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arXiv 2024年

作者： Zhu, Zhiyu Yang, Yang Chen, Mingzhe Guo, Caili Cheng, Julian Cui, Shuguang The Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Faculty of Applied Science School of Engineering The University of British Columbia KelownaBCV1V 1V7 Canada The Chinese University of Hong Kong Shenzhen518172 China

The growing demand for location-based services in areas like virtual reality, robot control, and navigation has intensified the focus on indoor localization. Visible light positioning (VLP), leveraging visible light communications (VLC), becomes a promising indoor positioning technology due to its high accuracy and low cost. This paper provides a comprehensive survey of VLP systems. In particular, since VLC lays the foundation for VLP, we first present a detailed overview of the principles of VLC. Then, we provide an in-depth overview of VLP algorithms. The performance of each positioning algorithm is also compared in terms of various metrics such as accuracy, coverage, and orientation limitation. Beyond the physical layer studies, the network design for a VLP system is also investigated, including multi-access technologies, resource allocation, and light-emitting diode (LED) placements. Next, the applications of the VLP systems are overviewed. Finally, this paper outlines open issues, challenges, and opportunities for the research field. In a nutshell, this paper constitutes the first holistic survey on VLP from state-of-the-art studies to practical uses. Copyright © 2024, The Authors. All rights reserved.

关键词： Resource allocation

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Spectrum efficiency maximization with trajectory design in UAV-enabled mobile relaying

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The Journal of China Universities of Posts and Telecommunications 2019年第4期26卷 17-24页

作者： Sun Chuanzhi Hu Zhiqun Wen Xiangming Lu Zhaoming Qi Hang Beijing Laboratory of Advanced Information Networks Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and TelecommunicationsBeijing 100876China School of Computer and Information Engineering Hubei UniversityWuhan 430062China

With the advantages of low cost and high mobility,unmanned aerial vehicles(UAVs)have played an important role in wireless *** investigate a UAV-enabled mobile relaying system,where a UAV is used as a mobile relay to assist in the communication from a ground source to a ground destination since their direct link is *** the conventional mobile relay in which the UAV adopts straight line or circular trajectory,we consider a more general elliptical trajectory and use realistic channel *** assuming that the UAV employs time-division duplexing(TDD)based decode-and-forward(DF)relaying,we jointly optimize the time allocations and the UAV trajectory to formulate the maximization of spectrum efficiency(SE).The simulation results show that the trajectory we designed achieves a higher SE than the optimal circular trajectory and static relaying.

关键词： UAV mobile relay time allocations elliptical trajectory

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Adaptive Information Bottleneck Guided Joint Source and Channel Coding for Image Transmission

arXiv

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arXiv 2022年

作者： Sun, Lunan Yang, Yang Chen, Mingzhe Guo, Caili Saad, Walid Poor, H. Vincent The Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Beijing Laboratory of Advanced Information Net works School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Wireless@VT Group Bradley Department of Electrical and Computer Engineering Virginia Tech ArlingtonVA United States The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Joint source and channel coding (JSCC) for image transmission has attracted increasing attention due to its robustness and high efficiency. However, the existing deep JSCC research mainly focuses on minimizing the distortion between the transmitted and received information under a fixed number of available channels. Therefore, the transmitted rate may be far more than its required minimum value. In this paper, an adaptive information bottleneck (IB) guided joint source and channel coding (AIB-JSCC) method is proposed for image transmission. The goal of AIB-JSCC is to reduce the transmission rate while improving the image reconstruction quality. In particular, a new IB objective for image transmission is proposed so as to minimize the distortion and the transmission rate. A mathematically tractable lower bound on the proposed objective is derived, and then, adopted as the loss function of AIB-JSCC. To trade off compression and reconstruction quality, an adaptive algorithm is proposed to adjust the hyperparameter of the proposed loss function dynamically according to the distortion during the training. Experimental results show that AIB-JSCC can significantly reduce the required amount of transmitted data and improve the reconstruction quality and downstream task accuracy. Copyright © 2022, The Authors. All rights reserved.

关键词： Economic and social effects

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Positioning Using Visible Light Communications: A Perspective Arcs Approach

arXiv

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arXiv 2022年

作者： Zhu, Zhiyu Guo, Caili Bao, Rongzhen Chen, Mingzhe Saad, Walid Yang, Yang The Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical Engineering Princeton University Princeton NJ08544 United States Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States

Visible light positioning (VLP) is an accurate indoor positioning technology that uses luminaires as transmitters. In particular, circular luminaires are a common source type for VLP, that are typically treated only as point sources for positioning, while ignoring their geometry characteristics. In this paper, the arc feature of the circular luminaire and the coordinate information obtained via visible light communication (VLC) are jointly used for positioning, and a novel perspective arcs approach is proposed for VLC-enabled indoor positioning. The proposed approach does not rely on any inertial measurement unit and has no tilted angle limitaion at the user. First, a VLC assisted perspective circle and arc algorithm (V-PCA) is proposed for a scenario in which a complete luminaire and an incomplete one can be captured by the user. Based on plane and solid geometry theory, the relationship between the luminaire and the user is exploited to estimate the orientation and the coordinate of the luminaire in the camera coordinate system. Then, the pose and location of the user in the world coordinate system are obtained by single-view geometry theory. Considering the cases in which parts of VLC links are blocked, an anti-occlusion VLC assisted perspective arcs algorithm (OA-V-PA) is proposed. In OA-V-PA, an approximation method is developed to estimate the projection of the luminaire's center on the image and, then, to calculate the pose and location of the user. Simulation results show that the proposed indoor positioning algorithm can achieve a 90th percentile positioning accuracy of around 10 cm. Moreover, an experimental prototype is implemented to verify the feasibility. In the established prototype, a fused image processing method is proposed to simultaneously obtain the VLC information and the geometric information. Experimental results in the established prototype show that the average positioning accuracy is less than 5 cm for different tilted angles of the user.

关键词： Visible light communication

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Deformation mechanism and collapse treatment of the rock surrounding a shallow tunnel based on on-site monitoring

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Journal of Mountain Science 2020年第12期17卷 2897-2914页

作者： QIU Hong-zhi CHEN Xiao-qing WU Qi-hong WANG Ren-chao ZHAO Wan-yu QIAN Ke-jiang School of Architecture and Civil Engineering Chengdu UniversityChengdu 610106China Key Laboratory of Mountain Hazards and Earth Surface Processes Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Hunan International Scientific and Technological Innovation Cooperation Base of Advanced Construction and Maintenance Technology of Highway Changsha University of Science&TechnologyChangsha 410114China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

When tunnels are constructed at shallow depths in areas with poor geological conditions,such as portal sections,valleys and hillsides in regions with granitic bedrock,considerable excavation-induced deformation of the surrounding rock may occur,potentially resulting in tunnel *** main reason for these problems is the lack of understanding of the deformation mechanism and evolution of the soft granitic rock surrounding the tunnel and the adoption of inappropriate construction technology and *** article analyzes the deformation mechanism of the rock surrounding a shallow tunnel based on in situ monitoring data as a case study and suggests that certain measures should be taken to effectively control the deformation of the surrounding rock and to minimize the potential for tunnel *** results show that the deformation of the granitic soil surrounding the tunnel can be divided into three stages:the rapid deformation stage,the slow deformation stage and the stabilization *** construction methods should be carefully selected to ensure safety during tunnel excavation in the first *** avoid secondary disasters caused by tunnel collapses,three treatment measures may be implemented as part of safety management:enhancing the monitoring of the surrounding rock deformation,adjusting the construction methods and optimizing the support *** particular,accurate monitoring data and timely information feedback play a vital role in tunnel ***,engineers with considerable engineering experience and professional knowledge are needed to analyze the monitoring data and make accurate predictions of tunnel deformation to ensure that reasonable measures are taken in the process of shallow tunnel excavation.

关键词： Shallow tunnel Surrounding rock deformation Field monitoring Treatment for collapse Information feedback

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High-performance parallel classical scheme for simulating shallow quantum circuits

arXiv

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arXiv 2021年

作者： Zhang, Shihao Bao, Jiacheng Sun, Yifan Li, Lvzhou Sun, Houjun Zhang, Xiangdong Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements of Ministry of Education Beijing Key Laboratory of Nanophotonics & Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Millimeter Wave and Terahertz Techniques School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China

Recently, constant-depth quantum circuits are proved more powerful than their classical counterparts at solving certain problems, e.g., the two-dimensional (2D) hidden linear function (HLF) problem regarding a symmetric binary matrix. To further investigate the boundary between classical and quantum computing models, in this work we propose a high-performance two-stage classical scheme to solve a full-sampling variant of the 2D HLF problem, which combines traditional classical parallel algorithms and a gate-based classical circuit model together for exactly simulating the target shallow quantum circuits. Under reasonable parameter assumptions, a theoretical analysis reveals our classical simulator consumes less runtime than that of near-term quantum processors for most problem instances. Furthermore, we demonstrate the typical all-connected 2D grid instances by moderate FPGA circuits, and show our designed parallel scheme is a practically scalable, high-efficient and operationally convenient tool for simulating and verifying graph-state circuits performed by current quantum hardware. © 2021, CC BY.

关键词： Timing circuits

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BTI Aging Monitoring based on SRAM Start-up Behavior

BTI Aging Monitoring based on SRAM Start-up Behavior

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Asian Test Symposium (ATS)

作者： Shengyu Duan Peng Wang Gaole Sai School of Computer Engineering and Science Shanghai University Shanghai China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (数字)9781728174679

ISBN: (纸本)9781728174686

Bias Temperature Instability (BTI) is one of the dominant CMOS aging mechanisms. It causes time-dependent variation, threatening circuit lifetime reliability. BTI-induced circuit errors are not detectable at the fabrication stage. On-line monitoring schemes are therefore necessary to capture the degradations during the operational time. Traditional aging monitoring techniques exhibit high implementation complexity and low stability. In this paper, we propose a BTI monitoring approach by simply tracking the start-up behavior of SRAM cells. SRAM is a widely used on-chip device in many applications. We study the impact of BTI for SRAM start-up values and age some cells in a manipulated manner. The BTI degradation is evaluated based on the number of SRAM cells starting with a certain value. This technique can be used to estimate the degradation for on-chip logic circuits without introducing additional circuitry, and thus has very low implementation complexity. We use an SRAM array with 1024 cells to estimate the degradations for multiple logic circuits, and show the average mean absolute percentage error as 8.48%. In addition, this technique is robust considering process, voltage and temperature variations.

关键词： Degradation Monitoring Logic circuits Transistors SRAM cells Aging System-on-chip

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Lightdet: A Lightweight and Accurate Object Detection Network

Lightdet: A Lightweight and Accurate Object Detection Networ...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Qiankun Tang Jie Li Zhiping Shi Yu Hu Research Center for Intelligent Computing Systems State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing Advanced Innovation Center for Imaging Theory and Technology Capital Normal University

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

The extensive computational burden limits the usage of accurate but complex object detectors in resource-bounded scenarios. In this paper, we present a lightweight object detector, named LightDet, to address this dilemma. We design a lightweight backbone that is able to capture rich low-level features by the proposed Detail-Preserving Module. To effectively aggregate bottom and top-down features, we introduce an efficient Feature-Preserving and Refinement Module. A lightweight prediction head is employed to further reduce the entire network complexity. Experimental results show that our LightDet achieves 75.5% mAP on PASCAL VOC 2007 at the speed of 250 FPS and 24.0% mAP on MS COCO dataset.

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Distributed reinforcement learning for age of information minimization in real-time IoT systems

arXiv

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arXiv 2021年

作者： Wang, Sihua Chen, Mingzhe Yang, Zhaohui Yin, Changchuan Saad, Walid Cui, Shuguang Poor, H. Vincent The Beijing Laboratory of Advanced Information Network The Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States The Department of Engineering King’s College London WC2R 2LS United Kingdom The Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States Chinese University of Hong Kong Shenzhen518172 China

In this paper, the problem of minimizing the weighted sum of age of information (AoI) and total energy consumption of Internet of Things (IoT) devices is studied. In the considered model, each IoT device monitors a physical process that follows nonlinear dynamics. As the dynamics of the physical process vary over time, each device must find an optimal sampling frequency to sample the real-time dynamics of the physical system and send sampled information to a base station (BS). Due to limited wireless resources, the BS can only select a subset of devices to transmit their sampled information. Thus, edge devices must cooperatively sample their monitored dynamics based on the local observations and the BS must collect the sampled information from the devices immediately, hence avoiding the additional time and energy used for sampling and information transmission. To this end, it is necessary to jointly optimize the sampling policy of each device and the device selection scheme of the BS so as to accurately monitor the dynamics of the physical process using minimum energy. This problem is formulated as an optimization problem whose goal is to minimize the weighted sum of AoI cost and energy consumption. To solve this problem, we propose a novel distributed reinforcement learning (RL) approach for the sampling policy optimization. The proposed algorithm enables edge devices to cooperatively find the global optimal sampling policy using their own local observations. Given the sampling policy, the device selection scheme can be optimized thus minimizing the weighted sum of AoI and energy consumption of all devices. Simulations with real data of PM 2.5 pollution show that the proposed algorithm can reduce the sum of AoI by up to 17.8% and 33.9% and the total energy consumption by up to 13.2% and 35.1%, compared to a conventional deep Q network method and a uniform sampling policy. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy utilization

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A novel deep learning model based on YOLOv5 optimal method for coal gangue image recognition

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Scientific Reports 2025年第1期15卷 1-10页

作者： Tongkai Gu Yasheng Chang Feihan Cao Haiyan Zhao Sitong Yan Wei Liu School of Mechanical and Electrical Engineering Xi’an University of Architecture and Technology Xi’an 710055 China School of Optical and Electronic Information & Suzhou Key Laboratory of Biophotonics & International Joint Metacenter for Advanced Photonics and Electronics Suzhou City University Suzhou 215104 China School of Architecture & Design Kunshan Dengyun College of Science and Technology Suzhou 215300 China School of Computer Science and Technology Soochow University Suzhou 215006 China School of Optoelectronic Information Engineering Soochow University Suzhou 215006 China

Coal gangue recognition presents significant challenges in the mining industry due to its inefficient and costly traditional treatment methods. The advent of deep learning techniques has introduced novel solutions for automating and online coal gangue processing. Despite the potential of deep learning models, challenges such as overfitting and the need for extensive labeled datasets hinder their effectiveness. You Only Look Once version 5 (YOLOv5), with its rapid inference speed and high accuracy, offers a suitable solution for real-time coal gangue detection. This research investigates the application of YOLOv5 for coal gangue image recognition, involving data preprocessing, model training, and optimization. Experimental results demonstrate that incorporating the multiple channel attention mechanism and lightweight content-aware re-assembly of features up-sampling operator significantly improves model confidence and recognition performance.

关键词： Coal gangue detection Detection accuracy Overfitting Preprocessing YOLOv5

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