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Cell-Free Massive MIMO with Multi-Antenna Users over Weichselberger Rician Channels

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arXiv 2022年

作者： Li, Xin Zhang, Jiayi Wang, Zhe Ai, Bo Ng, Derrick Wing Kwan The School of Electronic and Information Engineering The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China School of Electrical Engineering and Telecommunications University of New South Wales NSW2052 Australia

We consider a cell-free massive multiple-input multiple-output (MIMO) system with multi-antenna access points and user equipments (UEs) over Weichselberger Rician fading channels with random phase-shifts. More specifically, we investigate the uplink spectral efficiency (SE) for two pragmatic processing schemes: 1) the fully centralized processing scheme with global minimum mean square error (MMSE) or maximum ratio (MR) combining;2) the large-scale fading decoding (LSFD) scheme with local MMSE or MR combining. To improve the system SE performance, we propose a practical uplink precoding scheme based on only the eigenbasis of the UE-side correlation matrices. Moreover, we derive novel closed-form SE expressions for characterizing the LSFD scheme with the MR combining. Numerical results validate the accuracy of our derived expressions and show that the proposed precoding scheme can significantly improve the SE performance compared with the scenario without any precoding scheme. Copyright © 2022, The Authors. All rights reserved.

关键词： Spectrum efficiency

Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach

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arXiv 2022年

作者： Li, Yang Wei, Xinhao Li, Yuanzheng Dong, Zhaoyang Shahidehpour, Mohammad The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The School of Artifcial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The Electrical and Computer Engineering Department Illinois Institute of Technology ChicagoIL60616 United States The ECE Department The King Abdulaziz University Saudi Arabia

As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has received increasing attention in recent years. However, so far little attention has been paid to privacy preservation issues in the detection of FDIAs in smart grids. Inspired by federated learning, a FDIA detection method based on secure federated deep learning is proposed in this paper by combining Transformer, federated learning and Paillier cryptosystem. The Transformer, as a detector deployed in edge nodes, delves deep into the connection between individual electrical quantities by using its multi-head self-attention mechanism. By using federated learning framework, our approach utilizes the data from all nodes to collaboratively train a detection model while preserving data privacy by keeping the data locally during training. To improve the security of federated learning, a secure federated learning scheme is designed by combing Paillier cryptosystem with federated learning. Through extensive experiments on the IEEE 14-bus and 118-bus test systems, the effectiveness and superiority of the proposed method are verified. Copyright © 2022, The Authors. All rights reserved.

关键词： Smart power grids

LAPNet: Non-rigid registration derived in k-space for magnetic resonance imaging

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arXiv 2021年

作者： Küstner, Thomas Pan, Jiazhen Qi, Haikun Cruz, Gastao Gilliam, Christopher Blu, Thierry Yang, Bin Gatidis, Sergios Botnar, René Prieto, Claudia Department of Diagnostic and Interventional Radiology Tübingen Germany The School of Biomedical Engineering and Imaging Sciences King's College London St. Thomas' Hospital London United Kingdom The Institute of Signal Processing and System Theory University of Stuttgart Stuttgart Germany The School of Biomedical Engineering ShanghaiTech University Shanghai China Electronic and Telecommunications Eng RMIT University Melbourne Australia The Department of Electronic Engineering Chinese University Hong Kong Hong Kong

Physiological motion, such as cardiac and respiratory motion, during Magnetic Resonance (MR) image acquisition can cause image artifacts. Motion correction techniques have been proposed to compensate for these types of motion during thoracic scans, relying on accurate motion estimation from undersampled motion-resolved reconstruction. A particular interest and challenge lie in the derivation of reliable non-rigid motion fields from the undersampled motion-resolved data. Motion estimation is usually formulated in image space via diffusion, parametric-spline, or optical flow methods. However, image-based registration can be impaired by remaining aliasing artifacts due to the undersampled motion-resolved reconstruction. In this work, we describe a formalism to perform non-rigid registration directly in the sampled Fourier space, i.e. k-space. We propose a deep-learning based approach to perform fast and accurate non-rigid registration from the undersampled k-space data. The basic working principle originates from the Local All-Pass (LAP) technique, a recently introduced optical flow-based registration. The proposed LAPNet is compared against traditional and deep learning image-based registrations and tested on fully-sampled and highly-accelerated (with two undersampling strategies) 3D respiratory motion-resolved MR images in a cohort of 40 patients with suspected liver or lung metastases and 25 healthy subjects. The proposed LAPNet provided consistent and superior performance to image-based approaches throughout different sampling trajectories and acceleration factors. © 2021, CC BY.

关键词： Magnetic resonance imaging

HASN:A Hierarchical Attack Surface Network for system Security Analysis

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China Communications 2019年第5期16卷 137-157页

作者： Kangyu Huang Lin Yang Renfang Fu Shengli Zhou Zheng Hong College of Command and Control Engineering Army Engineering UniversityNanjing 210007China China Electronic Equipment & System Engineering Corporation Beijing 100141China State Grid Jiangsu Electric Power Company Research Institute Nanjing 210019China Information Department of Zhejiang Police College Hangzhou 310053China

Attack surfaces, as one of the security models, can help people to analyse the security of systems in cyberspace, such as risk assessment by utilizing various security metrics or providing a cost-effective network hardening solution. Numerous attack surface models have been proposed in the past decade,but they are not appropriate for describing complex systems with heterogeneous components. To address this limitation, we propose to use a two-layer Hierarchical Attack Surface Network(HASN) that models the data interactions and resource distribution of the system in a component-oriented view. First, we formally define the HASN by extending the entry point and exit point framework. Second, in order to assess data input risk and output risk on the HASN, we propose two behaviour models and two simulation-based risk metrics. Last, we conduct experiments for three network systems. Our experimental results show that the proposed approach is applicable and effective.

关键词： attack surface security analysis security model risk assessment

Cache-Assisted Content Delivery for NOMA-Based Satellite-Edge-Terminal Cooperation Networks

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Cache-Assisted Content Delivery for NOMA-Based Satellite-Edg...

IEEE Conference on Global Communications (GLOBECOM)

作者： Chao Fang Hang Xu Yingshan Li Haofei Xie Shu-Ming Tseng Zheng Yang Deze Zeng Faculty of Information Technology Beijing University of Technology Beijing China Purple Mountain Laboratories Nanjing China Key Laboratory of Industrial Internet of Things & Networked Control Chongqing University of Posts and Telecommunications Chongqing China Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education Fujian Normal University Fuzhou China School of Computer Science China University of Geosciences Wuhan China

To satisfy differentiated service requirements of delay-sensitive and computing-intensive tasks in satellite communication networks, we propose a cache-assisted low-latency content distribution scheme in multi-cell multi-carrier nonorthogonal multiple access (MCMC-NOMA)-based satellite-edge-terminal cooperation environments. In the paper, a delay minimization problem is formulated to achieve optimal content distribution by jointly optimizing the allocation of subchannels and transmit power, which is decomposed and solved in each slot by using many-to-one matching and successive convex approximation, respectively. Simulation results show that the proposed model significantly improve network latency and content distribution in comparison to its existing counterparts in cloud-edge-terminal cooperation networks.

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Pmu-Based Real-Time Distribution system State Estimation Considering Anomaly Detection, Discrimination and Identification

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SSRN

SSRN 2022年

作者： Popov, Marjan Veerakumar, Nidarshan Ćetenović, Dragan Kongurai, Krit Jongepier, Arjen Terzija, Vladimir Delft University of Technology Faculty of EEMCS Mekelweg 4 Delft2628CD Netherlands The Department of Electrical & Electronic Engineering The University of Manchester Manchester United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Svetog Save 65 Čačak32000 Serbia Stedin B.V. Netherlands Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan250061 China

In this paper, a real-time state estimation platform for distribution grids monitored by Phasor Measurement Units (PMUs) is developed, tested, and validated using Real TimeDigital Simulator (RTDS). The developed platform serves as a proof-of-concept for potential implementation in an existing 50 kV ring network of the Dutch distribution utility Stedin medium voltage distribution grid located in the southwest (Zeeland area) of the Netherlands. To catch up with the fast sampling rates of PMUs, the platform incorporates computationally efficient techniques for state estimation and detection, discrimination and identification of anomalies like bad data and sudden load changes. Forecasting Aided State Estimation has been utilized to enable measurement innovations needed for fast anomaly detection, discrimination, and identification, whilst the Extended Kalman Filter (EKF) algorithm is selected to provide fast state forecasting and filtering. The platform has been tested under various normal and abnormal operating conditions considering different statistical properties of measurement noise as well as different bad data and sudden load change scenarios. To demonstrate advantages and disadvantages for embedding EKF into the platform, EKF is compared with Unscented Kalman Filter (UKF) in terms of estimation accuracy, computation efficiency, and compatibility with the module for anomaly detection, discrimination, and identification. The results of extensive simulations provide good hints about the feasibility of PMU-based real-time state estimation for the Stedin distribution grid. © 2022, The Authors. All rights reserved.

关键词： State estimation

Inverse linear-quadratic discrete-time finite-horizon optimal control for indistinguishable homogeneous agents: a convex optimization approach

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arXiv 2021年

作者： Zhang, Han Ringh, Axel Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Mathematical Sciences Chalmers University of Technology University of Gothenburg Gothenburg41296 Sweden

The inverse linear-quadratic optimal control problem is a system identification problem whose aim is to recover the quadratic cost function and hence the closed-loop system matrices based on observations of optimal trajectories. In this paper, the discrete-time, finite-horizon case is considered, where the agents are also assumed to be homogeneous and indistinguishable. The latter means that the agents all have the same dynamics and objective functions and the observations are in terms of "snap shots" of all agents at different time instants, but what is not known is "which agent moved where" for consecutive observations. This absence of linked optimal trajectories makes the problem challenging. We first show that this problem is globally identifiable. Then, for the case of noiseless observations, we show that the true cost matrix, and hence the closed-loop system matrices, can be recovered as the unique global optimal solution to a convex optimization problem. Next, for the case of noisy observations, we formulate an estimator as the unique global optimal solution to a modified convex optimization problem. Moreover, the statistical consistency of this estimator is shown. Finally, the performance of the proposed method is demonstrated by a number of numerical examples. Copyright © 2021, The Authors. All rights reserved.

关键词： Convex optimization

The Medium Energy X-ray telescope (ME) onboard the Insight-HXMT astronomy satellite

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Science China(Physics,Mechanics & Astronomy) 2020年第4期63卷 35-48页

作者： XueLei Cao WeiChun Jiang Bin Meng WanChang Zhang Tao Luo Sheng Yang ChunLei Zhang YuDong Gu Liang Sun XiaoJing Liu JiaWei Yang Xian Li Ying Tan ShaoZhen Liu YuanYuan Du FangJun Lu YuPeng Xu Ju Guan ShuangNan Zhang HuanYu Wang TiPei Li ChengMo Zhang XiangYang Wen JinLu Qu LiMing Song XiaoBo Li MingYu Ge YuPeng Zhou ShaoLin Xiong Shu Zhang YongJie Zhang ZeHao Cheng Fei Zhang MaoShun Li XiaoHua Liang Min Gao EnBo Yang XiaoHang Liu HongWei Liu YiJung Yang Fan Zhang Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China Department of Engineering Physics Tsinghua UniversityBeijing 100084China Beijing Key Laboratory of Space Thermal Control Technology Beijing Institute of Spacecraft System EngineeringBeijing 100094China Department of Modern Physics School of Physical SciencesUniversity of Science and Technology of ChinaHefei 230022China School of Physical Sciences Guizhou UniversityGuivang 550025China School of Opto-Electronic Information Science and Technology Yantai UniversityYantai 264005China University of Chinese Academy of Sciences Beijing 100049China

The Medium Energy X-ray telescope(ME) is one of the three main telescopes on board the Insight hard X-ray modulation telescope(Insight-HXMT) astronomy satellite. ME contains 1728 pixels of Si-PIN detectors sensitive in 5-30 ke V with a total geometrical area of 952 cm^2. The application specific integrated circuit(ASIC) chip, VA32TA6, is used to achieve low power consumption and low readout noise. The collimators define three kinds of field of views(FOVs) for the telescope, 1°×4°, 4°×4°,and blocked ones. Combination of such FOVs can be used to estimate the in-orbit X-ray and particle background *** energy resolution of ME is ~3 ke V at 17.8 ke V(FWHM) and the time resolution is 255 μs. In this paper, we introduce the design and performance of ME.

关键词： Si-PIN ASIC medium energy X-ray

Research on a new hysteresis control technology for flexible high-voltage direct current transmission 2

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Research on a new hysteresis control technology for flexible...

2nd IEEE International Conference on Automation, electronics and Electrical engineering, AUTEEE 2019

作者： Zhang, Dian Qin, Qingliang Wang, Bo College of Automation Electronic Engineering Qingdao University of Science Technology Qingdao China China National Automation Control System Corp Engineering Department Beijing China

ISBN: (纸本)9781728150291

The nearest level approximation control algorithm (nlm) is employed for multi-level multi-module (mmc) in the flexible high-voltage direct current (hdvc) converter. The decimal part of this algorithm needs to input sine digital pulse width modulator (dpwm), however, since the dpwmis too sensitive and less stable, the output digital pulse becomes too narrow and the digital signal frequency changes too fast. In order to solve the multilevel problems of the inverter frequency operation, the hysteretic Schmidt comparison method is proposed to meet the requirement of precision. This method can not only ensure the stability of the output digital signal, but also can adjust the hysteretic Schmidt trigger threshold, obtain more ideal digital pulse width which reduces the digital signal output frequency and make digital output signals stable and the pulse width, the grading sorting algorithm and guarantee the reduction of the output control pulse frequency. The feasibility of the method is verified through simulation and the actual running results of this method in field-programmable gate array (fpga) show that the study of nlm control algorithm can optimize the flexible hvdc control requirements. © 2019 IEEE.

关键词： HVDC power transmission