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Low-Complexity Joint Communication and Sensing Beamforming for ISAC Systems: A Bisection Search Approach

IEEE Internet of Things Journal 2025年第13期12卷 25620-25632页

作者： Wang, Jionghui Wang, Bin Fang, Jun Li, Hongbin University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Guangdong Dejiu New Energy Co. Ltd Foshan528200 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States

We investigate the problem of joint sensing and communication beamforming for multiple-input multiple-output integrated sensing and communication (MIMO-ISAC) systems. The objective is to minimize the Cramér-Rao bound (CRB) of the direction-of-arrival of a point target or the CRB of the target response matrix of an extended target, subject to a number of communication signal-to-interference-plus-noise-ratio (SINR) constraints. Although such a problem has been studied in prior works, existing methods such as semidefinite programming (SDP) suffer a prohibitively high computational complexity. To address this issue, we first employ a bisection search framework to transform the non-convex problem into a series of feasibility-checking problems, and then develop an efficient gradient-based algorithm for feasibility checking. Unlike the SDP method which needs to lift the problem to a high-dimensional space, our proposed method directly works on the original beamformer domain. Our analysis and numerical results show that the proposed algorithm presents a significant advantage over the SDP method in terms of computational efficiency, meanwhile achieving the same communication/sensing performance. © 2014 IEEE.

关键词： Cramer-Rao bounds

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Boosting Monolayer Transition Metal Dichalcogenides Growth by Hydrogen-Free Ramping during Chemical Vapor Deposition

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Nano Letters 2024年第27期24卷 8277-8286页

作者： Liu, Hongwei Zhang, Tianyi Wu, Peng Lee, Hae Won Liu, Zhenjing Tang, Tsz Wing Tang, Shin-Yi Kang, Ting Park, Ji-Hoon Wang, Jun Zhang, Kenan Zheng, Xudong Peng, Yu-Ren Chueh, Yu-Lun Liu, Yuan Palacios, Tomás Kong, Jing Luo, Zhengtang Department of Chemical and Biological Engineering Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction The Hong Kong University of Science and Technology Kowloon999077 Hong Kong Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering National Tsing-Hua University Hsinchu30013 Taiwan Department of Materials Science and Engineering Korea University Seoul02841 Korea Republic of Key Laboratory for Micro-Nano Optoelectronic Devices of Ministry of Education School of Physics and Electronics Hunan University Changsha410082 China

The controlled vapor-phase synthesis of two-dimensional (2D) transition metal dichalcogenides (TMDs) is essential for functional applications. While chemical vapor deposition (CVD) techniques have been successful for transition metal sulfides, extending these methods to selenides and tellurides often faces challenges due to uncertain roles of hydrogen (H2) in their synthesis. Using CVD growth of MoSe2 as an example, this study illustrates the role of a H2-free environment during temperature ramping in suppressing the reduction of MoO3, which promotes effective vaporization and selenization of the Mo precursor to form MoSe2 monolayers with excellent crystal quality. As-synthesized MoSe2 monolayer-based field-effect transistors show excellent carrier mobility of up to 20.9 cm2/(V·s) with an on-off ratio of 7 × 107. This approach can be extended to other TMDs, such as WSe2, MoTe2, and MoSe2/WSe2 in-plane heterostructures. Our work provides a rational and facile approach to reproducibly synthesize high-quality TMD monolayers, facilitating their translation from laboratory to manufacturing. © 2024 American Chemical Society.

关键词： Monolayers

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Training Graph Neural Networks on Growing Stochastic Graphs 48

Training Graph Neural Networks on Growing Stochastic Graphs

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Cerviño, Juan Ruiz, Luana Ribeiro, Alejandro University of Pennsylvania Department of Electrical and Systems Engineering Philadelphia United States Mit Computer Science & Artificial Intelligence Laboratory Cambridge United States

ISBN: (纸本)9781728163277

Graph Neural Networks (GNNs) rely on graph convolutions to exploit meaningful patterns in networked data. Based on matrix multiplications, convolutions incur in high computational costs leading to scalability limitations in practice. To overcome these limitations, proposed methods rely on training GNNs in smaller number of nodes, and then transferring the GNN to larger graphs. Even though these methods are able to bound the difference between the output of the GNN with different number of nodes, they do not provide guarantees against the optimal GNN on the very large graph. In this paper, we propose to learn GNNs on very large graphs by leveraging the limit object of a sequence of growing graphs, the graphon. We propose to grow the size of the graph as we train, and we show that our proposed methodology - learning by transference - converges to a neighborhood of a first order stationary point on the graphon data. A numerical experiment validates our proposed approach. © 2023 IEEE.

关键词： Graph Neural Networks Graphons

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State Estimation for Integrated Energy Systems: Motivations, Advances, and Future Work

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IEEE Transactions on Power Systems 2024年第4期40卷 3057-3073页

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on State Estimation (SE) for Integrated Energy Systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power Systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy Systems-State Estimation (IES-SE) and more established Electric Power System-State Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： Power system analysis

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Digital Twins for Photorealistic Event-Based Structural Dynamics 41st

Digital Twins for Photorealistic Event-Based Structural Dyna...

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41st IMAC, A Conference and Exposition on Structural Dynamics, 2023

作者： Davis, Allison Walker, Edward Chen, Marcus Felipe, Moises Mascareñas, David Moreu, Fernando Cattaneo, Alessandro Department of Electrical Engineering and Computer Science College of Engineering and Applied Science University of Wyoming LaramieWY United States Department of Mechanical Engineering George R. Brown School of Engineering Rice University HoustonTX United States Department of Electrical and Computer Engineering College of Engineering University of Washington SeattleWA United States Los Alamos National Laboratory Los AlamosNM United States Department of Civil Construction and Environmental Engineering University of New Mexico AlbuquerqueNM United States

ISBN: (纸本)9783031349096

Digital twins are virtual representations of real-world structures that can be used for modeling and simulation. Because of digital twins’ ability to simulate complex structural behaviors, they also have potential for structural health monitoring (SHM) applications. Video-based SHM techniques are advantageous due to the lower installation/maintenance costs, analysis in high-spatial resolution, and its non-contact monitoring features. Both digital twins and video-based techniques hold particular interest in the fields of non-destructive evaluation, damage identification, and modal analysis. An effective use of these techniques for SHM applications still poses several challenges. Neural radiance fields (NeRFs) are an emerging and promising type of neural network that can render photorealistic novel views of a complex scene using a sparse data set of 2D images. Originally, NeRF was designed to capture static scenes, but recent work has extended its capability to capture dynamic scenes which has implications for medium and long-term SHM. However, to date, most NeRFs use frame-based images and videos as input data. Frame-based video monitoring approaches result in redundant information derived from the fact that, for structural dynamics monitoring, only a small number of active pixels record the actual dynamical changes in the structure, resulting in intensive computational loads for data processing and storage. A promising alternative is event-based imaging, which only records pixel-wise changes on the illumination of a scene. Event-based imaging creates a sparse set of data, while accurately capturing the dynamics. The work proposes a method to extract the dynamics of a structure using a generated digital twin. Using Unreal Engine 5, digital twins of rigid and non-rigid structures were generated. The digital twin model was then used along with an event-based camera simulator to generate event-based data. A frequency analysis framework was then developed to extract the

关键词： Cameras

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Neural Architecture Search for Image Dehazing

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1337-1347页

作者： Mandal, Murari Meedimale, Yashwanth Reddy Satish Kumar Reddy, M. Vipparthi, Santosh Kumar Kalinga Institute of Industrial Technology Deemed to Be University School of Computer Engineering Bhubaneswar751024 India Walmart Global Tech Hyderabad500081 India Texas A&m University Computer Science and Engineering Department College StationTX77843 United States Indian Institute of Technology Ropar Cvpr Laboratory at Department of Electrical Engineering Rupnagar140001 India

Manual design of deep networks require numerous trials and parameter tuning, resulting in inefficient utilization of time, energy, and resources. In this article, we present a neural architecture search (NAS) algorithm - AutoDehaze, to automatically discover effective neural network for single image dehazing. The proposed AutoDehaze algorithm is built on the gradient-based search strategy and hierarchical network-level optimization. We construct a set of search space layouts to reduce memory consumption, avoid the NAS collapse issue, and considerably accelerate the search speed. We propose four search spaces AutoDehaze B, AutoDehaze U1, AutoDehaze U2, and AutoDehaze L, which are inspired by the boat-shaped, U-shaped, and lateral connection-based designs. To the best of authors knowledge, this is a first attempt to present an NAS method for dehazing with a variety of network search strategies. We conduct a comprehensive set of experiments on Reside-Standard (SOTS), Reside-β (SOTS) and Reside-β (HSTS), D-Hazy, and HazeRD datasets. The architectures discovered by the proposed AutoDehaze quantitatively and qualitatively outperform the existing state-of-the-art approaches. The experiments also show that our models have considerably fewer parameters and runs at a faster inference speed in both CPU and GPU devices. © 2020 IEEE.

关键词： Network architecture

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A Framework for Cyber-Secure Monitoring and Safe Operation of Solar PV Microgrids

A Framework for Cyber-Secure Monitoring and Safe Operation o...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Kim, Jaewon Ilic, Marija Xie, Le Massachusetts Institute of Technology Laboratory for Information & Decision Systems CambridgeMA02139 United States Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA02139 United States Texas A&m University Department of Electrical & Computer Engineering College StationTX77843 United States

ISBN: (纸本)9798350376067

In this paper, we introduce a systematic design of an end-to-end cyber-secure monitoring and safe operation framework for solar photovoltaic (PV)-rich microgrids, by focusing on the use of on-line attack detector for defending against potential cyber-physical attacks and sensor measurement data processing for operational safety. The proposed approach is based on: 1) identifying component models using their input and output measurements;2) dynamic watermarking (DW) methodology for on-line cyber-attack detection and its timing;and 3) an adaptive event-driven safe shutdown procedure after attack detection. It is shown how these three components interactive steps jointly to ensure safe operation under both normal operational scenarios and compromised operational scenarios with some malicious sensors caused by cyber-attacks on solar PV microgrids. Through this on-line integration, the proposed framework dynamically adapts to varying solar irradiance, load demands, operating conditions, and potential cyber-physical attacks. This forms a cyber-physical system which can pro-actively detect and mitigate potential cyber-physical attacks on solar PV microgrids. We describe its proof-of-concept implementation using real-world industrial solar farm data provided by the CenterPoint Energy. This study contributes to enhancing the cyber-security and safe operation of solar PVrich power systems, offering a scalable solution to other types of emerging renewable-rich energy distribution systems. © 2024 IEEE.

关键词： Cyber attacks

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A 2.2-3.6 GHz CMOS Reconfigurable Fourth-Order Bandpass Filter With Compact Size and High Selectivity Using Transformer-Type Resonators

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IEEE Transactions on Microwave Theory and Techniques 2023年第1期71卷 218-229页

作者： Li, Kun Liu, Bin Chi, Pei-Ling Wang, Yong Yang, Tao University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu Sichuan610054 China National Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan Nanhu Laboratory Research Center of Advanced Rf Chips and Systems Jiaxing Zhejiang314000 China

A compact reconfigurable CMOS bandpass filter (BPF) with high selectivity is proposed using transformer-type resonators in this article. The transformer-type resonator is constructed by a transformer loaded with parallel varactors for frequency tuning, and two varactors are then added across primary wind and secondary wind for coupling tuning. With the transformer-type structure, one resonator is formed inside another resonator, thus fully utilizing the chip area and resulting in a miniaturized structure. Magnetic and electrical couplings are formed within the transformer-type resonator and facilitate the bandwidth (BW) tuning. The quality factor (Q) of each resonator is improved by cross-coupled negative resistance structure. Meanwhile, two pairs of transformer-type resonators are placed side-by-side and naturally form a quadruplet structure;as a result, two transmission zeros (TZs) are introduced at each side of the passband thus significantly improving the selectivity and stopband rejection of the BPF. The proposed tunable on-chip BPF is manufactured by a commercial 55 nm bulk CMOS technology with a core area of 1.48 × 0.54 mm2. The filter center frequency (CF) can be tuned from 2.2 to 3.6 GHz, while the 3 dB fractional BW (FBW) can be tuned from 14% to 33%. The shape factor of the proposed filter is 1.4-1.9. © 1963-2012 IEEE.

关键词： Varactors

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Optical Ciphering Scheme for Cancellable Speaker Identification System

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computer Systems science & engineering 2023年第4期45卷 563-578页

作者： Walid El-Shafai Marwa A.Elsayed Mohsen A.Rashwan Moawad I.Dessouky Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi EAbd El-Samie Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Communications Faculty of EngineeringCairo UniversityCairoEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Most current security and authentication systems are based on personal *** security problem is a major issue in the field of biometric *** is due to the use in databases of the original *** biometrics will forever be lost if these databases are *** privacy is the most important goal of cancelable *** order to protect privacy,therefore,cancelable biometrics should be non-invertible in such a way that no information can be inverted from the cancelable biometric templates stored in personal identification/verification *** methodology to achieve non-invertibility is the employment of non-invertible *** work suggests an encryption process for cancellable speaker identification using a hybrid encryption *** system includes the 3D Jigsaw transforms and Fractional Fourier Transform(FrFT).The proposed scheme is compared with the optical Double Random Phase Encoding(DRPE)encryption *** evaluation of simulation results of cancellable biometrics shows that the algorithm proposed is secure,authoritative,and *** encryption and cancelability effects are good and reveal good ***,it introduces recommended security and robustness levels for its utilization for achieving efficient cancellable biometrics systems.

关键词： Cancellable biometrics jigsaw transform FrFT DRPE speaker identification

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Hemodynamic Analysis and Diagnosis Based on Multi-Deep Learning Models

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Fluid Dynamics & Materials Processing 2023年第6期19卷 1369-1383页

作者： Xing Deng Feipeng Da Haijian Shao School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Jiangsu University of Science and TechnologyZhenjiang212003China Department of Electrical and Computer Engineering University of NevadaLas Vegas89154USA

This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional *** work is intended to improve current methods for the assessment of human health through measurement of the distribution of four types of blood cells,namely,eosinophils,neutrophils,monocytes,and lymphocytes,known for their relationship with human body damage,inflammatory regions,and organ illnesses,in particular,and with the health of the immune system and other hazards,such as cardiovascular disease or infections,more in *** results of the experiments show that the deep learning models can automatically extract features from the blood cell images and properly classify them with an accuracy of 98%,97%,and 89%,respectively,with regard to the training,verification,and testing of the corresponding datasets.

关键词： Blood cell analysis deep learning models classification-detection

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