检索结果-内蒙古大学图书馆

IEEE International Conference on Communications (ICC)

作者： Zhiyu Zhu Yang Yang Mingzhe Chen Caili Guo Yipeng Bai Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

Visible light positioning (VLP) is a promising positioning technique, which, however, typically requires multiple luminaires to achieve accurate positioning. This paper proposes a novel visual odometry (VO) assisted visible light positioning algorithm (VO-VLP) in achieving positioning with only a single luminaire. In the considered model, a user equipped with a camera jointly uses geometric features in the captured images and coordinates information obtained via visible light communication (VLC) for positioning. The proposed VLP algorithm does not rely on any extra inertial measurement unit and relaxes the tilted angle limitation at the user. In particular, VO-VLP first uses the circle feature of a luminaire to obtain dual normal vectors of the luminaire. Then, the basic principle of VO is used to eliminate the wrong normal vector by exploiting the geometric features in two consecutive images captured when the user moves. Finally, the pose and location of the user are obtained by using an artificially marked point on the luminaire's contour. VO-VLP can achieve accurate positioning with only a single luminaire and a camera. Simulation results show that the proposed indoor positioning algorithm can achieve a 97th-percentile positioning accuracy of around 10 cm.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Content-driven Joint Resource Allocation Based on Vehicle-edge Synergy in Vehicular networks

Content-driven Joint Resource Allocation Based on Vehicle-ed...

引用

IEEE Wireless Communications and Networking Conference Workshops (WCNCW)

作者： Xu Zhu Fangfang Liu Zhimin Zeng Caili Guo Jiujiu Chen Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781728195070;9781728195087

With the rapid growth of computer vision applications, a large amount of video data in vehicular networks are used for content analysis. As a representative technology in the field of artificial intelligence, deep learning has been widely used in video content understanding. However, deep learning models are usually accompanied by huge amount of calculation, which put great pressure on traditional wireless communication resource and Mobile Edge Computing (MEC) server. To solve this problem, in this paper, we first propose a DNN model segmentation strategy, and then propose a content-driven joint resource allocation scheme based on vehicle-edge synergy to maximize the accuracy of video content understanding under the constraints of communication and computing resources. Due to the real-time nature of resource allocation and the variability of the environment in vehicular networks, we design a Multi-agent Distributed Q-Learning algorithm to solve such multi-constrained nonlinear programming problems. Finally, the simulation results show that our proposed vehicle-edge synergy based joint resource allocation scheme has better video content understanding performance and system delay.

关键词： Deep learning Computational modeling Simulation Conferences Streaming media Programming Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Content-based Vehicle Selection and Resource Allocation for Federated Learning in IoV

Content-based Vehicle Selection and Resource Allocation for ...

引用

IEEE Wireless Communications and Networking Conference Workshops (WCNCW)

作者： Siyu Wang Fangfang Liu Hailun Xia Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In order to use datasets collected from multiple vehicles to train a machine learning model while ensuring vehicle user privacy, federal learning framework was introduced into the Internet of Vehicles. Federated learning is a distributed learning framework. Under the federated learning framework, the packet error rate and wireless bandwidth have a great influence on the global model training process because the vehicle exchanges model parameters with the central server through the wireless channel. With limited bandwidth, the central server needs to select a more appropriate subset of vehicles candidates to participate in federated learning. In this paper, image classification is taken as a typical application in the Internet of vehicles. The dataset contents of different vehicles are different, and the selection of different subsets of vehicles will affect the accuracy and convergence rate of the global model. Therefore, an algorithm of vehicle selection and wireless resource allocation based on dataset content is proposed. Vehicles selection and wireless resource allocation are designed as an optimization problem by joint considerations of vehicle computing resource, datasets, and wireless resources with the goal of maximizing loss function decay of the global model. Finally, simulation with the CIFAR-10 dataset verifies that the vehicle selection and resource allocation algorithm based on the dataset content is superior to the baseline methods in terms of model accuracy and convergence rate.

关键词： Wireless communication Training Computational modeling Conferences Bandwidth Collaborative work Internet

来源：评论

学校读者我要写书评

暂无评论

WiAgent: Link Selection for CSI-Based Activity Recognition in Densely Deployed Wi-Fi Environments

WiAgent: Link Selection for CSI-Based Activity Recognition i...

引用

IEEE Conference on Wireless Communications and Networking

作者： Xinbin Shen Lingchao Guo Zhaoming Lu Xiangming Wen Shuang Zhou Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In this work, we address the issue of Wi-Fi-based human activity recognition (HAR) system in densely deployed Wi-Fi environments. With the benefit of sufficient information provided by Wi-Fi channel state information (CSI), HAR based on Wi-Fi has become an active research area in recent years. Traditional Wi-Fi CSI-based HAR applications usually focus on utilizing one Wi-Fi transmitter and one or several Wi-Fi receivers to extract the activity-related features, ignoring the communication among multiple Wi-Fi devices in the real world. In this paper, we present a novel Wi-Fi link selection model on the basis of continuous state decision-making process in which CSI is modeled as a part of the state. The model, referred to as WiAgent, takes an action of selecting one Wi-Fi link according to current state, and then updates the state for the choice of the next action. From extensive experiment results, our method performs better than other solutions in a given environment where multiple Wi-Fi transmitters exist.

关键词： Training Transmitters Conferences Decision making Receivers Activity recognition Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Integrating Listwise Ranking into Pairwise-based Image-Text Retrieval

arXiv

引用

arXiv 2023年

作者： Li, Zheng Guo, Caili Wang, Xin Feng, Zerun Wang, Yanjun 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 Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China China Telecom Digital Intelligence Technology Co. Ltd. Beijing100035 China

Image-Text Retrieval (ITR) is essentially a ranking problem. Given a query caption, the goal is to rank candidate images by relevance, from large to small. The current ITR datasets are constructed in a pairwise manner. Image-text pairs are annotated as positive or negative. Correspondingly, ITR models mainly use pairwise losses, such as triplet loss, to learn to rank. Pairwise-based ITR increases positive pair similarity while decreasing negative pair similarity indiscriminately. However, the relevance between dissimilar negative pairs is different. Pairwise annotations cannot reflect this difference in relevance. In the current datasets, pairwise annotations miss many correlations. There are many potential positive pairs among the pairs labeled as negative. Pairwise-based ITR can only rank positive samples before negative samples, but cannot rank negative samples by relevance. In this paper, we integrate listwise ranking into conventional pairwise-based ITR. Listwise ranking optimizes the entire ranking list based on relevance scores. Specifically, we first propose a Relevance Score Calculation (RSC) module to calculate the relevance score of the entire ranked list. Then we choose the ranking metric, Normalised Discounted Cumulative Gain (NDCG), as the optimization objective. We transform the non-differentiable NDCG into a differentiable listwise loss, named Smooth-NDCG (S-NDCG). Our listwise ranking approach can be plug-and-play integrated into current pairwise-based ITR models. Experiments on ITR benchmarks show that integrating listwise ranking can improve the performance of current ITR models and provide more user-friendly retrieval results. The code is available at https://***/AAA-Zheng/Listwise_ITR. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

A Scalable Computation Offloading Scheme for MEC Based on Graph Neural networks

A Scalable Computation Offloading Scheme for MEC Based on Gr...

引用

IEEE Globecom Workshops

作者： Tuan Wu Wenpeng Jing Xiangming Wen Zhaoming Lu Shuyue Zhao Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665423915

Recently, computation offloading has become a promising technology to support computation-intensive applications on resource-limited mobile devices (MDs). However, existing offloading schemes suffer from poor generalization and scalability to different applications, since they mainly consider one or a few specific task dependency topologies of the application. Different from the existing schemes, this paper introduces a novel neural network, i.e., graph neural network (GNN), to adapt to the diversity of the applications. Therefore, we propose a GNN and deep reinforcement learning (DRL)-based scheme that optimizes offloading to minimize the long-term average application completion time and MD’s energy consumption. Specifically, considering the variation of the wireless network, a fine-grained task-level scheduling mechanism is presented. In addition, a scalable GNN-enabled preprocessing network is designed to process the state of the various applications and the wireless network. Furthermore, we obtain the optimal scheduling policy via training based on policy gradient algorithm under the stochastic application arrival of the unlimited inter arrival time. Extensive simulations demonstrate the effectiveness and superiority of the proposed scheme under different average inter arrival times. Specifically, the proposed scheme can lower at least 172% of the application completion time and 45% of the energy consumption of the MD compared with other baseline schemes.

关键词： Training Performance evaluation Energy consumption Wireless networks Scalability Optimal scheduling Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Slice-Based Service Function Chain Embedding with Multiple Factors

Slice-Based Service Function Chain Embedding with Multiple F...

引用

IEEE Globecom Workshops

作者： Hang Li Zixuan Kong Wan Xiang Xiangming Wen Zhaoming Lu Luhan Wang Yawen Chen Wenpeng Jing Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Beijing Laboratory of Advanced Information Networks Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665423915

Network slicing is a promising technology to provide various services on a common physical network infrastructure. A network slice is a logical virtual network composed of a group of service function chains (SFCs) and the network operator performs SFC embedding (SFCE) to create and orchestrate network slices. Compared to conventional SFCE, implementing slice-based SFCE (SBSFCE) faces some new challenges like diversified requirements of SFCs, inter-slice and intra-slice VNF sharing, and slice priority-based admission control due to the introduction of slice dimension. In this paper, we study the SBSFCE problem jointly considering the above challenges. We formulate the problem and devise a dynamic programming-based heuristic, SBSEA to solve it. The simulation results demonstrate that SBSEA outperforms the existing solution and achieves near-optimal performance.

关键词： Service function chaining Simulation Network slicing Heuristic algorithms Conferences Admission control Faces

来源：评论

学校读者我要写书评

暂无评论

Camera assisted received signal strength algorithm for indoor visible light positioning

Camera assisted received signal strength algorithm for indoo...

引用

2021 IEEE/CIC International Conference on Communications in China, ICCC 2021

作者： Li, Chengyang Yang, Yang Bai, Lin Yu, Bei Guo, Caili Xia, Hailun School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing100876 China China Shipbuilding Industry Systems Engineering Research Institute Beijing100094 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing100876 China

ISBN: (纸本)9781665443852

In this paper, a camera assisted received signal strength (CA-RSS) algorithm is proposed for visible light positioning (VLP) systems. The basic idea of CA-RSS is to simultaneously utilize visual and strength information of visible lights to achieve accurate positioning at low cost. With rectangular LED layout, the irradiance angles of the visible lights can be estimated regardless of the orientations of the LEDs. Based on the estimated irradiance angles, the distances between the LEDs and the receiver are obtained. Then, the two-dimensional (2D) position of the receiver can be calculated at low cost using a linear least square method. Based on the solid geometry theory, we further propose an independent solution method for three-dimensional (3D) positioning, which can avoid error propagation issue of dependent solution method. Moreover, considering the imperfect channel model in practice, we propose a calibration method of Lambertian model for practical uses. Simulation results show that the proposed approach can achieve 80th percentile accuracies of less than 10 cm for 3D positioning regardless of the orientations of the LEDs and the receiver. In addition, experimental results show that the proposed algorithm achieves an average 3D positioning error of 4.48 cm in a 70 cm × 70 cm × 140 cm space. © 2021 IEEE.

关键词： Light emitting diodes

来源：评论

学校读者我要写书评

暂无评论

Broadband Optically Transparent Absorber and Multi-Band Stealth Based on Organic Metasurface

引用

Chinese Physics Letters 2025年第5期 97-103页

作者： Chuwen Lan Yutong Gao Zehua Gao Hongye Wang Ke Bi Ming Lei Guoan Zhao School of Information and Communication Engineering Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications School of ScienceBeijing University of Posts and Telecommunications School of Integrated Circuits Beijing University of Posts and Telecommunications Network Education College of Beijing University of Posts and Telecommunications

Optically transparent microwave absorbers and multi-band stealth have extensive potential applications in military defense and wireless communication fields, and thus have attracted considerable attention. So far,most related work is based on inorganic transparent conductive metasurfaces. In this paper, we proposed and experimentally demonstrated a flexible, broadband and optically transparent microwave absorber using an organic metasurface. The metasurface absorber is composed of a sandwich structure, in which electric resonances and magnetic resonances are induced resulting in broadband absorption. A spraying process was developed to prepare this metasurface absorber. Both simulations and experiment show that this metasurface has broadband microwave absorption and good optical transparency. We further found that by using a multi-layer structure, visible, radar,and infrared stealth(multi-band stealth) can be achieved simultaneously. With the advantages of excellent foldability and low cost, the proposed metasurfaces may have applications in military and wireless communication fields.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Highly Efficient Generation of Non-diffraction Bessel Beams with Metasurface 3

Highly Efficient Generation of Non-diffraction Bessel Beams ...

引用

3rd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2020

作者： Zeng, Ting Deng, Li Li, Shufang Feng, Botao Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728190457

A reflection metasurface that can generate non-diffraction Bessel beams and achieve anomalous reflection with high efficiency at 5.8 GHz is proposed in this paper. The unit it utilizes has excellent amplitude and phase characteristics, greatly facilitating the construction of the proposed metasurface and laying a solid foundation for the improvement of efficiency. According to non-diffraction theory and anomalous reflection law, two metasurfaces are designed for comparison. The simulation results show that the designed metasurfaces successfully realize the non-diffractive beam with a focusing distance of 126 mm (2.44 λ0), and can bend the normally reflected wave to the direction 10° from the +z direction in a vertical plane 45° away from the +x direction. The average efficiency of the metasurface within the focusing range is as high as 84.5%, thus could be used as radio energy transmission, telecommunication multiplexing and accurate detection devices. © 2020 IEEE.

关键词： Diffraction

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：