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A survey on user-centric cell-free massive MIMO systems

Digital Communications and Networks 2022年第5期8卷 695-719页

作者： Shuaifei Chen Jiayi Zhang Jing Zhang Emil Björnson Bo Ai School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong UniversityBeijing100044China Department of Computer Science KTH Royal Institute of TechnologySE-16440KistaSweden Department of Electrical Engineering(ISY) Linköping UniversitySE-58183LinköpingSweden State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing100044China

The mobile data traffic has been exponentially growing during the last several *** was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UDN))and/or the increased number of active antennas per Access Point(AP)(i.e.,massive Multiple-Input Multiple-Output(mMIMO)).However,neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation(6G)wireless communications due to the inter-cell interference and large quality-of-service ***-Free(CF)mMIMO,which combines the best aspects of UDN and mMIMO,is viewed as a key solution to this *** such systems,each User Equipment(UE)is served by a preferred set of surrounding APs *** this paper,we provide a survey of the state-of-the-art literature on CF *** a starting point,the significance and the basic properties of CF mMIMO are *** then present the canonical framework to discuss the essential details(i.e.,transmission procedure and mathematical system model).Next,we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and *** that,we discuss the practical issues in implementing CF mMIMO and point out the potential future ***,we conclude this paper with a summary of the key lessons learned in this field.

关键词： 6G network User-centric cell-free network Massive multiple-input multiple-output

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Sequential generation of self-starting diverse operations in all-fiber laser based on thulium-doped fiber saturable absorber

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Chinese Physics B 2022年第6期31卷 87-90页

作者： Pei Zhang Kaharudin Dimyati Bilal Nizamani Mustafa M.Najm S.W.Harun School of Electrical and Information Engineering Huaihua UniversityHuaihua 418008China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua 418008China Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Advanced Technology and Multidiscipline Airlangga UniversitySurabaya 60115Indonesia Institute of Computer Science and Digital Innovation UCSI UniversityKuala LumpurMalaysia

Self-starting Q-switching,Q-switched mode-locking and mode-locking operation modes are achieved sequentially in an all-fiber erbium-doped fiber laser with thulium-doped fiber saturable absorber for the first *** central wavelengths of Q-switching,Q-switched mode-locking and mode-locking operation modes are 1569.7 nm,1570.9 nm,and 1572 nm,*** mode-locking operation of the proposed fiber laser generates stable dark soliton with a repetition rate of 0.99 MHz and signal-to-noise ratio of 65 *** results validate the capability of generating soliton pulse by doped fiber saturable ***,the proposed fiber laser is beneficial to the applications of optical communication and signal processing system.

关键词： all-fiber laser Q-switched mode-locking dark soliton fiber saturable absorber

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Perimeter Defense using a Turret with Finite Range and Service Times

arXiv

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arXiv 2023年

作者： Bajaj, Shivam Bopardikar, Shaunak D. Moll, Alexander Von Torng, Eric Casbeer, David W. Department of Electrical and Computer Engineering Michigan State University United States Department of Computer Science and Engineering Michigan State University United States Control Science Center Air Force Research Laboratory United States

We consider a perimeter defense problem in a planar conical environment comprising a single turret that has a finite range and non-zero service time. The turret seeks to defend a concentric perimeter against N ≥ 2 intruders. Upon release, each intruder moves radially towards the perimeter with a fixed speed. To capture an intruder, the turret’s angle must be aligned with that of the intruder’s angle and must spend a specified service time at that orientation. We address offline and online versions of this optimization problem. Specifically, in the offline version, we establish that in general parameter regimes, this problem is equivalent to solving a Travelling Repairperson Problem with Time Windows (TRP-TW). We then identify specific parameter regimes in which there is a polynomial time algorithm that maximizes the number of intruders captured. In the online version, we present a competitive analysis technique in which we establish a fundamental guarantee on the existence of at best (N − 1)-competitive algorithms. We also design two online algorithms that are provably 1 and 2-competitive in specific parameter regimes. © 2023, CC BY-NC-SA.

关键词： Polynomial approximation

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Intelligent PID controller Based on Deep Reinforcement Learning

Intelligent PID Controller Based on Deep Reinforcement Learn...

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Robotics, control and Automation (ICRCA), International Conference on

作者： Yinhe Zhai Qiang Zhao Yinghua Han Jinkuan Wang Wenying Zeng College of Information Science and Engineering Northeastern University Shenyang China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao China

ISBN: (数字)9798350344721

ISBN: (纸本)9798350344738

PID control is still the most important and popular method in industrial control at present. PID control is easy to achieve and it can improve the steady-state performance and dynamic performance of the system. PID controller can be used for all objects, however, it has some problems with parameter adjustment and control effect. The proportional integral differential coefficient of PID control is fixed, and it can't change when disturbed, so the stability of the system will be affected. Moreover, PID control is prone to overshoot and can't be used in specific systems. Reinforcement learning (RL) algorithms have developed rapidly from discrete action to continuous action in recent years. It has aroused the high interest of researchers in the field of automatic control. RL control performs better in the degree of intelligence and dynamic performance, however, the steady-state performance is poor. The sensitive response of RL control will damage the actuator. In this paper, an adaptive PID controller based on deep reinforcement learning is proposed. By designing reward values, the desired control effect is described. In this way, an agent is trained to provide parameters to the PID controller in real time. It can improve the response speed of the system, suppress overshoot, and have a certain anti-disturbance ability by training the agent to achieve real-time PID parameter adjustment.

关键词： Training PI control Heuristic algorithms Industrial control Deep reinforcement learning Real-time systems Steady-state

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Grey Wolf Algorithm for Human-Robot Collaborative Disassembly Line Balancing Problem Subject to Dangerous Components 19

Grey Wolf Algorithm for Human-Robot Collaborative Disassembl...

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19th IEEE International Conference on Networking, Sensing and control, ICNSC 2022

作者： Li, Chong Guo, Xi Wang Wang, Jiacun Qin, Shujin Qi, Liang Tang, Ying Liaoning Petrochemical University Artificial Intelligence and Software Fushun China Information and Control Liaoning Petrochemical University Monmouth University United States Monmouth University Computer Science and Software Engineering West Long Branch United States Shangqiu Normal University Economics and Management Shangqiu China Shandong University of Science and Technology Computer Intelligent Science and Technology Qingdao China Roman University Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9781665472432

Disassembly is a critical remanufacturing process to obtain reusable components from discarded products. Due to the limitation of disassembly by humans or robots alone, the human-robot collaborative disassembly method is used to obtain components. Three types of components are considered in this paper: dangerous, delicate and normal. Robots disassemble dangerous components, humans disassemble delicate components, and both humans and robots can disassemble normal components. A mathematical model that maximizes disassembly profit is established. An improved gray wolf optimizer algorithm to solve the single-product disassembly line balancing problem is proposed. The algorithm is compared with the migratory bird optimization algorithm and the brain storming optimization algorithm to test its performance. Experimental results show that the proposed algorithm has a faster convergence speed. © 2022 IEEE.

关键词： Profitability

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Headmotion: Human-Machine Interaction Requires Only Your Head Movement 2nd

Headmotion: Human-Machine Interaction Requires Only Your Hea...

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2nd EAI International Conference on Edge Computing and IoT: Systems, Management and Security, ICECI 2021

作者： Xu, Duoteng Zhu, Peizhao Zheng, Chuyu College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518061 China College of Computer Science and Software Engineering Shenzhen University Guangdong Shenzhen518061 China College of Electronics and Information Engineering Shenzhen University Guangdong Shenzhen518061 China

ISBN: (纸本)9783031042300

With increasing demand for smart wearable devices and the booming development of pervasive computing, more and more new human-computer interaction methods for wearable devices are proposed to make up for the shortcomings of traditional wearable device interaction methods and improve the efficiency and ubiquity of interaction. Up to now, the human-computer interaction of wearable devices is still dominated by contact interactions, such as touching the screen and pressing physical buttons. This interaction method is convenient in most scenarios, but there are limitations in some situations, such as disabled people cannot use their hands for human-computer interaction, and drivers are not suitable for touch interaction with their hands when driving. To address this shortcoming, we designed a natural interaction system for ear-worn smart devices, which includes a deep network recognition model based on acceleration, angular velocity and angle data of head motion collected by inertial units worn on the ear. The interaction system now can realize human-computer interaction of head motion in various complex scenarios, which greatly liberates the user’s hands. We have experimentally verified the excellent accuracy and real-time performance of our designed system. © 2022, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Human computer interaction

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A Data Transmission Approach Based on Ant Colony Optimization and Threshold Proxy Re-encryption in WSNs

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Journal of Artificial Intelligence and Technology 2022年第1期2卷 23-31页

作者： Jing Liu Zenghui Liu Chenyu Sun Junxi Zhuang College of Computer Science Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of EducationBeijing 100124China College of Automation Engineering Beijing PolytechnicBeijing 100176China

Wireless sensor networks(WSNs)have become increasingly popular due to the rapid growth of the Internet of *** open wireless transmission media are easy to attack,security is one of the primary design concerns for *** solutions consider routing and data encryption as two isolated issues,providing incomplete ***,in this paper,we divide the WSN communication process into a data path selection phase and a data encryption *** propose an improved transmission method based on ant colony optimization(ACO)and threshold proxy re-encryption for WSNs,and we named it as *** method resists internal and external attacks and ensures safe and efficient data *** the data path selection stage,the ACO algorithm is used for network *** improvement of the pheromone concentration is *** order to resist attacks from external attackers,proxy re-encryption is extended to WSN in the data encryption *** threshold secret sharing algorithm is introduced to generate a set of re-encryption key fragments composed of random numbers at the source *** confirm the performance of our model via simulation studies.

关键词： wireless sensors network ant colony optimization pheromone proxy re-encryption threshold

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Development of control Strategies for an Industrial Robot to Increase Energy Efficiency

Development of Control Strategies for an Industrial Robot to...

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International Symposium for Design and Technology of Electronics Packages (SIITME)

作者： Marius - Alexandru Dobrea Mihaela Vasluianu Giorgian Neculoiu Gabriela-Valentina Olteanu Mihaela-Gabriela Boicu Eduard Vârlan Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Bucharest Romania Faculty of Hidrotechnics Technical University of Civil Engineering of Bucharest Bucharest Romania

ISBN: (数字)9798331539511

ISBN: (纸本)9798331539528

The paper aims to optimize the energy consumption of industrial robots, with the goal of reducing operational costs and improving the sustainability of the production process. The methods discussed include using energy-efficient components, reducing idle times, and optimizing robot trajectory programming to minimize unnecessary movements. The project presents a simulation of an industrial process for sorting and depalletizing parts using a KUKA KR 4 Agilus robot, along with Arduino development boards for control and coordination. A color sensor system is employed for object detection, optimizing the robot’s movements based on the data collected. To analyze energy and time efficiency, two movement routines were compared: one based on SLIN and the other on SPTP.

关键词： Energy consumption Service robots Robot kinematics Production Programming Robot sensing systems Industrial robots Energy efficiency Trajectory Sustainable development

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Dynamic Multi-Task Interactive Evolutionary Optimization Algorithm with Search Space Alignment

Dynamic Multi-Task Interactive Evolutionary Optimization Alg...

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Congress on Evolutionary Computation

作者： Weidong Wu Xiaoyan Sun Yong Zhang Wei Song School of Information and Control Engineering China University of Mining and Technology Xuzhou China School of Artifical Intelligence and Computer Science Jiangnan University Wuxi China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

The interactive evolutionary multi-task optimization approach assisted by surrogate models has proven successful in enhancing individualized recommendation performance. However, in light of the dynamically changing user preferences, it becomes imperative to further develop more powerful knowledge sharing strategy to improve the interactive multi-task optimization efficiency. A probability model-assisted search space alignment among multiple tasks method is proposed for knowledge transfer across multi-task environment. Additionally, a diversity maintaining mechanism of the transferred population is proposed to improve the quality and diversity of the initial population in a preference varied multi-task environment. The research demonstrates the effectiveness of the proposed approach in achieving effective knowledge transfer across multi-task environmen. Furthermore, the utilization of a high-quality initial population not only enhances the evolutionary search efficiency of the algorithm but also significantly improves the accuracy, diversity., and novelty of personalized recommendation.

关键词： Adaptation models Accuracy Heuristic algorithms Sociology Evolutionary computation Multitasking Statistics

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Rollout-Based Interactive Motion Planning for Automated Vehicles *

Rollout-Based Interactive Motion Planning for Automated Vehi...

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International Conference on Intelligent Transportation

作者： Ning Wang Xiao Chen Jonas Mårtensson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Longitudinal and lateral motion planning poses a significant challenge to achieving full autonomy in automated vehicles. This work focuses on studying the motion planning problem for automated vehicles specifically in a highwaymerging scenario. The problem is modeled as an infinite horizon optimal control problem, taking into account finite control sets for the ego agents and uncontrolled state components of surrounding traffic. For this type of control problem, obtaining a real-time solution that meets both high safety and efficiency requirements can be difficult. In this study, we employ the rollout approach, which involves online optimization following the simulation of a known baseline policy instead of relying solely on extensive offline training. We compare the performance of one and multistep lookahead rollout algorithms against several state-of-the-art benchmark policies in simulation. The simulation results indicate that the rollout algorithm significantly enhances safety while simultaneously maintaining a high average speed within the merging scenario. Furthermore, we conduct simulation studies to assess the rollout methods in adapting to varying behaviors of surrounding vehicles. Additionally, we investigate the impact of different horizon settings and the introduction of terminal cost approximation.

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