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IEEE International Conference on Unmanned systems (ICUS)

作者： Yihan Zhao Xuting Duan Jianshan Zhou Long Zhang State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory School of Transportation Science and Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time.

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DOA Estimation for Coherent Multipath Signals with Covariance Matrix Reconstruction in Hybrid Massive Circular Array 1

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5th International Conference on Electrical Engineering and information Technologies for Rail Transportation, EITRT 2021

作者： Wu, Xinmeng Sun, Xiaofang Ding, Jianwen Lu, Xiaotong Zhong, Zhangdui Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China National Research Center of Railway Safety Assessment Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beiing Jiaotong University Beijing100044 China China State Railway Group Co. Ltd Beijing China

ISBN: (数字)9789811699092

ISBN: (纸本)9789811699085

Hybrid massive multiple-input multiple-output (MIMO) is regarded as a promising and economic technique to improve the spectral efficiency. However, regarding to the direction of arrival (DOA) estimation, the spatial covariance matrix cannot be obtained by conventional sample average algorithm in hybrid massive MIMO systems. Besides, the performance of DOA estimation can be affected dramatically by the multipath especially in railway scenarios. To address these issues, this paper proposes a two-dimensional (2-D) DOA estimation method based on covariance matrix reconstruction for coherent signals in hybrid massive MIMO systems, which combine the large circular antenna array with one-dimensional digital processing. We first carry out the coherent preprocessing by dividing the massive uniform-circular-arrays (UCAs) into four subarrays. Moreover, each submatrix is reconstructed and the arithmetic average of the reconstructed covariance matrices is calculated. Then, multiple signal classification (MUSIC) algorithm is introduced for the DOA estimation. Finally, the numerical results demonstrate that the proposed approach achieves a profound precision over the existing ones. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Spectrum efficiency

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Adaptive Data Collaboration Based on Multi-Agent Reinforcement Learning in Internet of Things

Adaptive Data Collaboration Based on Multi-Agent Reinforceme...

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IEEE International Conference on communications Workshops, ICC

作者： Yatong Wang Yunjie Li Fengsheng Wei Gang Feng School of Information and Electronics Beijing Institute of Technology Beijing China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China National Key Lab. on Communications and Yangtze Delta Region Institute (Huzhou) University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

Decentralized Federated Learning (DFL) has become a prominent privacy-preserving data collaboration paradigm in Internet of Things (IoT), crucial for advancing Artificial Intelligence applications. However, the intricate dynamics of wireless environments and the heterogeneity among collaborative IoT nodes present great challenges to the learning efficiency of conventional DFL processes. Therefore, the development of an adaptive collaboration strategy of heterogeneous nodes is of prominent importance to facilitate efficient DFL in IoT networks. In this paper, we introduce an adaptive data collaboration mechanism based on multi-agent reinforcement learning (MADC) that enables heterogeneous nodes to learn tailored collaboration strategies in dynamic IoT networks. In MADC design, we tackle inherent challenges such as vast action space and overestimation by proposing the mean filed representation and dual critic network-based approximation methods. Extensive numerical results demonstrate that the proposed MADC outperforms in terms of model accuracy, learning efficiency, and communication cost compared to baselines.

关键词： Wireless communication Adaptive systems Costs Accuracy Federated learning Conferences Collaboration

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Novel algorithm for communication signal blind separation-EASIBSA algorithm

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Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of technology 2008年第1期30卷 91-94页

作者： Fu, Wei-Hong Yang, Xiao-Niu Liu, Nai-An Zeng, Xing-Wen State Key Lab. of Integrated Service Networks Xidian University Xi'an 710071 China National Laboratory of Information Control Technology for Communication System Jiangnan Electronic Communications Research Institute Jiaxing 314033 China

Aim at the problem of the communication signal blind source separation, a novel blind separation algorithm based on step size adaptation (EASIBSA) to increase the convergence rate of the separation algorithm was present by using the idea of parameter adaptation optimization, which was based on Equivariant Adaptive Separation via Independent (EASI) algorithm. This algorithm related the learning rate with the object function and adapted it by using the stochastic gradient method, which avoided the selection of optimum learning rate and speed up the convergence rate. Simulation results showed that improved algorithm could increase the convergence rate of separation algorithm by two times without affecting the separation capability.

关键词： Blind source separation Convergence rate Digital communication Parameter adaptation

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A Novel Channel Estimation Scheme for Frequency-Selective mmWave Massive MIMO systems

A Novel Channel Estimation Scheme for Frequency-Selective mm...

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International Conference on Wireless communications and Signal Processing (WCSP)

作者： Zhigang Song Jian Sun Wensheng Zhang Cheng-Xiang Wang Minggao Zhang Shandong Provincial Key Lab of Wireless Communication Technologies School of Information Science and Engineering Shandong University Qingdao China The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing China National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

In this paper, a two-stage channel estimation scheme is presented for frequency-selective millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with hybrid precoding. Specifically, at the first stage, likelihood function with respective to the channel angle of departure (AoD) and angle of arrival (AoA) are maximized by the deterministic maximum likelihood (DML) estimator to obtain a coarse channel estimate. At the second stage, a space-alternating generalized expectation-maximization (SAGE) based algorithm is proposed to refine the channel parameters. In addition, an angle paring scheme is proposed to paired the AoA and AoD. Simulation results show the better performance of the proposed method.

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing

On the Approximation of the Quotient of Two Gaussian Densiti...

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International Conference on information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Yanbo Xue Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Career Science Lab Beijing China

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target.

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Ray Tracing Based Sub-6 GHz Wireless Channel Characteristics Analysis in Underground Garage Environments

Ray Tracing Based Sub-6 GHz Wireless Channel Characteristics...

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IEEE International Conference on Electronics and Communication Engineering (ICECE)

作者： Xiaole Li Cuiping Zhang Jian Sun Wensheng Zhang Cheng-Xiang Wang Shandong Provincial Key Lab of Wireless Communication Technologies School of Information Science and Engineering Shandong University Qingdao China Shandong Provincial Key Lab of Wireless Communication Technologies Shandong University Qingdao China The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing China National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

ISBN: (纸本)9781728188577

Indoor hot spots is a major deployment scenario of the fifth generation (5G) network. In the indoor scenario, the radio wave propagation characteristics of underground garages are still not fully understood. In addition, Sub-6 GHz band is the main frequency band used in domestic 5G networks recently. This paper mainly uses ray tracing to study the wireless channel characteristics in the scenario of underground garage under Sub6 GHz frequency band. Firstly, a three-dimensional (3D) simulation scenario is built, and the channel simulation is carried out at 3.5 GHz frequency band. According to the simulation data, the results shows that the path loss index is smaller than that in the 3GPP indoor scenario. Then, the channel data of Sub-6 GHz continuous frequency band is simulated at 500 MHz interval, the influence of material properties on channel characteristics is studied. We find that the path loss increases while the distance between the transmitter (Tx) and receiver (Rx) increases, and the change is obvious at a long distance with increasing frequency.

关键词： Wireless communication Solid modeling Three-dimensional displays 5G mobile communication Radio transmitters Receivers Ray tracing

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On the Gaussian Filtering for Nonlinear Dynamic systems Using Variational Inference

On the Gaussian Filtering for Nonlinear Dynamic Systems Usin...

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International Conference on information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Ji Li Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Locaris Electronic Technology Co. Ltd Zhengzhou China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper introduces a new variational Gaussian filtering approach for estimating the state of a nonlinear dynamic system. We first assume that the predictive distribution of the state is Gaussian and derive an iterative method for updating the state posterior in the natural parameter space through KullbackLeibler divergence minimization. The obtained update rule is the same as that of the conjugate-computation variational inference technique in Bayesian learning. The derivation here is simpler and more insightful. We then impose a Wishart prior on the inverse of the state prediction covariance to take into account the impact of approximating the state predictive distribution using a Gaussian density on the state posterior estimation. The prediction covariance is identified jointly with the state using variational inference and the established state posterior update rule to achieve the desired Gaussian filtering. Simulation study examines the performance of the proposed filtering framework in target tracking based on bearing and range measurements.

关键词： Target tracking Smoothing methods Filtering Estimation Filtering algorithms Prediction algorithms Minimization Nonlinear dynamical systems Bayes methods Iterative methods

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Study on Modelling of a DC Coaxial Motor in Marine Applications

Study on Modelling of a DC Coaxial Motor in Marine Applicati...

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International Conference on system Science and Engineering (ICSSE)

作者： Nguyen Duc Thinh Duong Ngoc Quan Nguyen Tan Tien Do Xuan Phu Department of Electrical Engineering and Information Technology Vietnamese-German University Binh Duong Vietnam Institute of Engineering HUTECH University of Technology Ho Chi Minh city Vietnam National Key Laboratory of Digital Control and System Engineering Ho Chi Minh University of Technology Ho Chi Minh city Vietnam MediRobotic Lab. Vietnamese-German University Binh Duong Vietnam

The main goal of this paper studies modeling of a direct current coaxial motor (DCCM) and testing the main parameters of DCCM on the experimental model. The DCCM contains two rotors named inner runner and outer runner. The inner runner and the outer runner rotate in opposite directions to each other. The shaft of the inner runner and the shaft of the outer runner are coincident and inserted on two separate bearings. To prove this idea, the mathematic model is achieved by a combination of a mathematic model of DC motor and mathematic model of single phase coaxial motor. Simulation result of the mathematic model in Matlab shows the truth of the hypothesis of the design. The result of testing DCCM of the experimental model is fit to the result of simulation of DCCM in Matlab. Consequently, the DCCM can substitute for other kinds of propellers especially in marine applications.

关键词： DC motors Mathematical model Shafts Torque measurement Induction motors Torque

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Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison

arXiv

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arXiv 2022年

作者： Liu, Tianying Zhang, Lu Wang, Yang Guan, Jihong Fu, Yanwei Zhao, Jiajia Zhou, Shuigeng Department of Computer Science and Technology Tongji University Shanghai201804 China The Project Management Office of China National Scientific Seafloor Observatory Tongji University Shanghai200092 China Shanghai Key Lab of Intelligent Information Processing The School of Computer Science Fudan University Shanghai200438 China Shanghai Key Lab of Intelligent Information Processing The School of Data Science Fudan University Shanghai200433 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

The generic object detection (GOD) task has been successfully tackled by recent deep neural networks, trained by an avalanche of annotated training samples from some common classes. However, it is still non-trivial to generalize these object detectors to the novel long-tailed object classes, which have only few labeled training samples. To this end, the Few-Shot Object Detection (FSOD) has been topical recently, as it mimics the humans' ability of learning to learn, and intelligently transfers the learned generic object knowledge from the common heavy-tailed, to the novel long-tailed object classes. Especially, the research in this emerging field has been flourishing in recent years with various benchmarks, backbones, and methodologies proposed. To review these FSOD works, there are several insightful FSOD survey articles [58, 59, 74, 78] that systematically study and compare them as the groups of fine-tuning/transfer learning, and meta-learning methods. In contrast, we review the existing FSOD algorithms from a new perspective under a new taxonomy based on their contributions, i.e., data-oriented, model-oriented, and algorithm-oriented. Thus, a comprehensive survey with performance comparison is conducted on recent achievements of FSOD. Furthermore, we also analyze the technical challenges, the merits and demerits of these methods, and envision the future directions of FSOD. Specifically, we give an overview of FSOD, including the problem definition, common datasets, and evaluation protocols. The taxonomy is then proposed that groups FSOD methods into three types. Following this taxonomy, we provide a systematic review of the advances in FSOD. Finally, further discussions on performance, challenges, and future directions are presented. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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