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Modular Multilevel DC-DC Converter With Inherent Bipolar Operation Capability for Resilient Bipolar MVDC Grids

CPSS Transactions on Power Electronics and Applications 2022年第1期7卷 37-48页

作者： Shanshan Zhao Yu Chen Shenghui Cui Jingxin Hu State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology China Department of Electrical and Computer Engineering Seoul National University Korea Institute for Power Generation and Storage Systems E. ON Energy Research Center RWTH Aachen University Germany

Bipolar medium-voltage dc (MVDC) distribution systems are of great interests nowadays due to its high availability and reliability. A bipolar MVDC grid can be established by the installation of power-balancers or directly by converters with inherent bipolar operation capability to avoid the extra cost and volume. Therefore, this paper proposes a modular multilevel dc-dc converter (MMDC) with inherent bipolar operation capability for the interconnection of bipolar MVDC grids and LVDC girds. Considering that the MMDC is normally only capable of operating with monopole MVDC distribution systems due to the symmetric structure and operation scheme, a center-tapped high-frequency interface transformer is employed on the MV side of the MMDC. Based on the concept of the flux dc-bias cancellation, a dedicated operation method is proposed, whereby the power flows of the two MVDC poles can be regulated independently with a simple control scheme, and no penalty of increased current rating is imposed on the semiconductor devices or the interface transformer compared to the conventional MMDC with monopole operation. Additionally, the MMDC can realize single-pole operation in case one pole is faulty and deliver at least 50% of the rated power capacity, which significantly enhance the reliability and availability of the power delivery. The validity of the proposed bipolar operation scheme of the MMDC has been verified by both simulations and experiments with a down-scale prototype.

关键词： Multilevel converters Semiconductor devices Prototypes DC-DC power converters Transformers Valves Power electronics

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A Survey of Recent Advances in Optimization Methods for Wireless Communications

arXiv

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arXiv 2024年

作者： Liu, Ya-Feng Chang, Tsung-Hui Hong, Mingyi Wu, Zheyu So, Anthony Man-Cho Jorswieck, Eduard A. Yu, Wei The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen China Shenzhen Research Institute of Big Data China The Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States The Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong The Institute for Communication Technology Technische Universitat Braunschweig Germany The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada

Mathematical optimization is now widely regarded as an indispensable modeling and solution tool for the design of wireless communications systems. While optimization has played a significant role in the revolutionary progress in wireless communication and networking technologies from 1G to 5G and onto the future 6G, the innovations in wireless technologies have also substantially transformed the nature of the underlying mathematical optimization problems upon which the system designs are based and have sparked significant innovations in the development of methodologies to understand, to analyze, and to solve those problems. In this paper, we provide a comprehensive survey of recent advances in mathematical optimization theory and algorithms for wireless communication system design. We begin by illustrating common features of mathematical optimization problems arising in wireless communication system design. We discuss various scenarios and use cases and their associated mathematical structures from an optimization perspective. We then provide an overview of recently developed optimization techniques in areas ranging from nonconvex optimization, global optimization, and integer programming, to distributed optimization and learning-based optimization. The key to successful solution of mathematical optimization problems is in carefully choosing or developing suitable algorithms (or neural network architectures) that can exploit the underlying problem structure. We conclude the paper by identifying several open research challenges and outlining future research directions. Copyright © 2024, The Authors. All rights reserved.

关键词： Beamforming

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UAV-Assisted Downlink-and-Uplink Communication in the Presence of Multiple Malicious Jammers

UAV-Assisted Downlink-and-Uplink Communication in the Presen...

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IEEE Conference on Wireless Communications and Networking

作者： Zhiyu Huang Zhichao Sheng Ali A. Nasir Cheng Yin Antonino Masaracchia Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University Shanghai China Department of Electrical Engineering and Center for Communication Systems and Sensing KFUPM Dhahran Saudi Arabia Institute for Communication Systems University of Surrey U.K. School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast U.K.

This paper investigates the unmanned aerial vehicle (UAV)-assisted communication network with multiple downlink users (DLUs) and uplink users (ULUs) in the presence of multiple malicious jammers. To guarantee fairness among the users and their uplink and downlink communication throughput, we aim to maximize the minimum average throughput by jointly optimizing the scheduling of ULUs/DLUs, three dimensional (3D) trajectory and the UAV transmission power. Although the optimization problem is computationally intractable due to its non-convexity, we develop an iterative algorithm based on the block coordinate descend approach and the successive convex approximation technique to solve the problem efficiently. Numerical outcomes show that our proposed algorithm can improve throughput significantly over several benchmark schemes.

关键词： Three-dimensional displays Processor scheduling Benchmark testing Throughput Autonomous aerial vehicles Downlink Scheduling

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Exploration of Optimizing FPGA-based Qubit Controller for Experiments on Superconducting Quantum Computing Hardware

Exploration of Optimizing FPGA-based Qubit Controller for Ex...

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IEEE International Conference on Electro-Information Technology

作者： Hans Johnson Silvia Zorzetti Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL U.S.A. Superconducting Quantum Materials and Systems Center (SQMS) Fermi National Accelerator Laboratory Batavia IL U.S.A.

This work explores avenues and target areas for optimizing FPGA-based control hardware for experiments conducted on superconducting quantum computing systems and serves as an introduction to some of the current research at the intersection of classical and quantum computing hardware. With the promise of building larger-scale error-corrected quantum computers based on superconducting qubit architecture, innovations to room-temperature control electronics are needed to bring these quantum realizations to fruition. The QICK (Quantum Instrumentation Control Kit) is one leading experimental FPGA-based implementations. However, its integration into other experimental quantum computing architectures, especially those using superconducting radiofrequency (SRF) cavities, is largely unexplored. We identify some key target areas for optimizing control electronics for superconducting qubit architectures and provide some preliminary results to the resolution of a control pulse waveform. With optimizations targeted at 3D superconducting qubit setups, we hope to bring to light some of the requirements in classical computational methodologies to bring out the full potential of this quantum computing architecture, and to convey the excitement of progress in this research.

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Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Us...

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Quantum Computing and engineering (QCE), IEEE International Conference on

作者： Hans Johnson Silvia Zorzetti Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL U.S.A. Fermi National Accelerator Laboratory Superconducting Quantum Materials and Systems Center (SQMS) Batavia IL U.S.A.

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

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A Wideband Decoupling Technique for Stacked Patch Antenna Array By Using Triangular Layout

A Wideband Decoupling Technique for Stacked Patch Antenna Ar...

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IEEE Conference on Antenna Measurements & Applications (CAMA)

作者： Yulin Fang Zijian Shao Yue Ping Zhang Key Laboratory of High-Speed Electronic Systems Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering Princeton University Princeton USA School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781665490382

A wideband stacked patch antenna decoupling technique is proposed in this paper. The shorted stacked microstrip patch antenna (SS-MPA) achieves excellent isolation between E-plane coupled elements while the coupling between H-plane coupled elements is relatively large. By employing the triangular layout, the H-plane coupling is lessened to a certain extent. To further reduce the mutual coupling between the adjacent elements, a pair of twisted slits on the ground along the non-radiating edge of the SS-MPA are etched, which introduces a new decoupling null in the coupling curve of the intersecting elements, achieving a good decoupling performance in the SSMPA array. Results indicate that good decoupling performance can be realized.

关键词： Couplings Antenna measurements Mutual coupling Patch antennas Layout Microstrip antennas Microstrip

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Energy-Efficient Design in STAR-RIS Assisted Communication System with Antenna Selection

Energy-Efficient Design in STAR-RIS Assisted Communication S...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Guangyang Zhang Yang Lu Bo Ai Zhangdui Zhong Zhiguo Ding Tony Q. S. Quek School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing China Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi UAE Department of Electrical and Electronic Engineering University of Manchester Manchester UK Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

This paper investigates the energy-efficient beamforming design in a simultaneous transmission and reflection-reconfigurable intelligent surface (STAR-RIS) assisted wireless communication system, where the antenna selection scheme is adopted. An energy efficiency (EE) maximization problem is formulated by optimizing the transmit beamformers and the phase shift vectors subject to the power budget constraint of the base station (BS), the maximum transmit power constraint per antenna and the users' data rate requirements. An alternating optimization-based algorithm is proposed to tackle the coupled variables, and the quadratic transform is used to deal with the fractional formulations. Simulation results demonstrate that the antenna selection scheme can significantly improve the EE performance by suppressing the energy consumption due to massive antennas. With the assistance of the STAR-RIS, the EE performance is further enhanced.

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Deep Neural Network Architecture Search for Accurate Visual Pose Estimation aboard Nano-UAVs

Deep Neural Network Architecture Search for Accurate Visual ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： E. Cereda L. Crupi M. Risso A. Burrello L. Benini A. Giusti D. Jahier Pagliari D. Palossi Dalle Molle Institute for Artificial Intelligence USI and SUPSI Lugano Switzerland Department of Control and Computer Engineering Politecnico di Torino Turin Italy Department of Electrical Electronic and Information Engineering University of Bologna Bologna Italy Integrated Systems Laboratory ETH Zürich Zürich Switzerland

Miniaturized autonomous unmanned aerial vehicles (UAVs) are an emerging and trending topic. With their form factor as big as the palm of one hand, they can reach spots otherwise inaccessible to bigger robots and safely operate in human surroundings. The simple electronics aboard such robots (sub-100 mW) make them particularly cheap and attractive but pose significant challenges in enabling onboard sophisticated intelligence. In this work, we leverage a novel neural architecture search (NAS) technique to automatically identify several Pareto-optimal convolutional neural networks (CNNs) for a visual pose estimation task. Our work demonstrates how reallife and field-tested robotics applications can concretely leverage NAS technologies to automatically and efficiently optimize CNNs for the specific hardware constraints of small UAVs. We deploy several NAS-optimized CNNs and run them in closed-loop aboard a 27-g Crazyflie nano-UAV equipped with a parallel ultra-low power System-on-Chip. Our results improve the State-of-the-Art by reducing the in-field control error of 32% while achieving a real-time onboard inference-rate of ~10Hz@10mW and ~50Hz@90mW.

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CODiT: Conformal Out-of-Distribution Detection in Time-Series Data

arXiv

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arXiv 2022年

作者： Kaur, Ramneet Sridhar, Kaustubh Park, Sangdon Jha, Susmit Roy, Anirban Sokolsky, Oleg Lee, Insup Department of Computer and Information Science University of Pennsylvania United States Department of Electrical and Systems Engineering University of Pennsylvania United States School of Cybersecurity and Privacy Georgia Institute of Technology United States Computer Science Laboratory SRI International United States

Machine learning models are prone to making incorrect predictions on inputs that are far from the training distribution. This hinders their deployment in safety-critical applications such as autonomous vehicles and healthcare. The detection of a shift from the training distribution of individual datapoints has gained attention. A number of techniques have been proposed for such out-of-distribution (OOD) detection. But in many applications, the inputs to a machine learning model form a temporal sequence. Existing techniques for OOD detection in time-series data either do not exploit temporal relationships in the sequence or do not provide any guarantees on detection. We propose using deviation from the in-distribution temporal equivariance as the non-conformity measure in conformal anomaly detection framework for OOD detection in time-series data. Computing independent predictions from multiple conformal detectors based on the proposed measure and combining these predictions by Fisher's method leads to the proposed detector CODiT with guarantees on false detection in time-series data. We illustrate the efficacy of CODiT by achieving state-of-the-art results on computer vision datasets in autonomous driving. We also show that CODiT can be used for OOD detection in non-vision datasets by performing experiments on the physiological GAIT sensory dataset. Code, data, and trained models are available at https://***/kaustubhsridhar/time-series-OOD. © 2022, CC BY.

关键词： Forecasting

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Tractable Data Enriched Distributionally Robust Chance-Constrained CVR

arXiv

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arXiv 2022年

作者： Zhang, Qianzhi Bu, Fankun Guo, Yi Wang, Zhaoyu Department of Electrical and Computer Engineering Iowa State University AmesIA50011 United States Power Systems Laboratory ETH Zürich Zürich8092 Switzerland

This paper proposes a tractable distributionally robust chance-constrained conservation voltage reduction (DRCC-CVR) method with enriched data-based ambiguity set in unbalanced three-phase distribution systems. The increasing penetration of distributed renewable energy not only brings clean power but also challenges the voltage regulation and energy-saving performance of CVR by introducing high uncertainties to distribution systems. In most cases, the conventional robust optimization methods for CVR only provide conservative solutions. To better consider the impacts of load and PV generation uncertainties on CVR implementation in distribution systems and provide less conservative solutions, this paper develops a data-based DRCC-CVR model with tractable reformulation and data enrichment method. Even though the uncertainties of load and photovoltaic (PV) can be captured by data, the availability of smart meters (SMs) and micro-phasor measurement units (PMUs) is restricted by cost budget. The limited data access may hinder the performance of the proposed DRCC-CVR. Thus, we further present a data enrichment method to statistically recover the high-resolution load and PV generation data from low-resolution data with Gaussian Process Regression (GPR) and Markov Chain (MC) models, which can be used to construct a data-based moment ambiguity set of uncertainty distributions for the proposed DRCC-CVR. Finally, the nonlinear power flow and voltage dependant load models and DRCC with moment-based ambiguity set are reformulated to be computationally tractable and tested on a real distribution feeder in Midwest U. S. to validate the effectiveness and robustness of the proposed method. © 2022, CC BY.

关键词： Energy conservation

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