检索结果-内蒙古大学图书馆

Coexisting RIS Induced Multipath Fading in High-Speed Train Systems

IEEE Transactions on Vehicular Technology 2025年

作者： Wu, Wei Wang, Wennai Song, Rongfang Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education College of Telecommunication and Information Engineering Nanjing210003 China

Reconfigurable Intelligent Surfaces (RIS) have recently emerged as a promising and cost-effective technology for enabling stable and reliable communications in high-speed train (HST) environments. However, the coexistence of multiple RIS-assisted networks in confined train environments poses significant theoretical and practical challenges. This study focuses on the RIS coexistence problem in HST systems, specifically investigating the impact of multipath fading induced by coexisting RIS (C-RIS) on interfered users. First, we develop a simplified mutual-coupling channel model for C-RIS-induced multipath (CR-MP), applicable to operational frequency bands above 5 GHz. Second, we evaluate the effects of CR-MP on interfered users using the multipath power ratio (MPR), defined as the ratio of the received signal power to the desired signal power. The MPR formulation is derived as a function of the user's spatial position, operational frequency, and penetration loss. Finally, we analyze the spatial and temporal characteristics of the CR-MP channel through the MPR radiation pattern and the received signal envelope, respectively. Simulation results reveal that the spatial characteristics are time-varying and strongly influenced by the frequency difference and penetration loss, while the temporal characteristics depend on the user's position. When the target user is located in specific positions, the fading effects induced by CR-MP can be negligible with a reduced frequency difference, while the received signal power gain can be significantly enhanced with an increased frequency difference. The findings of this study provide practical insights for RIS deployment in real-world systems, particularly for mitigating C-RIS-induced interference in coexisting RIS-assisted networks. © 1967-2012 IEEE.

关键词： Light rail transit

来源：评论

学校读者我要写书评

暂无评论

Security and Reliability Tradeoff of NOMA Based Hybrid Satellite-Terrestrial network With a Friendly Jammer

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第2期74卷 3439-3444页

作者： Li, Bin Zou, Yulong Wu, Tonghua Zhang, Zaichen Chen, Mingkai Jiang, Yuhan NUPT Key Lab Broadband Wireless Commun & Sensor Network Minist Educ Nanjing 210003 Peoples R China NUPT Jiangsu Engn Res Ctr Commun & Network Technol Nanjing 210003 Peoples R China NUPT Sch Telecommun & Informat Engn Nanjing 210003 Peoples R China Nari Grp Corp Nanjing 211106 Peoples R China Southeast Univ Frontiers Sci Ctr Mobile Informat Commun & Secur Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China

This paper analyzes the security and reliability tradeoff (SRT) performance for a hybrid satellite-terrestrial network (HSTN) using the non-orthogonal multiple access (NOMA) protocol. To improve the SRT performance of the NOMA based HSTN, a friendly jammer assisted transmission (FJT) scheme is proposed and its outage and intercept probability expressions are carried out in closed-form. The transmission secrecy outage probability is given to show the tradeoff between the security and reliability of the FJT scheme. For the purposes of comparison, the none jammer aided transmission (NJT) scheme is also considered in simulations. Numerical results reveal that the FJT scheme significantly enhances the SRT performance of each user and the whole system compared to the NJT scheme. Moreover, the power allocation between users and that between the relay and the friendly jammer can be adjusted to achieve better SRT performance.

关键词： Security and reliability tradeoff (SRT) non-orthogonal multiple access (NOMA) friendly jammer hybrid satellite-terrestrial network Security and reliability tradeoff (SRT) non-orthogonal multiple access (NOMA) friendly jammer hybrid satellite-terrestrial network

来源：评论

学校读者我要写书评

暂无评论

High spatial resolution and dynamic OFDR-based method for detecting ship structural response

引用

MEASUREMENT SCIENCE AND TECHNOLOGY 2025年第3期36卷 035214-035214页

作者： He, Bo Fu, Xuelei Gui, Xin Li, Zhengying Wuhan Univ Technol Sch Informat Engn Luoshi Rd 122 Wuhan 430070 Peoples R China Hubei Key Lab Broadband Wireless Commun & Sensor N Luoshi Rd 122 Wuhan 430070 Peoples R China Wuhan Univ Technol Opt Fiber Sensing Technol & Network Natl Engn Res Ctr Luoshi Rd 122 Wuhan 430070 Peoples R China

Ships, as thin-walled structures, experience various structural responses at critical components and may even fail under sustained time-varying wave forces. Understanding the structural behaviors of key components during operation is essential for accurate ship safety assessments. The lack of an effective strain monitoring system that integrates both high spatial resolution and dynamic monitoring capabilities affects the timely detection of these structural responses. This paper presents a high spatial resolution dynamic strain monitoring system using optical frequency domain reflectometry, achieving a system spatial resolution of 0.11 mm, a sensing spatial resolution of 20 mm, and a sampling frequency of 10 Hz. A box girder model of a river-sea-going ship is employed to simulate structural responses under wave-induced conditions. Simulation results validate the system's accuracy. By analyzing strain distribution and variation, this study explores the dynamic collapse behavior of structures under wave forces.

关键词： ship behavior strain detection structural response OFDR experimental investigation

来源：评论

学校读者我要写书评

暂无评论

communication-Efficient Distributed Learning in Massive IoT: A Graph-Based Perspective

Communication-Efficient Distributed Learning in Massive IoT:...

引用

IEEE Conference on wireless communications and networking

作者： Lindong Zhao Jingyue Tang Mingzhe Chen Liang Zhou Weihua Zhuang Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Various distributed learning approaches emerge for enabling ubiquitous intelligence in Internet of Things (IoT) without sacrificing data privacy. To improve communication efficiency in frequent knowledge exchange over resource-constrained IoT, different techniques for client selection have been proposed. However, the intractable scalability issues remain to be addressed in massive IoT, since highly-coupled co-channel interference adds exponential complexity to combinatorial client selection. In this work, we develop a client selection framework highly-scalable to large-scale networks with thousands of devices, which exploits the inherent graph structure derived from knowledge exchange and co-channel interference. Specifically, we first model a client selection problem for jointly optimizing learning performance and system cost under volatile network conditions. The formulated problem is encoded into a node classification problem by a directed graph. Subsequently, a general yet simple solver is designed based on graph neural networks, which selects clients by classifying node status with recursive neighborhood aggregation of node representations. Finally, extensive experimental results demonstrate that the proposed approach can perform on par with state-of-the-art methods, while scaling to networks whose size is orders of magnitude larger than they can handle.

关键词： Performance evaluation Knowledge engineering Computer aided instruction Costs Distance learning Scalability Graph neural networks Data models Internet of Things Interchannel interference

来源：评论

学校读者我要写书评

暂无评论

Research on Personalized Course Resource Recommendation Method Based on GEMRec

引用

APPLIED SCIENCES-BASEL 2025年第3期15卷 1075-1075页

作者： Wang, Enliang Sun, Zhixin Nanjing Univ Posts & Telecommun Post Big Data Technol & Applicat Engn Res Ctr Jian Nanjing 210003 Peoples R China Nanjing Univ Posts & Telecommun Post Ind Technol Res & Dev Ctr State Posts Bur Int Nanjing 210003 Peoples R China Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Network Minist Educ Nanjing 210003 Peoples R China

With the rapid growth of online educational resources, existing personalized course recommendation systems face challenges in multimodal feature integration and limited recommendation interpretability when dealing with complex and diverse instructional content. This paper proposes a graph-enhanced multimodal recommendation method (GEMRec), which effectively integrates text, video, and audio features through a graph attention network and differentiable pooling. Innovatively, GEMRec introduces graph edit distance into the recommendation system to measure the structural similarity between a learner's knowledge state and course content at the knowledge graph level. Additionally, it combines SHAP (SHapley Additive exPlanations) value computation with large language models to generate reliable and personalized recommendation explanations. Experiments on the MOOCCubeX dataset demonstrate that the GEMRec model exhibits strong convergence and generalization during training. Compared with existing methods, GEMRec achieves 0.267, 0.265, and 0.297 on the Precision@10, Recall@10, and NDCG@10 metrics, respectively, significantly outperforming traditional collaborative filtering and other deep learning models. These results validate the effectiveness of multimodal feature integration and knowledge graph enhancement in improving recommendation performance.

关键词： multimodal deep learning knowledge graph personalized course recommendation graph neural network interpretability

来源：评论

学校读者我要写书评

暂无评论

¹⁸F-FDG PET radiomics score construction by automatic machine learning for treatment response prediction in elderly patients with diffuse large B-cell lymphoma: a multicenter study

引用

JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY 2025年第3期151卷 1-11页

作者： Zhao, Jincheng Zhao, Wenzhuo Chen, Man Rong, Jian Teng, Yue Chen, Jianxin Xu, Jingyan China Pharmaceut Univ Nanjing Drum Tower Hosp Sch Basic Med & Clin Pharm Dept Hematol Nanjing Peoples R China Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Network Minist Educ Nanjing Peoples R China Nanjing Univ Nanjing Drum Tower Hosp Dept Nucl Med Affiliated HospMed Sch Nanjing Peoples R China

Purpose To explore the development and validation of automated machine learning (AutoML) models for F-18-FDG PET imaging-based radiomics signatures to predict treatment response in elderly patients with diffuse large B-cell lymphoma (DLBCL). Methods A retrospective analysis was conducted on 175 elderly (>= 60 years) DLBCL patients diagnosed between March 2015 and March 2023 at two medical centers, with a total of 1010 lesions. The baseline PET imaging-based radiomics features of the training cohort were processed using AutoML model AutoGluon to generate a radiomics score (radscore) and predict treatment response at the lesion and patient levels. Furthermore, a multivariable logistic analysis was used to design and evaluate a multivariable model in the training and validation cohorts. Results ROC curve analysis showed that the radscore generated by AutoML exhibited higher accuracy in predicting treatment response at the lesion level compared to metabolic parameters (SUVmax, MTV, and TLG) in both the training group (AUC: 0.791, 0.542, 0.667, 0.651, respectively) and the validation group (AUC: 0.712, 0.616, 0.639, 0.657, respectively). Multivariable logistic analysis indicated that NCCN-IPI (OR = 5.427, 95% CI: 1.163-25.317), BCL-2 (OR = 3.714, 95% CI: 1.406-9.816), TMTV (OR = 4.324, 95% CI: 1.095-17.067), and avg-radscore (OR = 3.176, 95% CI: 1.313-7. 686) were independent predictors of treatment response. The multivariable model comprising NCCN-IPI, BCL-2, TMTV, and avg-radscore outperformed conventional models and clinical-pathological models in predicting treatment response. (P<0.05). Conclusion The radscore generated by AutoML can predict the treatment response of elderly DLBCL patients, potentially aiding in clinical decision-making.

关键词： F-18-FDG PET/CT Diffuse large B-cell lymphoma Automated machine learning Treatment response Radiomics

来源：评论

学校读者我要写书评

暂无评论

Transmit Rate Enhancement for STAR-RIS-Assisted Uplink NOMA

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 7651-7665页

作者： Feng, Youhong Xu, Longzhu Li, Qiang Yan, Shihao Wang, Hong Ng, Derrick Wing Kwan Anhui Normal University School of Physics and Electronic information Wuhu241000 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Edith Cowan University School of Science and Security Research Institute JoondalupWA6027 Australia Nanjing University of Posts and Telecommunications School of Communication and Information Engineering Nanjing210003 China University of New South Wales School of Electrical Engineering and Telecommunications SydneyNSW2033 Australia

In this paper, a novel simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) enhanced uplink non-orthogonal multiple access (NOMA) communication network is investigated. Specifically, we tackle the transmit rate maximization problem for the strong user, subject to the constraints on total power consumption and the successive interference cancellation order, while guaranteeing the minimum quality-of-service requirement for the weak user. To address such a non-convex optimal problem, we introduce a novel, efficient, and low-complexity scheme. Specifically, the power allocation and receive beamforming optimization solutions are acquired in closed forms, and the transmission and reflection coefficients are obtained in semi-closed forms with a one-dimensional bisection search. Then, theoretical analysis demonstrates our proposed scheme has a lower complexity compared to the schemes with alternating direction method of multipliers (ADMM) and semidefinite relaxation (SDR) strategies, and the complexity advantage of our proposed scheme over the SDR and ADMM aided schemes becomes prominent when the number of RIS elements increase. Simulation results show that the proposed STAR-RIS-NOMA scheme achieves a better performance than the conventional STAR-RIS-aided orthogonal multiple access (OMA) scheme and STAR-RIS aided NOMA scheme adopting random phase shifts. More specifically, the proposed STAR-RIS-NOMA scheme outperforms the STAR-RIS-OMA scheme in terms of the strong user's rate, especially when the quality-of-service (QoS) requirements for weak user is high, or there is a significant difference channel quality between the reflecting and transmitting links. © 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

Multi-Modal Sensing and Lighting Estimation for PoE-Enabled Intelligent and Energy-Efficient Lighting networks

引用

IEEE Internet of Things Journal 2025年

作者： Tang, Liwei Xu, Yuanyuan Liu, Xiaodong Wang, Yuhao Wang, Jinyuan Shao, Huilong Nanchang University School of Information Engineering Nanchang330031 China Nanchang Laboratory Nanchang330224 China Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China

The application of power over Ethernet (PoE)-enabled lighting has emerged as a groundbreaking technology with the potential to achieve cooperative control and create an energy-saving lighting network. However, fine-grained user-side lighting environment perception is crucial to improve energy efficiency and user experience. To tackle this issue, a PoE-enabled intelligent lighting network with multi-modal sensing is proposed. Specifically, a multi-modal sensor is designed and installed on the side of the luminaire to provide both fine-grained lighting environment monitor and dimming. Then, a multilayer perceptron (MLP)-based estimation scheme is proposed to estimate the illumination and color temperature information around the user activity area. Moreover, an experimental lighting network is constructed and deployed in a classroom to measure practical lighting dataset. The proposed scheme effectively estimates the lighting quality on the user side based on the measurement data. Furthermore, based on the estimated information and the collaborative control capabilities of PoE, the operating current of the luminaire is updated in real time, and thus the ambient light resource is fully utilized. Finally, the proposed lighting network achieves a 39.99% energy saving. © 2014 IEEE.

关键词： Lighting fixtures

来源：评论

学校读者我要写书评

暂无评论

Cross-Modal Haptic Generation for Emergency Rescue in Internet of Robotic Things

引用

IEEE Internet of Things Journal 2025年

作者： Liu, Hengfa Wei, Xin Gao, Yun Zhou, Liang Qian, Yi Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing210003 China University of Nebraska-Lincoln Department of Electrical and Computer Engineering OmahaNE68588 United States

Robots equipped with multi-modal sensing capabilities play an important role in the Internet of Robotic Things (IoRT), especially in emergency rescue. However, existing rescue robots pose challenges for human operators in achieving precise manipulation due to the absence of haptic signals. Additionally, limited and fluctuating bandwidth in emergency rescue renders current cross-modal haptic generation schemes ineffective. To overcome this dilemma, we propose a novel cross-modal haptic generation scheme that enhances scalability across diverse network conditions by leveraging correlations among audio-visual-haptic modalities. Specifically, we first propose an edge-device collaboration-based architecture that dynamically extracts semantics from audio-visual signals, tailored to the current network conditions, for haptic generation. This is achieved by predicting the network state at the edge and performing multi-modal encoding and fusion at the device. Next, we design a scalable cross-modal haptic generation scheme that implements the optimal generation strategy based on received audio-visual semantics of different granularities, ensuring real-time acquisition of coarse-grained or fine-grained haptic feedback. Finally, numerical experimental results conducted on a multi-modal dataset and a simulated emergency environment indicate that the proposed scheme reliably generates haptic signals in emergency rescue. © 2025 IEEE.

关键词： Robots

来源：评论

学校读者我要写书评

暂无评论

Cross-Modal Haptic Compression Inspired by Embodied AI for Haptic communications

引用

IEEE Transactions on Multimedia 2025年

作者： Lu, Hang Tan, Xinmeng Chen, Mingkai Zhang, Zhe Zhang, Xuguang Chen, Jianxin Wei, Xin Zhao, Tiesong Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology China Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Fuzhou University Fujian Science & Technology Innovation Laboratory for Optoelectronic Information Fuzhou350108 China

Haptic data compression has gradually become a key issue for emerging real-time haptic communications in Tactile Internet (TI). However, it is challenging to achieve a tradeoff between high perceptual quality and compression ratio in haptic data compression scheme. Inspired by the perspective of embodied AI, we propose a cross-modal haptic compression scheme for haptic communications to improve the perception quality on TI devices in this paper. Since multimodal fusion is routinely employed to improve the ability of system in cognition, we assume that haptic codec is guided by visual semantics to optimize parameter settings in the coding process. We first design a multi-dimensional tactile feature fusion network (MTFFN) relying on multi-head attention mechanism. The MTFFN extracts the multi-dimensional features from the material surface and maps them to infer the coding parameters. Secondly, we provide second-order difference and linear interpolation to establish an criterion for the determination of optimal codec parameters, which are customized by the material categories so as to give high robustness. Finally, the simulation results reveal that our compression scheme can efficiently make a personalized codec procedure for different materials, obtaining more than 17% improvement in terms of compression ratio with high perceptual quality at the same time. © 2025 IEEE.

关键词： Data compression ratio

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：