检索结果-内蒙古大学图书馆

Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

来源：评论

学校读者我要写书评

暂无评论

Unimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation

引用

IEEE Transactions on Mobile Computing 2025年

作者： Zhang, Rongyu Chi, Xiaowei Zhang, Wenyi Liu, Guiliang Wang, Dan Wang, Fangxin Shenzhen China The Hong Kong Polytechnic University Department of Computing Hong Kong The Hong Kong University of Science and Technology Hong Kong Department of Electrical Engineering and Computer Science University of California Irvine United States Shenzhen China Shenzhen China Guangdong Provincial Key Laboratory of Future Networks of Intelligence China

Multimodal learning has significantly advanced the extraction of features from varied data sources, enhancing model performance. Federated learning (FL) complements this by enabling collaborative training while maintaining data privacy. The fusion of these two fields, multimodal federated learning, offers considerable promise. Yet, standard methods often incorrectly assume that each node in the FL network has a full complement of multimodal data, which is rare in real-world applications. In our study, we present a novel architecture designed to surmount these challenges, termed the Unimodal Training - Multimodal Prediction (UTMP) framework, positioned within the multimodal federated learning paradigm. Our proposed model, the HA-Fedformer, is a transformer-based model crafted to facilitate unimodal training on the client-side using exclusively unimodal datasets and to execute multimodal inference by synthesizing insights from multiple clients. Our HA-Fedformer model effectively handles non-IID data through a novel uncertainty-aware aggregation technique and layer-wise Markov Chain Monte Carlo sampling in local encoders. It also resolves misaligned language sequences via cross-modal decoder aggregation, capturing correlations between decoders trained on different modalities. Our comprehensive evaluations conducted on widely recognized sentiment analysis benchmarks demonstrate the superiority of the HA-Fedformer. The results show that our model achieves a substantial uplift in performance. © 2002-2012 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Blind Joint Multi-DFO Estimation for High-Mobility OFDM Communication Systems

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Feng, Yunqi Zhu, Zhehua Lu, Weidang Zhao, Nan Nallanathan, Arumugam Zhejiang University of Technology College of Information Engineering Key Laboratory of Communication Networks and Applications of Zhejiang Province Hangzhou310023 China Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of

In high-mobility communication systems, the relative motion between the transceivers will cause severe Doppler shifts, resulting in the doubly-selective fading channel. In this correspondence, a blind joint multiple Doppler frequency offsets (DFOs) estimator is proposed for high-mobility communication with orthogonal frequency division multiplexing (OFDM). Both the receive beamforming and multi-beamformer redundancy are employed to estimate and compensate multiple DFOs, thereby effectively mitigating the channel time-variation. Moreover, the inter-channel interference (ICI) has been derived to further analyze the impact of residual DFOs due to the estimation error on the system performance. Numerical results verify that the proposed blind estimator substantially outperforms existing ones. © 1967-2012 IEEE.

关键词： Frequency allocation

来源：评论

学校读者我要写书评

暂无评论

STARS-Enabled Full-Duplex Two-Way mMIMO System Under Spatially-Correlated Channels

arXiv

引用

arXiv 2025年

作者： Papazafeiropoulos, Anastasios Kourtessis, Pandelis Chatzinotas, Symeon Kaklamani, Dimitra I. Venieris, Iakovos S. The Communications and Intelligent Systems Research Group University of Hertfordshire HatfieldAL10 9AB United Kingdom SnT The University of Luxembourg Luxembourg The Microwave and Fiber Optics Laboratory Greece The Intelligent Communications and Broadband Networks Laboratory School of Electrical and Computer Engineering National Technical University of Athens Athens Zografou15780 Greece

Low-cost reconfigurable intelligent surfaces (RISs) are being considered as promising physical-layer technology for next-generation wireless networks due to their ability to re-engineer the propagation environment by tuning their elements. Although RIS-aided systems have many advantages, one of their major bottlenecks is that they can provide coverage only in front of the surface. Fortunately, simultaneous transmitting and reflecting surface (STARS)-assisted systems have emerged to fill this gap by providing 360◦ wireless coverage. In parallel, full-duplex (FD) communication offers a higher achievable rate through efficient spectrum utilization compared to the half-duplex (HD) counterpart. Moreover, two-way/bi-directional communications in an FD system can further enhance the system’s spectral efficiency. Hence, in this paper, we propose a STARS-enabled massive MIMO deployment in an FD two-way communication network for highly efficient spectrum utilization, while covering the dead zones around the STARS. This model enables simultaneous information exchange between multiple nodes, while potentially doubling the spectral efficiency (SE). By invoking the use-and-then-forget (UaTF) combining scheme, we derive a closed-form expression for an achievable SE at each user of the system considering both uplink and downlink communications based on statistical channel state information (CSI), while also accounting for imperfect CSI and correlated fading conditions. Moreover, we formulate an optimization problem to obtain an optimal passive beamforming matrix design at the STARS that maximizes the sum achievable SE. The considered problem is non-convex and we propose a provably-convergent low-complexity algorithm, termed as projected gradient ascent method (ProGrAM), to obtain a stationary solution. Extensive numerical results are provided to establish the performance superiority of the FD STARS-enabled system over the HD STARS-enabled and FD conventional RIS (cRIS)-enabled coun

关键词： Digital television

来源：评论

学校读者我要写书评

暂无评论

Beam Pattern Modulation Embedded Hybrid Transceiver Optimization for Integrated Sensing and Communication

引用

IEEE Transactions on Wireless Communications 2025年

作者： Liu, Boxun Gao, Shijian Yang, Zonghui Cheng, Xiang Yang, Liuqing Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Internet of Things Thrust Guangzhou511400 China Internet of Things Thrust Intelligent Transportation Thrust Guangzhou511400 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Department of Civil and Environmental Engineering SAR Hong Kong Hong Kong

Integrated sensing and communication (ISAC) emerges as a promising technology for 6G, particularly in the millimeter-wave (mmWave) band. However, the widely utilized hybrid architecture in mmWave systems compromises multiplexing gain due to the constraints of limited radio-frequency (RF) chains. Moreover, additional sensing functionalities exacerbate the impairment of spectrum efficiency (SE). In this paper, we present an optimized beam pattern modulation-embedded ISAC (BPM-ISAC) transceiver design, which spares one RF chain for sensing and uses the remaining ones for communication. To compensate for the reduced SE, index modulation across communication beams is applied. We formulate an optimization problem aimed at minimizing the mean squared error (MSE) of the sensing beampattern, subject to a symbol MSE constraint. This problem is then solved by sequentially optimizing the analog and digital parts. Both the multi-aperture structure (MAS) and the multi-beam structure (MBS) are considered in the analog part. We conduct theoretical analysis on the asymptotic pairwise error probability (APEP) and the Cramér-Rao bound (CRB) of direction of arrival (DoA) estimation. Numerical simulations validate the overall enhanced ISAC performance over existing alternatives. © 2025 IEEE. All rights reserved.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

Synesthesia of Machines (SoM)-Enhanced Wideband Multi-User CSI Learning With LiDAR Sensing

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Zhang, Haotian Gao, Shijian Cheng, Xiang Yang, Liuqing Peking University State Key Laboratory of Photonics and Communications School of Electronics Beijing100871 China Guangzhou511400 China The Chinese University of Hon g Kong Guangdong Provincial Key Laboratory of Future Networks of Intelligence Shenzhen China Internet of Things Thrust Intelligent Transportation Thrust Guangzhou510000 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

Light detection and ranging (LiDAR) has been utilized for optimizing wireless communications due to its ability to detect the environment. This paper explores the use of LiDAR in channel estimation for wideband multi-user multiple-input-multiple-output orthogonal frequency division multiplexing systems and introduces a LiDAR-Enhanced Channel State Information (CSI) Learning Network (LE-CLN). By utilizing user positioning information, LE-CLN first calculates user-localized over-complete angular measurements. It then investigates the correlation between LiDAR and CSI, transforming raw LiDAR data into a low-complexity format embedded with signal propagation characteristics. LE-CLN also adapts the use of LiDAR based on channel conditions through attention mechanisms. Thanks to the unique wireless features offered by LiDAR, LE-CLN achieves higher estimation accuracy and spectrum efficiency compared to benchmarks, particularly in latency-sensitive applications where pilot transmissions are expected to be reduced. © 1967-2012 IEEE.

关键词： Orthogonal frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

An Efficient Multi-band Infrared Small Objects Detection Approach for Low-Altitude Artificial Intelligence of Thing

引用

IEEE Internet of Things Journal 2025年

作者： Peng, Yuhuai Wang, Jing Wang, Wenqian Liu, Lei Atiquzzaman, Mohammed Guizani, Mohsen Dustdar, Schahram Northeastern University School of Computer Science and Engineering Shenyang110819 China Zhiyuan Research Institute Hangzhou310024 China Northeastern University School of Computer Science and Engineering Shenyang110819 China Xidian University State Key Laboratory of Integrated Service Networks Xi'an710071 China University of Oklahoma School of Computer Science NormanOK73019 United States Mohamed Bin Zayed University of Artificial Intelligence Department of Machine Learning Masdar United Arab Emirates Technische Universität Wien Distributed Systems Group Vienna1040 Austria

As a cutting-edge technology of low-altitude Artificial Intelligence of Thing (AIoT), UAV object detection significantly enhances the surveillance services capabilities of low-altitude AIoT. However, the difficulty of object detection is exacerbated by the high proportion of small and obscure objects in the captured images. To address the mentioned challenges, we present an efficient multi-band infrared small object detection approach for low-altitude intelligent surveillance services. Firstly, we propose the Multi-band infrared Image Fusion algorithm based on Cascade-GAN (MIF-CGAN), which produces fused images with high information entropy and high contrast. Then, the Transformer-based Multi-scale Dense Small Object Detection (MsDSOD) algorithm is proposed. The algorithm consists of the Global-Local Object Detection (G-LOD) network, the Object Dense Area Extraction (O-DAE) module, and the Weighted Boxes Fusion (WBF) module. It extracts small objects features at different scales from infrared images and fuses the global and local detection results to accurately identify small objects in dense scenes. Furthermore, compared to the traditional algorithms, the mean Average Precision (mAP) of MsDSOD is improved by 0.80% and the Average Precision in small object detection (APs) is improved by 0.72%. The proposed algorithm is optimally suited to deal with complex scenes with dense small objects and background occlusion. © 2014 IEEE.

关键词： Infrared imaging

来源：评论

学校读者我要写书评

暂无评论

Intelligent Energy-Efficient Resource Allocation for Multi-UAV-Assisted Mobile Edge Computing networks

引用

China Communications 2025年第4期22卷 339-355页

作者： Hu Han Shen Le Zhou Fuhui Wang Qun Zhu Hongbo The China Information Consulting and Designing Institute CO. Ltd.Nanjing 210000China The Jiangsu Key Laboratory of Wireless Communications(Nanjing University of Posts and Telecommunications) Nanjing 210003China The Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of Education(Nanjing University of Posts and Telecommunications)Nanjing 210003China The College of Artificial Intelligence(Nanjing University of Aeronautics and Astronautics) Nanjing 210000China The Department of Computer Science(San Francisco State University) San FranciscoCAUSA

The unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)has been deemed a promising solution for energy-constrained devices to run smart applications with computationintensive and latency-sensitive requirements,especially in some infrastructure-limited areas or some emergency ***,the multi-UAVassisted MEC network remains largely *** this paper,the dynamic trajectory optimization and computation offloading are studied in a multi-UAVassisted MEC system where multiple UAVs fly over a target area with different trajectories to serve ground *** considering the dynamic channel condition and random task arrival and jointly optimizing UAVs'trajectories,user association,and subchannel assignment,the average long-term sum of the user energy consumption minimization problem is *** address the problem involving both discrete and continuous variables,a hybrid decision deep reinforcement learning(DRL)-based intelligent energyefficient resource allocation and trajectory optimization algorithm is proposed,named HDRT algorithm,where deep Q network(DQN)and deep deterministic policy gradient(DDPG)are invoked to process discrete and continuous variables,*** results show that the proposed HDRT algorithm converges fast and outperforms other benchmarks in the aspect of user energy consumption and latency.

关键词： dynamic trajectory optimization intelligent resource allocation unmanned aerial vehicle uav assisted uav assisted mec energy efficiency smart applications mobile edge computing mec deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Using Depth-Enhanced Spatial Transformation for Student Gaze Target Estimation in Dual-View Classroom Images

Using Depth-Enhanced Spatial Transformation for Student Gaze...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Haonan Miao Peizheng Zhao Yuqi Sun Fang Nan Xiaolong Zhang Yaqiang Wu Feng Tian School of Computer Science and Technology Xi’an Jiaotong University Xi’an China Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an China School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou China Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Dual-view gaze target estimation in classroom environments has not been thoroughly explored. Existing methods lack consideration of depth information, primarily focusing on 2D image information and neglecting the latent 3D spatial context, which could lead to suboptimal transformation and cause the gaze cone to intersect with an incorrect object. This paper introduces a novel dual-view gaze target estimation method tailored for classroom settings, leveraging depth-enhanced spatial transformations. By formulating a depth-enhanced 2D space, our method uses depth-enhanced spatial transformation to accurately project students’ gaze cones to the teacher-oriented image. Additionally, we collected a dataset named DVSGE, specifically for student gaze target estimation in dual-view classroom images. Experimental results demonstrate significant performance improvements of 9.8% in AUC and 19.9% in L2-Distance for our method, surpassing existing methods.

关键词： Three-dimensional displays Estimation Focusing Signal processing Acoustics Speech processing

来源：评论

学校读者我要写书评

暂无评论

Uplink Control Information Based Clustered Access and Discontinuous Reception Management for mMTC

引用

IEEE Communications Letters 2025年

作者： Wang, Shao-Di Wang, Chang-Long Wang, Hui-Ming Zhou, Feng Leung, Victor C. M. Xidian University Key Laboratory of Electronic Information Countermeasure and Simulation Technology of Ministry of Education Xi’an710071 China Xi’an Jiaotong University School of Information and Communication Engineering Ministry of Education Key Lab for Intelligent Networks and Network Security Xi’an710049 China Shenzhen MSU BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Uplink control information (UCI) and discontinuous reception (DRX) play important roles for massive machine type communication (mMTC). Despite their standalone significance, a conspicuous gap exists in comprehensively exploring the synergy between UCI and DRX concerning both energy conservation and latency reduction for mMTC. In this letter, we propose a UCI-based clustered access and DRX management (UCADM) scheme that strikes a balance between these two critical performance metrics, reducing energy usage while preserving low latency in uplink-downlink interaction for mMTC. Specifically, we present a strictly feasible solution for the proposed UCADM scheme by using the spectral radius and the constraint projection, which can effectively solve DRX switching operations as indicated by scheduling information from UCI. Simulation results confirm the effectiveness of our scheme. © 1997-2012 IEEE.

关键词： Information management

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：