检索结果-内蒙古大学图书馆

Blockage-Resilient Integrated Sensing and communication in mmWave Networks: Multi-View Collaboration and Efficient Task Allocation

引用

IEEE Transactions on Mobile Computing 2025年

作者： Cui, Yue Ding, Haichuan Ma, Ying Li, Xuanheng Zhang, Haixia Fang, Yuguang Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Beijing Institute of Technology School of Information and Electronics Beijing100081 China Dalian University of Technology School of Information and Communication Engineering Dalian116023 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Shandong University Shandong Provincial Key Laboratory of Wireless Communication Technologies School of Control Science and Engineering Jinan250061 China City University of Hong Kong Department of Computer Science Hong Kong Hong Kong

Integrated sensing and communication (ISAC) has emerged as a promising technology for future millimeter wave (mmWave) networks. However, the susceptibility of mmWave signals to blockages poses considerable challenges for ISAC as it can result in unreliable links and disrupted sensing. As a result, this paper investigates the blockage-resilient ISAC design that leverages the robustness offered by multi-base station (BS) collaboration. Given the dynamic blockages and the fluctuation in the targets' radar cross section (RCS), the blockage-resilient multiBS collaborative ISAC design is cast as a chance constrained integer programming (CCIP) by jointly considering the diverse deadlines of different sensing tasks and the spatial/temporal user-target pairing for dual-functional radar and communication (DFRC) waveform scheduling. To facilitate efficient solution finding, we develop a group concatenating assisted reinforcement learning (GCRL) algorithm, where we linearize the chance constraints via variable grouping and concatenation, enabling the RL agent to understand the problem structure with bipartite graphs so as to develop an efficient branching policy. Extensive experiments demonstrate the resilience of the obtained ISAC scheme to dynamic blockages. © 2025 IEEE. All rights reserved.

关键词： Integer programming

来源：评论

学校读者我要写书评

暂无评论

Evolving Multi-Access Edge Computing (MEC) for Diverse Ubiquitous Resources Utilization: A Survey

引用

Telecommunication Systems 2025年第2期88卷 1-41页

作者： Khattak, Muhammad Ilyas Yuan, Hui Khan, Ajmal Ahmad, Ayaz Ullah, Inam Ahmed, Manzoor School of Control Science and Engineering Shandong University Jinan Shandong Province China Communication and Information Research Center Sultan Qaboos University Muscat Oman Department of Electrical Engineering College of Engineering King Faisal University Al-Ahsa Saudi Arabia School of Computer Science and Technology Shandong Jianzhu University (SDJZU) Jinan China School of Computer and Information Science and AI Industrial Technology Research Hubei Engineering University Xiaogan China

The surge in smart device usage and the demand for high-throughput, low-latency mobile networks have accelerated the adoption of distributed smart applications and Collaborative Resource Management (CRM) techniques such as Multi-Access Edge Computing (MEC). With its ability to handle large data volumes, computational demands, scalability, and high energy consumption, MEC represents the next generation of Mobile Cloud Computing (MCC), addressing key challenges in emerging smart applications. MEC supports real-time, high-throughput, and energy-efficient techniques like task offloading and ultra-reliable low-latency communication (URLLC). However, as these techniques become more widespread, their diversity increases, leading to complexities that make them harder to understand and validate in different applications. This includes their use in areas like assistance for unmanned vehicles (UVs), autonomous driving, unmanned aerial vehicles (UAVs), high altitude platforms (HAPs), underwater unmanned vehicles (UUVs), satellite air-ground communication (SAGC), and other emerging systems that rely on Collaborative Resource Management (CRM). Although a number of review articles pertaining to MEC systems exist, we analyzed techniques beyond task offloading that explore MEC system applicability in diverse domains, including UUVs, vehicular edge computing, Re-configurable Intelligent Surfaces (RIS), Massive MIMO, autonomous driving, HAPs, and SAGC. From the perspective of these optimization techniques, this article highlights their role in shaping MEC’s evolution, focusing on parameters such as real-time response, energy efficiency, and other critical factors in task offloading processes. We also explored the role of Standard Development Organizations (SDOs), such as ETSI and IEEE, in advancing MEC systems. This included an analysis of offloading techniques based on their principles, features, and trade-offs, using key performance indicators (KPIs) for fair comparison, while ident

关键词： Computation offloading

来源：评论

学校读者我要写书评

暂无评论

A Deep Reinforcement Learning-Based Multi-Objective Charging Scheduling Method for Electric Vehicle Charging Station

引用

IEEE Internet of Things Journal 2025年

作者： Zhao, Qiang Wu, Wenwei Cheng, Ningyu Guo, Ge Han, Yinghua Northeastern University at Qinhuangdao School of Control Engineering Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinghuangdao066004 China Northeastern University at Qinhuangdao School of Control Engineering Qinhuangdao066004 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China Northeastern University at Qinhuangdao School of Computer and Communication Engineering Hebei Qinhuangdao066004 China

This paper investigates the charging scheduling problem within an Electric Vehicle Charging Station (EVCS), aiming to coordinate multiple charging piles to optimize the charging process. The objectives are to increase the profit for the Charging Station Operator (CSO) and enhance user satisfaction while mitigating significant fluctuations in grid load. However, since these objectives originate from different stakeholders, they are inherently conflicting;a strategy trained using fixed objective weights cannot satisfy all of them simultaneously. Additionally, uncertainties such as vehicle arrival and departure times, power requirements, and grid tariffs complicate the modeling of this process. To address these challenges, this paper reformulates the scheduling process as a Markov Decision Process (MDP) and proposes a novel model-free reinforcement learning method. By integrating randomly varying objective preferences into the inputs of agents, a set of policies corresponding to different objective preferences can be learned through a single training session. As a result, agents can execute various policies to satisfy the stakeholders’ needs based on these preferences. Moreover, a sampling adjustment strategy is introduced to improve the uniformity of the final non-dominated solution set and enhance the ability of the agent to explore the objective space. Experiments show that the proposed method can effectively solve the multi-objective problem of cooperative charging within an EVCS. Compared to the baseline method, the proposed method can achieve superior results while simultaneously reducing the computational cost to a significant extent. © 2014 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Global Spatial-Temporal Information-based Residual ConvLSTM for Video Space-Time Super-Resolution

引用

IEEE Transactions on Multimedia 2025年

作者： Fu, Congrui Yuan, Hui Jiang, Shiqi Zhang, Guanghui Shen, Liquan Hamzaoui, Raouf Center of Experimental Teaching China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China Shandong University School of software Shandong Jinan China Shandong University School of Computer Science and Technology China Shanghai University School of Communication and Information Engineering Shanghai China De Montfort University School of Engineering and Sustainable Development LeicesterLE1 9BH United Kingdom

By converting low-frame-rate, low-resolution videos into high-frame-rate, high-resolution ones, space-time video super-resolution techniques can enhance visual experiences and facilitate more efficient information dissemination. We propose a convolutional neural network (CNN) for space-time video super-resolution, namely GIRNet. Our method combines long-term global information and short-term local information from the video to better extract complete and accurate spatial-temporal information. To generate highly accurate features and thus improve performance, the proposed network integrates a feature-level temporal interpolation module with deformable convolutions and a global spatial-temporal information-based residual convolutional long short-term memory (convLSTM) module. In the feature-level temporal interpolation module, we leverage deformable convolution, which adapts to deformations and scale variations of objects across different scene locations. This provides a more efficient solution than conventional convolution for extracting features from moving objects. Our network effectively uses forward and backward feature information to determine inter-frame offsets, leading to the direct generation of interpolated frame features. In the global spatial-temporal information-based residual convLSTM module, the first convLSTM is used to derive global spatial-temporal information from the input features, and the second convLSTM uses the previously computed global spatial-temporal information feature as its initial cell state. This second convLSTM adopts residual connections to preserve spatial information, thereby enhancing the output features. Experiments on the Vimeo90K dataset show that the proposed method outperforms open source state-of-the-art techniques in peak signal-to-noise-ratio (by 1.45 dB, 1.14 dB, and 0.2 dB over STARnet, TMNet, and 3DAttGAN, respectively), structural similarity index(by 0.027, 0.023, and 0.006 over STARnet, TMNet, and 3DAttGAN, respectiv

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Optical attenuation coefficient based optical coherence tomography angiography

引用

Optics communications 2025年 586卷

作者： Xiang, Ben Ding, Ning Jiang, Huiwen Liu, Jian Yu, Yao Luan, Jingmin Zhao, Yuqian Wang, Yi Yang, Yanqiu Wang, Fengwen Ma, Zhenhe School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao066004 China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China College of Information Science and Engineering Northeastern University Shenyang110819 China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao066004 China

In this study, we reported an optical coherence tomography angiography (OCTA) method based on optical attenuation coefficients (OAC), called OAC-based decorrelation (OACD), for mapping high-quality microvascular images. OACD utilizes the OAC instead of amplitude or phase to calculate flow signals, so OACD can intrinsically suppress noise arising from phase errors and intensity variations in OCT signals caused by the blood flow in superficial vasculature. The performance of the newly proposed algorithm is tested against previously reported OCTA algorithms (i.e., split-spectrum amplitude and phase-gradient angiography (SSAPGA) and principal component analysis (PCA)). Compared to SSAGPA and PCA, OACD can provide enhanced motion contrast in phantoms and in vivo experiments, facilitating better differentiation between vessels and static tissue. Benefiting from these advantages, the vascular images processed by the OACD method exhibit increased vascular visibility and connectivity, enhancing overall image quality. Our method holds promise for disease diagnosis and monitoring. © 2025 Elsevier B.V.

关键词： Optical coherence tomography

来源：评论

学校读者我要写书评

暂无评论

Secure Beamforming Design for IRS-ISAC Systems with a Hardware-Efficient Hybrid Beamforming Architecture

引用

IEEE Transactions on Vehicular technology 2025年

作者： Xiong, Weijie Zhao, Zhenglan Lin, Jingran Xiao, Zhiling Li, Qiang University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100083 China Tianfu Jiangxi Laboratory Sichuan Chengdu641419 China

In this paper, we employ a hardware-efficient hybrid beamforming (HB) architecture to achieve balanced performance in an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system. We consider a scenario where a multi-antenna, dual-function base station (BS) performs secure beamforming for a multi-antenna legitimate receiver while simultaneously detecting potential targets. Our objective is to maximize the communication secrecy gap by jointly optimizing the analog and digital beamformers, IRS reflection coefficients, and radar scaling factor, subject to constraints on beampattern similarity, total transmit power budget, and the constant modulus of both the analog beamformer and IRS reflection coefficients. This secrecy gap maximization problem is generally non-convex. To address this, we incorporate the exterior penalty method by adding the radar constraint as a penalty term in the objective function. We then propose an efficient approach based on the penalty dual decomposition (PDD) framework to solve the reformulated problem, featuring closed-form solutions at each step and guaranteeing convergence to a stationary point. Simulation results validate the effectiveness of the proposed algorithm and demonstrate the superiority of the IRS-ISAC system with HB architecture in balancing performance and hardware costs. © 1967-2012 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Load Balancing Routing Algorithm for LEO Satellite Networks Based on Ant Colony Optimization

引用

Internet technology Letters 2025年第3期8卷

作者： Zhi, Ruxin Wang, Jiahui Xu, Zhan Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

To address the problem of the unbalanced load and optimize the traffic distribution of large-scale low earth orbit (LEO) satellite networks, this paper proposes a load-balancing routing algorithm for LEO satellite networks based on ant colony optimization. The algorithm establishes the global optimal initial path through the improved ant colony algorithm to bypass the network bottleneck, makes local adjustments to cope with burst traffic changes to avoid congestion, and optimizes the "inferior" paths through regular rerouting to improve the overall network performance. The results show that the algorithm performs well in terms of packet loss rate, throughput, and load balancing, which can effectively alleviate the link utilization imbalance problem and provide a more stable and efficient service for the satellite network. Among them, the packet loss rate is reduced by 7.8%, and the load distribution index is improved by 30%. © 2025 The Author(s). Internet technology Letters published by John Wiley & Sons Ltd.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

A Cross-Task Transfer SAR Target Recognition Method Based on AMFFNet and IACGAN

引用

IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Wan, Xunyang Du, Xiaolin Cui, Guolong Chen, Xiaolong Zheng, Jibin Yantai University School of Computer and Control Engineering Yantai264005 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Naval Aviation University Yantai264001 China Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China

Convolutional neural networks (CNN) have shown excellent capability in synthetic aperture radar (SAR) target recognition. However, obtaining sufficient training samples for improving network recognition is difficult due to the deficiency of labeled SAR image data. To tackle the problem, a cross-task transfer method for SAR target recognition is proposed in this paper, which is based on a designed attention multi-scale feature fusion network (AMFFNet) and an improved auxiliary classifier generative adversarial network (IACGAN). In this method, firstly, a data augmentation method based on you only cut twice (YOCT) is devised for expanding the training samples. Secondly, the partial weight parameters of AMFFNet are initialized by the pre-trained IACGAN discriminator. Finally, AMFFNet is fine-tuned using the training samples. Additionally, on the network structure of AMFFNet, multi-scale features are extracted by adopting a multi-scale depth separable convolution module, which allows the model to acquire more informative features. Attention mechanisms are employed in this network to enhance its ability to capture important features while reducing the effects of noise. A multi-level feature fusion structure is used to further raise the representational capability of the model. Experimental results on multiple open-source real SAR datasets show that the proposed method can achieve better recognition performance under different percentages of training data, and the effectiveness and superiority of the method are confirmed by its robustness to noise. © 1965-2011 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Breather dynamics in an optomechanical array with staggered coupling

引用

Physical Review A 2025年第3期111卷 033502-033502页

作者： Yuan Zhao Yiheng Hou Yu Wang Zhuo Fan Wei Peng Qin Zhou Siliu Xu Shihua Chen Key Laboratory of Optoelectronic Sensing and Intelligent Control Hubei University of Science and Technology Xianning 437100 China School of Biomedical Engineering and Imaging Xianning Medical College Hubei University of Science and Technology Xianning 437100 China School of Electronic and Information Engineering Hubei University of Science and Technology Xianning 437100 China Research Center of Nonlinear Science School of Mathematics and Physical Sciences Wuhan Textile University Wuhan 430200 China School of Physics and Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing 211189 China

We present an approach toward generating highly controllable breathers, using an array of staggered optomechanical cavities that feature alternating coupling strengths. Four different types of breather states as well as stable two-soliton states are demonstrated to form in such an optomechanical array, thanks to the interplay between the photon-hopping induced tunneling effect and the photon-phonon coupling in the optomechanical cell. It is seen that both their photonic and phononic wave components manifest quasi-periodic oscillatory patterns and coherent localization. We unveil that such breather dynamics can be well controlled by adjusting the coupling strength, the cavity field decay, and the number of array cells. As a result, we observe an unusual odd-even lattice effect in that stable breathers are only available when the cell number is even. We anticipate that these findings from the staggered optomechanical configuration may expand the realm of cavity optomechanics, yielding promising applications such as on-chip manipulation of light propagation.

关键词： Solitons

来源：评论

学校读者我要写书评

暂无评论

Joint Vehicle Pairing, Spectrum Assignment and Power control for Sum-Rate Maximization in NOMA-Based V2X Underlaid Cellular Networks

引用

IEEE Internet of Things Journal 2025年

作者： Xue, Tong Zhang, Haixia Ding, Hui Yuan, Dongfeng Shandong University of Science and Technology College of Electronic and Information Engineering Shandong Qingdao266590 China Shandong Key Laboratory of Intelligent Communication and Sensing-Computing Integration Shandong Jinan250061 China Shandong University School of Control Science and Engineering Shandong Jinan250061 China

Vehicle-to-everything (V2X) underlaid cellular networks in underlaid mode suffers catastrophic co-channel interference caused by spectrum sharing, results in a reduced system sum-rate. To cope with this, this work studies a social-mobility-aware non-orthogonal multiple access (NOMA)-enabled V2X underlaid cellular network to mitigate the co-channel interference and improve the sum-rate. By jointly optimizing vehicle pairing and resources, a sum-rate maximization problem is formulated under the diverse quality of service requirements of both cellular and vehicular users. The formulated problem is proved to be a non-deterministic polynomial-time (NP)-hard problem, and is difficult to solve. As an alternative, we propose a NOMA-based joint vehicle pairing, spectrum assignment and power control algorithm (NOMA-JVP-SA-PCA), with which the original problem is decomposed into two disjoint subproblems, i. e., 1) joint vehicle pairing and spectrum assignment subproblem, and 2) power control subproblem. Dealing the first subproblem, we propose a heuristic social-mobility-aware vehicle pairing algorithm (HSMA-VPA) and a revised Kuhn-munkres-based spectrum assignment algorithm (KM-SAA) to acquire the vehicle pairing and spectrum assignment solutions. Then, solving the second subproblem, a closed-form power solution is obtained utilizing a three-dimensional geometric power control approach (3D-PCA). Finally, we solve the original problem through an iterative method. Simulation results show that the proposed NOMA-JVP-SA-PCA effectively enhances the sum-rate and outperforms the baseline algorithms around 24%-53% within a specific range. © 2014 IEEE.

关键词： Polynomial approximation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：