检索结果-内蒙古大学图书馆

FINT: Freshness-Based In-Band Network-Wide Telemetry in Resource-Constrained Environments

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2025年第2期22卷 1314-1329页

作者： Zhong, Peiran Zhou, Fanqin Feng, Lei Li, Wenjing Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

A new network monitoring technology called in-band network telemetry (INT) offers users the ability to gather precise, real-time data about the entire network. While several studies have used in-band network telemetry for network-wide monitoring, it is insufficient for the growing number of massive networks that are resource-constrained. Finding the most valuable information with the least amount of resources is challenging. In this paper, We formalize the problem of in-band network-wide telemetry with low resource overheads. This formalized problem aims to achieve high freshness of network performance data using fewer resources and reducing deployment and maintenance costs for O&M personnel. We propose a heuristic method based on path reorganization to address this issue. The heuristic algorithm for planning paths starts from greedy path planning results and finds a more appropriate planning scheme by merging and reorganizing paths. Additionally, probabilistic insertion is considered to reduce the impact of intrusiveness of in-band network telemetry. Simulation results show that our approach is effective in improving resource utilization and reducing the cost of monitoring the network compared to similar studies.

关键词： Age of information data plane programmability in-band network telemetry (INT) in-band network telemetry (INT) network management network management P4 P4 P4

来源：评论

学校读者我要写书评

暂无评论

Wideband Beamforming With RIS: A Unified Framework via Space-Frequency Transformation

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2025年 73卷 173-187页

作者： Qian, Xiaowei Hu, Xiaoling Liu, Chenxi Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China

The spectrum shift from sub-6G bands to high-frequency bands has posed an ever-increasing demand on the paradigm shift from narrowband beamforming to wideband beamforming. Despite recent research efforts, the problem of wideband beamforming design is particularly challenging in reconfigurable intelligent surface (RIS)-assisted systems, due to that the RIS is not capable of performing frequency-dependent phase shift, therefore inducing high signal processing complexity. In this paper, we propose a simple-yet-efficient wideband beamforming design for RIS-assisted systems, in which a transmitter sends wideband signals to a desired target with the aid of the RIS. In the proposed design, we exploit space-frequency Fourier transformation and stationary phase method to derive an approximate closed-form solution of RIS phase shifts, which significantly reduces the signal processing complexity compared to existing approaches. The obtained solution is then used to generate a large and flat beampattern over the desired frequency band. Through numerical results, we validate the effectiveness of our proposed beamforming design and demonstrate how it can improve system performance in terms of communication rate and sensing resolution. Beyond generating the flat beampattern, we highlight that our proposed design is capable of mimicking any desired beampattern by matching the RIS phase shift with the amplitude modulation function, thus providing valuable insights into the design of novel wideband beamforming for RIS-assisted systems.

关键词： Reconfigurable intelligent surfaces Array signal processing Wideband Narrowband Sensors Millimeter wave communication Delays Time-frequency analysis Standards RF signals Reconfigurable intelligent surface wideband beamforming space-frequency Fourier transformation stationary phase method

来源：评论

学校读者我要写书评

暂无评论

WiCamera: Vortex Electromagnetic Wave-Based WiFi Imaging

引用

IEEE TRANSACTIONS ON MOBILE COMPUTING 2025年第5期24卷 3633-3649页

作者： Xu, Leiyang Zheng, Xiaolong Du, Xinrun Liu, Liang Ma, Huadong Beijing Univ Posts & Telecommun Sch Comp Sci State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Current WiFi imaging approaches focus on monitoring dynamic targets to facilitate easy object distinction and capture rich signal reflections for image construction. In static object imaging, massive antenna array or emulated antenna array is often necessary. We propose WiCamera, a novel WiFi imaging prototype that utilizes vortex electromagnetic waves (VEMWs) to monitor stationary human postures using commodity WiFi, by generating human silhouettes with only 3 x 3 MIMO. VEMWs possess a helical wavefront with different phase variations, enabling the imaging of stationary objects through different OAM (Orbital Angular Momentum) modes with time-division multiplexing. WiCamera emits three OAM modes waves from WiFi devices and utilizes their phase variations for imaging. By ray tracing the received signals to a target image plane, WiCamera generates a wavefront image. A generative adversarial network (GAN)-based model is further utilized to refine the wavefront image and create a high-resolution human silhouette. The system's output images are evaluated using metrics such as structural similarity index measure (SSIM) and Szymkiewicz-Simpson coefficient (SSC), comparing them to ground truth images captured by cameras. The evaluation shows that WiCamera performs consistently well in various environments and with different users, with an SSIM reaching up to 0.89 and an SSC reaching up to 0.93.

关键词： Channel state information vortex electromagnetic wave orbital angular momentum orbital angular momentum ray tracing ray tracing posture imaging posture imaging posture imaging

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Ensemble Learning Paradigm With Spatial-Temporal Feature Extraction for Wireless Traffic Prediction

引用

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2025年第2期22卷 1727-1743页

作者： Zhu, Yifei Feng, Lei Zhou, Fanqin Li, Wenjing Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Accurately predicting traffic in a cellular network is challenging since the traffic time series integrated by various wireless services is non-stationary and reveals concealed spatial correlation among different cells. Due to that, the presence of bias in a single forecast model often hinders the ability to generalise under numerous circumstances in wireless traffic data, no particular approach stands out as clearly superior to the others. In this paper, we propose an adaptive ensemble learning paradigm that can benefit from centralizing individual forecast base models. It stacks the prediction outputs of several base learners due to the traffic dynamics characteristic. An improved convolutional neural network (CNN)-based representation learning method is designed to extract the high-order spatial-temporal features in the traffic data and obtain the adaptive weights of participating base learner models for the ensemble. The experimental results verify that the proposed ensemble approach can fully utilize spatial-temporal features and outperform individual statistical and machine-learning models regarding prediction accuracy. Furthermore, the ensemble method via stacking base models with fewer parameters is capable of generating predictions close to the large-parametric spatial-temporal transformer (ST-Tran) model produced.

关键词： Predictive models Feature extraction Data models Adaptation models Wireless communication Ensemble learning Accuracy Traffic control Convolutional neural networks Transformers wireless traffic prediction spatial-temporal feature extraction adaptive weight

来源：评论

学校读者我要写书评

暂无评论

A Lightweight SAR Ship Detection Network Based on Deep Multiscale Grouped Convolution, Network Pruning, and Knowledge Distillation

引用

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2025年 18卷 2190-2207页

作者： Hu, Boyi Miao, Hongxia Beijing Univ Posts & Telecommun Sch Informat & Commun Engn State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Deep learning has proven to be highly effective in synthetic aperture radar (SAR) image target detection. However, many latest deep learning models have predominantly focused on increasing depth and size to enhance detection accuracy, often ignoring the balance between accuracy and detection speed, as well as the practical deployment of these models on hardware platforms. Therefore, a lightweight algorithm for SAR ship detection is designed in this article. First, we propose a preliminary lightweight scheme, including a multiscale feature learning augmented backbone, a lightweight feature fusion neck, and a parameter-sharing lightweight detection head. Second, unimportant branches of the network are pruned to further compress the model. Finally, the detection accuracy of the model is enhanced by knowledge distillation without augmenting the model volume, which compensates for the accuracy loss caused by model compression. Experimental validation is conducted on three SAR image ship detection datasets (SSDD, high-resolution SAR images dataset, large-scale SAR ship detection dataset-v1.0) to thoroughly assess the effectiveness of the proposed lightweight algorithm. Experimental results on the three datasets demonstrate that the proposed method achieves a model volume reduction to one-third of the baseline while maintaining a minimal decrease in detection accuracy. In SSDD, the proposed method achieved 98.7 accuracy, 0.92M parameters, 3.1G FLOPS and 2.1 MB size of 1.5X pruning rate. Furthermore, it outperforms other state-of-the-art lightweight detectors.

关键词： Computational modeling Accuracy Convolution Marine vehicles Synthetic aperture radar Solid modeling Feature extraction Detectors Adaptation models Remote sensing Convolutional neural network (CNN) knowledge distillation (KD) lightweight network pruning synthetic aperture radar (SAR) target detection

来源：评论

学校读者我要写书评

暂无评论

Near-Field High-Speed User Sensing in Wideband mmWave Communications: Algorithms and Bounds

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2025年 73卷 919-935页

作者： Miao, Hongxia Peng, Mugen Beijing Univ Posts & Telecommun Sch Informat & Commun Engn State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Integrated sensing and communications (ISAC) has been expected to be a key technique in the sixth-generation cellular networks. With the increase of carrier frequency (to millimeter-wave or Terahertz spectrum) and antenna array size (to extremely large-scale antenna) in wireless communications, the near-field area is enlarged and cannot be ignored. Accordingly, the channel model and its estimation algorithms are changed, which bring new chances in ISAC. However, the impact of both Doppler and spatial wideband effects, caused by high mobility and multicarriers, on sensing performance using communication signals is not well studied. In this study, these two effects are shown to be helpful in user sensing. First, the channel model is proposed for a high-speed moving user transmitting an orthogonal frequency division multiplex (OFDM) signal, where there are six unknown parameters. Then, the Cramer-Rao lower bounds (CRLB) for joint six parameter estimation is determined, where the impact of the near-field parameter and the velocity on the CRLB of positioning are discussed and quantified. Further, to compensate for the deficiency that the CRLB is tight only in high signal-to-noise-ratio (SNR) scenarios, we derive the Ziv-Zakai bound (ZZB) for positioning by exploiting the prior information on positioning parameters. Subsequently, a joint position and velocity parameter estimation algorithm is designed by first performing a discrete fractional Fourier transform on the received signal to obtain a coarse estimation and then refining it by Newton-based refinement. Numerical results coincide with our analysis.

关键词： OFDM Estimation Signal processing algorithms Channel estimation Chirp Frequency estimation Training Signal to noise ratio Sensors Matching pursuit algorithms Near-field ISAC high-speed moving CRLB ZZB

来源：评论

学校读者我要写书评

暂无评论

A novel synchrosqueezing transform associated with linear canonical transform

引用

SIGNAL PROCESSING 2025年 227卷

作者： Miao, Hongxia Beijing Univ Posts & Telecommun Sch Informat & Commun Engn State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Synchrosqueezing transforms have aroused great attention for its ability in time-frequency energy rearranging and signal reconstruction, which are post-processing techniques of the time-frequency distribution. However, the time-frequency distributions, such as short-time Fourier transform and short-time fractional Fourier transform, cannot change the shape of the time-frequency distribution. The linear canonical transform (LCT) can simultaneously rotate and scale the time-frequency distribution, which enlarges the distance between different signal components with proper parameters. In this study, a convolution-type short-time LCT is proposed to present the time-frequency distribution of a signal, from which the signal reconstruction formula is given. Its resolutions in time and LCT domains are demonstrated, which helps to select suitable window functions. A fast implementation algorithm for the short-time LCT is provided. Further, the synchrosqueezing LCT (SLCT) transform is designed by performing synchrosqueezing technique on the short-time LCT. The SLCT inherits many properties of the LCT, and the signal reconstruction formula is obtained from the SLCT. Adaptive selections of the parameter matrix of LCT and the length of the window function are introduced, thereby enabling proper compress direction and resolution of the signal. Finally, numerical experiments are presented to verify the efficiency of the SLCT.

关键词： Synchrosqueezing transform Generalized convolution operation LCT Chirp Linear time-varying system

来源：评论

学校读者我要写书评

暂无评论

Estimation of displacement operations based on Fock states considering thermal noise in preparing probes

引用

OPTICS LETTERS 2025年第7期50卷 2413-2416页

作者： Di, Shijie Yuan, Renzhi Yang, Chuang Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 10013 Peoples R China

Displacement based quantum receivers can beat the standard quantum limit and have gained increasing attention in recent years. The displacement operation value can be estimated and calibrated by using Fock states as probes. In this Letter, we focus on the impacts of thermal noise when preparing the Fock probes on the estimation performance. We first derive the density matrix and the photon statistics of the noisy displaced number state with a uniformly distributed displacement phase. Based on the derived density matrix, we then analyze the performance of estimating displacement operations by using the maximum likelihood estimation (MLE) method. To decrease the computational complexity of the MLE, we further derive an approximated probability density of the photon numbers under small displacement. Besides, the quantum Cram & eacute;r-Rao bound (QCRB) is also derived to analyze the performance limit of the displacement estimation. Numerical results found that, though thermal noise can greatly degrade the MLE accuracy of the displacement operations, the performance advantage of using Fock probes still persists over classical coherent probes. Besides, we demonstrate that the MLE method based on Fock probes can well approach the QCRB when the displacement strength Nc <= similar to 1. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Coherent states Optical amplifiers Phase Photon statistics Quantum beats Quantum information

来源：评论

学校读者我要写书评

暂无评论

An efficient quantum proactive incremental learning algorithm

引用

Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 45-53页

作者： Lingxiao Li Jing Li Yanqi Song Sujuan Qin Qiaoyan Wen Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing 100876China

In scenarios where a large amount of data needs to be learned,incremental learning can make full use of old knowledge,signif-icantly reduce the computational cost of the overall learning process,and maintain high *** this paper,taking the MaxCut problem as our example,we introduce the idea of incremental learning into quantum computing,and propose a Quantum Proactive Incremental Learning algorithm(QPIL).Instead of a one-off training of quantum circuit,QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices,proactively reducing large-scale problems to smaller ones to solve in steps,providing an efficient solution for ***,some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at ***,in each incremental phase,the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current *** perform experiments on 120 different small-scale graphs,and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR),time cost,anti-forgetting,and solv-ing *** particular,QPIL’s AR surpasses 20%of mainstream quantum baselines,and the time cost is less than 1/5 of *** idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale MaxCut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training MaxCut quantum computing

来源：评论

学校读者我要写书评

暂无评论

IncEFL:a sharing incentive mechanism for edge-assisted federated learning in industrial IoT

引用

Digital Communications and Networks 2025年第1期11卷 106-115页

作者： Jiewei Chen Shaoyong Guo Tao Shen Yan Feng Jian Gao Xuesong Qiu State Key Laboratory of Networking and Switching Technology Beijing University of Post and TelecommunicationsBeijing 100087China Kunming University of Science and Technology Kunming 650031China Yunnan Provincial Academy of Science and Technology Kunming 650228China

As the information sensing and processing capabilities of IoT devices increase,a large amount of data is being generated at the edge of Industrial IoT(IIoT),which has become a strong foundation for distributed Artificial Intelligence(AI)***,most users are reluctant to disclose their data due to network bandwidth limitations,device energy consumption,and privacy *** address this issue,this paper introduces an Edge-assisted Federated Learning(EFL)framework,along with an incentive mechanism for lightweight industrial data *** order to reduce the information asymmetry between data owners and users,an EFL model-sharing incentive mechanism based on contract theory is *** addition,a weight dispersion evaluation scheme based on Wasserstein distance is *** study models an optimization problem of node selection and sharing incentives to maximize the EFL model consumers'profit and ensure the quality of training *** incentive-based EFL algorithm with individual rationality and incentive compatibility constraints is ***,the experimental results verify the effectiveness of the proposed scheme in terms of positive incentives for contract design and performance analysis of EFL systems.

关键词： Federated learning Data sharing Edge intelligence Incentives Contract theory

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：