obtain precise positions within a centimeter, or even within a millimeter. Generally, such a level of accuracy can be obtained by performing complex processing on expensive receivers and antennas. Such high-cost devices can be replaced by low-cost, single-frequency GPS receivers to obtain precise positions. To do so, in this paper, Carrier Phase (CP)-based relative algorithms are successfully implemented on a CUDA-enabled embedded board (the Jetson TK1) with two low-cost GNNS receivers. A CUDA-enabled graphics processing unit (GPU) is a highly parallel structure that makes efficient and faster CP-based algorithms and that can process large blocks of data in parallel. Our results from field measurements clearly show that the positioning performance of a Rover with respect to the Base receiver reached the centimeter level. Therefore, this work shows the possibility of accurately estimating the position of a receiver using low-cost hardware-based RTK algorithms. Copyrights © 2020 The Institute of electronics and information Engineers

关键词： Global positioning system

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Epidermal piezoresistive structure with deep learning-assisted data translation

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npj Flexible electronics 2022年第1期6卷 672-680页

作者： Changrok So Jong Uk Kim Haiwen Luan Sang Uk Park Hyochan Kim Seungyong Han Doyoung Kim Changhwan Shin Tae-il Kim Wi Hyoung Lee Yoonseok Park Keun Heo Hyoung Won Baac Jong Hwan Ko Sang Min Won Department of Electrical and Computer Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea School of Chemical Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Querrey Simpson Institute for Bioelectronics Northwestern UniversityEvanstonIL 60208USA Department of Mechanical Engineering Ajou UniversitySuwon 16499Republic of Korea School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea Biomedical Institute for Convergence(BICS) Sungkyunkwan University(SKKU)Suwon 16419Korea Department of Organic and Nano System Engineering Konkuk UniversitySeoul 05029Republic of Korea Department of Advanced Materials Engineering for Information and Electronics Kyung Hee UniversityYongin 17104Republic of Korea School of Semiconductor and Chemical Engineering Jeonbuk National UniversityJeonju 54896Republic of Korea

Continued research on the epidermal electronic sensor aims to develop sophisticated platforms that reproduce key multimodal responses in human skin,with the ability to sense various external stimuli,such as pressure,shear,torsion,and *** development of such applications utilizes algorithmic interpretations to analyze the complex stimulus shape,magnitude,and various moduli of the epidermis,requiring multiple complex equations for the attached *** this experiment,we integrate silicon piezoresistors with a customized deep learning data process to facilitate in the precise evaluation and assessment of various stimuli without the need for such *** the ability to surpass conventional vanilla deep regression models,the customized regression and classification model is capable of predicting the magnitude of the external force,epidermal hardness and object shape with an average mean absolute percentage error and accuracy of<15 and 96.9%,*** technical ability of the deep learning-aided sensor and the consequent accurate data process provide important foundations for the future sensory electronic system.

关键词： utilize attached precise

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