检索结果-内蒙古大学图书馆

23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Lu, Bingqing Lin, Rongheng Zou, Hua Beijing University of Posts and Telecommunications State Key Lab of Networking and Switching Technology Beijing100876 China

ISBN: (纸本)9781665494571

With the rapid development of the shipping industry, the traffic volume increases rapidly, which may leads to traffic risks such as collisions, stranding, running on rocks. Therefore, accurate ship trajectory prediction is of great significance. In this paper, we construct a novel CNN-LSTM trajectory prediction model, using the trajectory data recorded by the Automatic Identification System (AIS) as the training and testing sets. In the data aspect, we propose a new data processing scheme to partition AIS latitude and longitude data into neatly arranged regions. In the model aspect, we introduce the residual block and attention mechanism to the basic CNN-LSTM model. Moreover, the Ranger optimizer is applied to the optimization process of the model's loss function. The practicability and effectiveness of our model in ship trajectory prediction are verified by model evaluation. This not only has important application value for ships to travel safely and efficiently in complex navigable environments, but also for maritime traffic management. © 2021 IEEE.

关键词： Training Smart cities Wind speed Soft sensors Predictive models Rocks Stability analysis

来源：评论

学校读者我要写书评

暂无评论

Quantum algorithm for soft margin support vector machine with hinge loss function

引用

The Journal of China Universities of Posts and Telecommunications 2022年第4期29卷 32-41页

作者： Liu Hailing Zhang Jie Qin Sujuan Gao Fei State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Cryptology P.O.Box 5159Beijing 100878China

Soft margin support vector machine(SVM)with hinge loss function is an important classification algorithm,which has been widely used in image recognition,text classification and so ***,solving soft margin SVM with hinge loss function generally entails the sub-gradient projection algorithm,which is very time-consuming when processing big training data *** achieve it,an efficient quantum algorithm is ***,this algorithm implements the key task of the sub-gradient projection algorithm to obtain the classical sub-gradients in each iteration,which is mainly based on quantum amplitude estimation and amplification algorithm and the controlled rotation *** with its classical counterpart,this algorithm has a quadratic speedup on the number of training data *** is worth emphasizing that the optimal model parameters obtained by this algorithm are in the classical form rather than in the quantum state *** enables the algorithm to classify new data at little cost when the optimal model parameters are determined.

关键词： soft margin support vector machine hinge loss function the sub-gradient projection algorithm quantum algorithm quadratic speedup

来源：评论

学校读者我要写书评

暂无评论

IRS-Based Integrated Location Sensing and Communication for mmWave SIMO Systems

引用

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2023年第6期22卷 4132-4145页

作者： Hu, Xiaoling Liu, Chenxi Peng, Mugen Zhong, Caijun Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China

In this paper, we establish an integrated sensing and communication (ISAC) system based on a distributed semi-passive intelligent reflecting surface (IRS), which allows location sensing and data transmission to be conducted on the same time-frequency resources. The detailed working process of the proposed IRS-based ISAC system is designed, including the transmission protocol, location sensing and beamforming optimization. Specifically, each coherence block consists of the channel estimation period, the ISAC period with two time blocks, and the pure communication (PC) period. During the channel estimation period, the low-dimensional effective user-BS channel is estimated. During each time block of the ISAC period, data transmission and user positioning are carried out simultaneously. The estimated user location in the first time block will be used for beamforming design in the second time block. During the PC period, only data transmission is conducted, by invoking the user location estimated in the second time block of the ISAC period for beamforming design. Simulation results show that a millimeter-level positioning accuracy can be achieved by the proposed location sensing scheme. Besides, the proposed two beamforming schemes based on the estimated location achieve similar performance to the benchmark schemes assuming perfect channel state information, verifying the effectiveness of beamforming design using sensed location information.

关键词： Integrated sensing and communication (ISAC) intelligent reflecting surface (IRS) beamforming design location sensing

来源：评论

学校读者我要写书评

暂无评论

IDA-NET: Individual Difference aware Medical Image Segmentation with Meta-Learning

引用

PATTERN RECOGNITION LETTERS 2025年 187卷 21-27页

作者： Zhang, Zheng Yin, Guanchun Ma, Zibo Tan, Yunpeng Zhang, Bo Zhuang, Yufeng Beijing Univ Posts & Telecommun Sch Modern Post Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci Nat Pilot Software Engn Sch State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Individual differences in organ size and spatial distribution can lead to significant variations in the content of medical images at similar anatomical locations. These case-level differences are distinct from the domain shift between multi-source data, yet they can significantly affect model performance and are difficult to address using traditional transfer learning algorithms such as domain generalization. To address the individual difference issue, we propose an individual difference aware meta-learning strategy and introduce an individual discriminator module. These components are designed to learn features related to individual difference, enhancing the model's ability to accurately segment organs across different patients. Additionally, we present a Transformer-based U-Net framework that captures both long- and short-range dependencies from MR images. This framework utilizes a parallel attention module to address the limitations of self-attention and employs an inter-layer attention module to extract attention relationships across different layers. We evaluate our approach using the Synapse dataset. Results indicate that focusing on individual difference not only significantly improves the performance of various sub-modules, allowing our method to surpass several state-of-the-art methods, but also proves to be beneficial for many other methods as well.

关键词： Transformer U-Net Meta Learning Individual Difference Medical Image Segmentation

来源：评论

学校读者我要写书评

暂无评论

Semantic Synchronization for Enhanced Reliability in Communication Systems 25

Semantic Synchronization for Enhanced Reliability in Communi...

引用

IEEE Wireless Communications and networking Conference (IEEE WCNC)

作者： Liu, Xiaoyi Liang, Haotai Dong, Chen Xu, Xiaodong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Peng Cheng Lab Dept Broadband Commun Shenzhen Guangdong Peoples R China

ISBN: (纸本)9798350303582;9798350303599

As a new communication paradigm, semantic communication has received widespread attention in communication fields. However, since the decoding of semantic signals relies on contextual knowledge, misalignment between the starting position of the semantic signal and the AI-based semantic decoder would prevent source signal recovery and reconstruction. To achieve more precise semantic communication, this study proposes an image-based semantic synchronization method leveraging intrinsic semantic features of image content. Specifically, a shared synchronized image (SyncImg) is encoded into a synchronization vector header at the transmitter and sent to the receiver. The receiver adopts a sliding window semantic decoder combined with classification and template matching methods to locate the synchronization point. Experimental results demonstrate that compared with traditional methods, the proposed method achieves a lower miss detected ratio (MDR) and root-mean-square error (RMSE) under low signal-to-noise ratios, realizing accurate synchronization of semantic signals across different devices.

关键词： semantic synchronization semantic communication synchronized image

来源：评论

学校读者我要写书评

暂无评论

Memory-Effect Based QoE Evaluation Method and Guarantee Scheme in APN-Driven Game Acceleration

引用

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第5期11卷 4774-4792页

作者： Wang, Ying Wu, Weihong Liu, Jiang Jiang, Yuxin Huang, Tao Mao, Jianwei Peng, Shuping Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China Huawei Technol Datacom Res Dept Beijing 100876 Peoples R China

Application-aware networking (APN) is crucial for ensuring Quality of Experience (QoE) in real-time online games. The adversarial nature of real-time online games introduces a memory-effect in network fluctuations, where the accumulation of past QoE of players over time may influence their current QoE. This phenomenon adds complexity to QoE evaluation and impacts the APN-driven game QoE guarantee. To address this, we propose MEEG, a scheme aimed at evaluating and guaranteeing the QoE of real-time online games from the perspective of the memory-effect. MEEG introduces a memory-effect based QoE evaluation method, capturing the existence, time dependency, and intensity of the memory-effect. Then, an algorithm was developed to tackle the APN-driven game QoE guarantee problem, considering player QoE requirements and aiming to minimize resource costs in determining APN parameters. MEEG is applied to the popular real-time online game, Arena Of Valor, to create its specific QoE model. Experimental verification involving ten volunteers demonstrates that MEEG achieves a more precise QoE evaluation in network fluctuations, reducing the average mean square error (MSE) by up to 66.42% compared to existing schemes. Additionally, MEEG's QoE guarantee ability to withstand delay fluctuations increases from 150 ms to 350 ms while reducing resource consumption by up to 40%.

关键词： APN memory-effect network fluctuations QoE QoS APN memory-effect network fluctuations QoE QoS

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Network based on MLP-Mixer for OFDM Channel Estimation 25

A Hybrid Network based on MLP-Mixer for OFDM Channel Estimat...

引用

IEEE Wireless Communications and networking Conference (IEEE WCNC)

作者： Liu, Sirui Dong, Chen Zhang, Zhi Qin, Xiaoqi Xu, Xiaodong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Peng Cheng Lab Dept Broadband Commun Shenzhen Guangdong Peoples R China

ISBN: (纸本)9798350303582;9798350303599

In order to meet the requirements of 6G communication for environmental adaptability and interference resistance, obtaining accurate Channel state Information (CSI) is of paramount importance. However, traditional communication methods struggle to fulfill these demands, leading to a growing interest in deep learning-based channel estimation solutions among researchers. This paper introduces a solution to the channel estimation problem in OFDM systems, employing a deep learning approach based on the MLP-Mixer block, referred to as CENet. CENet's channel-mixing and token-mixing structures enable better capturing of both temporal and spectral channel characteristics. The proposed channel estimation method consists of two parts: firstly, preliminary channel estimation results are generated using the LS algorithm, and then CENet is employed to further refine these preliminary results. Simulation results demonstrate the superiority of the proposed approach over other deep learning methods. Additionally, this paper extends the method to MIMO scenarios and introduces pruning techniques to reduce redundant parameters in the MLP layers, thereby reducing computational complexity.

关键词： Channel Estimation Deep Learning Orthogonal frequency-division multiplexing (OFDM) MLP-Mixer Model Pruning

来源：评论

学校读者我要写书评

暂无评论

One Size Fits All: A Unified Traffic Predictor for Capturing the Essential Spatial-Temporal Dependency

引用

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024年第8期35卷 11317-11331页

作者： Luo, Guiyang Zhang, Hui Yuan, Quan Li, Jinglin Wang, Wendong Wang, Fei-Yue Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Jiaotong Univ Sch Comp & Informat Technol Beijing 100044 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Traffic prediction is a keystone for building smart cities in the new era and has found wide applications in traffic scheduling and management, environment policy making, public safety, and so on. Instead of creating a traffic predictor for each city, this article focuses on designing a unified network model that could be directly applied for traffic prediction in any city, by learning the essential spatial-temporal dependencies, i.e., the mutual relationship between traffic and the corresponding fine-grained road network. To achieve this goal, this article proposes a joint knowledge-and data-driven mechanism that novelly divides dependencies into three kinds of correlations, i.e., road segment, intra-intersection, and inter-intersection correlation, which capture the microcosmic, middle, and macroscopic dependencies between traffic and the road network, respectively. Specifically, we first construct traffic datasets that could cover all road segments from real-world trajectory datasets, which makes it possible to model the whole road network as a graph, with the help of fine-grained road topology. Then, we propose meta road segment learner, connection-aware spatial-temporal graph convolutional network (GCN), and multiscale residual networks for capturing the microcosmic, middle, and macroscopic dependencies, respectively. Our experiments on three real-world datasets demonstrate that our proposed method could: 1) achieve better prediction accuracy compared with several approaches and 2) capture the mutual relationship between traffic and the fine-grained road network since our model trained only using data from the source city achieves good performance when it is directly applied for traffic prediction in the target city, without any fine-tuning. The codes will be made publicly available.

关键词： Graph convolutional network (GCN) spatial-temporal dependencies (STDs) spatial-temporal GCN traffic prediction

来源：评论

学校读者我要写书评

暂无评论

Entropy-Based Importance Reordering method for Mitigating Distortion in Slow Fading Channels 25

Entropy-Based Importance Reordering method for Mitigating Di...

引用

IEEE Wireless Communications and networking Conference (IEEE WCNC)

作者： Liu, Yucheng Bao, Zhicheng Liang, Haotai Zheng, Zhe Dong, Chen Xu, Xiaodong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Peng Cheng Lab Dept Broadband Commun Shenzhen Guangdong Peoples R China

ISBN: (纸本)9798350303582;9798350303599

Semantic communication, as a new research paradigm, has garnered widespread attention from academia and industry. One of the important aspects is the study of channel estimation, which can further improve the recovery of signals in communication systems. However, most existing studies on semantic communication have only considered the case of perfect channel estimation. In this paper, pilots-assisted channel estimation is considered, and a symbol reordering method named Entropy-Based Importance Reordering (EBIR) is proposed to mitigate the distortions induced by slow fading channels. The method distinguishes important and unimportant semantic symbols based on the entropy value obtained from the entropy model. Based on the characteristics of channel estimation in slow fading time-varying channels, important semantic symbols are reassigned to improve signal recovery further. The results show that the effectiveness and universality of EBIR are validated for different sources, channel bandwidth ratios (CBRs) and channel states.

关键词： Semantic communications channel estimation slow fading channel importance reordering EBIR

来源：评论

学校读者我要写书评

暂无评论

Sensing-Based Beamforming Design for Joint Performance Enhancement of RIS-Aided ISAC Systems

引用

IEEE TRANSACTIONS ON COMMUNICATIONS 2023年第11期71卷 6529-6545页

作者： Qian, Xiaowei Hu, Xiaoling Liu, Chenxi Peng, Mugen Zhong, Caijun Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China

Reconfigurable intelligent surface (RIS) has shown its great potential in facilitating device-based integrated sensing and communication (ISAC), where sensing and communication tasks are mostly conducted on different time-frequency resources. While the more challenging scenarios of simultaneous sensing and communication (SSC) have so far drawn little attention. In this paper, we propose a novel RIS-aided ISAC framework where the inherent location information in the received communication signals from a blind-zone user equipment is exploited to enable SSC. We first design a two-phase ISAC transmission protocol. In the first phase, communication and coarse-grained location sensing are performed concurrently by exploiting the very limited channel state information, while in the second phase, by using the coarse-grained sensing information obtained from the first phase, simple-yet-efficient sensing-based beamforming designs are proposed to realize both higher-rate communication and fine-grained location sensing. We demonstrate that our proposed framework can achieve almost the same performance as the communication-only frameworks, while providing up to millimeter-level positioning accuracy. In addition, we show how the communication and sensing performance can be simultaneously boosted through our proposed sensing-based beamforming designs. The results presented in this work provide valuable insights into the design and implementation of other ISAC systems considering SSC.

关键词： Integrated sensing and communication reconfigurable intelligent surface multiple-input-multiple-output system location estimation beamforming design

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：