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Multi-AAV-Assisted On-Demand Charging in Dense wireless Rechargeable sensor networks

IEEE INTERNET OF THINGS JOURNAL 2025年第7期12卷 8821-8834页

作者： Xiong, Runqun Chen, Ciyuan Xu, Jiajun Dong, Xirui Pu, Jiahang Southeast Univ Sch Comp Sci & Engn Nanjing 211189 Peoples R China Huawei Technol Suzhou Co Ltd Suzhou 215000 Peoples R China Southeast Univ Coll Software Engn Nanjing 211189 Peoples R China

wireless rechargeable sensor networks (WRSNs) have emerged as a promising solution to overcome the energy bottleneck in traditional battery-powered sensor networks. However, the uncertain energy demands and dense deployment of sensor nodes pose significant challenges to efficient charging scheduling in WRSNs. To address these challenges, this article proposes a novel multi-AAV assisted on-demand partial charging scheduling (MOPCS) algorithm. MOPCS integrates the advantages of one-to-many charging, partial charging, and dynamic multi-AAV coordination to maximize the network lifetime and energy utilization. The key contributions of this work include a real-time adaptive charging scheduling trigger mechanism, an energy-efficient charging cluster division method, a spatiotemporally balanced task allocation among multiple autonomous aerial vehicles (AAVs), and a hybrid priority-based charging path planning algorithm. Extensive simulations demonstrate that MOPCS significantly outperforms state-of-the-art algorithms in terms of charging request response timeliness, node survival rate, and AAV energy efficiency, especially in dense network deployments. This work provides valuable insights and practical solutions for the design and optimization of AAV-assisted charging scheduling in WRSNs, paving the way for more sustainable and scalable wireless sensor networks in various application scenarios.

关键词： Energy consumption Autonomous aerial vehicles Energy efficiency Dynamic scheduling wireless sensor networks Resource management Optimization Inductive charging Heuristic algorithms wireless communication On-demand schedule autonomous aerial vehicle (AAV)-assisted mobile charging wireless rechargeable sensor networks (WRSNs)

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Equivalent Bandwidth Concept and Its Usage in the network Selection

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China communications 2025年第2期22卷 213-225页

作者： Ma Anhua Pan Su Zhou Weiwei Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts and TelecommunicationsNanjing 210003China

Maximize the resource utilization efficiency and guarantee the quality of service(QoS)of users by selecting the network are the key issues for heterogeneous network operators,but the resources occupied by users in different networks cannot be compared *** paper proposes a network selection algorithm for heterogeneous ***,the concept of equivalent bandwidth is proposed,through which the actual resources occupied by users with certain QoS requirements in different networks can be compared *** the concept of network applicability is defined to express the abilities of networks to support different *** proposed network selection algorithm first evaluates whether the network has enough equivalent bandwidth required by the user and then prioritizes network with poor applicability to avoid the situation that there are still residual resources in entire network,but advanced services can not be *** simulation results show that the proposed algorithm obtained better performance than the baselines in terms of reducing call blocking probability and improving network resource utilization efficiency.

关键词： call blocking probability equivalent bandwidth heterogeneous network network applicability

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A teacher-student based attention network for fine-grainedimage recognition

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Digital communications and networks 2025年第1期11卷 52-59页

作者： Ang Li Xueyi Zhang Peilin Li Bin Kang Key Laboratory of Broadband Wireless Communication and Sensor Network Technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing210003China School of Communications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing210003China School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing210003China

Fine-grained Image Recognition(FGIR)task is dedicated to distinguishing similar sub-categories that belong to the same super-category,such as bird species and car *** order to highlight visual differences,existing FGIR works often follow two steps:discriminative sub-region localization and local feature ***,these works pay less attention on global context *** neglect a fact that the subtle visual difference in challenging scenarios can be highlighted through exploiting the spatial relationship among different subregions from a global view ***,in this paper,we consider both global and local information for FGIR,and propose a collaborative teacher-student strategy to reinforce and unity the two types of *** framework is implemented mainly by convolutional neural network,referred to Teacher-Student Based Attention Convolutional Neural network(T-S-ACNN).For fine-grained local information,we choose the classic Multi-Attention network(MA-Net)as our baseline,and propose a type of boundary constraint to further reduce background noises in the local attention *** this way,the discriminative sub-regions tend to appear in the area occupied by fine-grained objects,leading to more accurate sub-region *** fine-grained global information,we design a graph convolution based Global Attention network(GA-Net),which can combine extracted local attention maps from MA-Net with non-local techniques to explore spatial relationship among *** last,we develop a collaborative teacher-student strategy to adaptively determine the attended roles and optimization modes,so as to enhance the cooperative reinforcement of MA-Net and *** experiments on CUB-200-2011,Stanford Cars and FGVC Aircraft datasets illustrate the promising performance of our framework.

关键词： Fine-grained image recognition Collaborative teacher-student strategy Multi-attention Global attention

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A Novel Spatiotemporal Correlation Anomaly Detection Method Based on Time-Frequency-Domain Feature Fusion and a Dynamic Graph Neural network in wireless sensor network

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IEEE sensors Journal 2025年第9期25卷 15548-15563页

作者： Ye, Miao Jiang, Zhibang Xue, Xingsi Li, Xingwang Wen, Peng Wang, Yong School of Information and Communication Guilin University of Electronic Technology Guilin541004 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fujian Fuzhou350118 China School of Physics and Electronic Information Engineering Henan Polytechnic University Jiaozuo454099 China

Attention-based transformers have played an important role in wireless sensor network (WSN) timing anomaly detection due to their ability to capture long-term dependencies. However, there are several issues that must be addressed, such as the fact that their ability to capture long-term dependencies is not completely reliable, their computational complexity levels are high, and the spatiotemporal features of WSN timing data are not sufficiently extracted for detecting the correlation anomalies of multinode WSN timing data. To address these limitations, this article proposes a WSN anomaly detection method that integrates frequency-domain features with dynamic graph neural networks (GNNs) under a designed self-encoder reconstruction framework. First, the discrete wavelet transform (DWT) effectively decomposes trend and seasonal components of time series to solve the poor long-term reliability of transformers. Second, a frequency-domain attention mechanism (FDAM) is designed to make full use of the difference between the amplitude distributions of normal data and anomalous data in this domain. Finally, a multimodal fusion-based dynamic graph convolutional network (MFDGCN) is designed by combining an attention mechanism and a graph convolutional network (GCN) to adaptively extract spatial correlation features. A series of experiments conducted on public datasets and their results demonstrate that the anomaly detection method designed in this article exhibits superior precision and recall than the existing methods do, with an F1 score of 93.5%, representing an improvement of 2.9% over that of the existing models. © 2025 IEEE. All rights reserved.

关键词： Normal distribution

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AUV-aided isolated sub-network prevention for reliable data collection by underwater wireless sensor networks

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COMPUTER networkS 2025年 262卷

作者： Nandyala, Chandra Sukanya Cho, Ho-Shin Kyungpook Natl Univ Sch Elect & Elect Engn Daegu 41556 South Korea

The unique characteristics of the underwater environment, such as limited infrastructure, challenging acoustic communication channels, and constrained battery power of underwater sensor nodes, significantly impact the overall network lifetime of underwater wireless sensor networks (UWSNs). In a multi-hop UWSN, the death of a special node - cut-vertex (CV) - divides the network into the main network and an isolated sub-network (ISN). The UWSN may struggle to operate continuously and efficiently owing to the death of underwater sensor nodes, resulting in a shorter network lifetime and reduced data reliability. Consequently, the data generated by the ISN is lost. To address this issue, this paper presents an autonomous underwater vehicle (AUV)-aided ISN prevention protocol for UWSNs. The proposed protocol employs an AUV to explore and identify a CV by utilizing the information collected from the sensor nodes. Subsequently, the AUV predicts the future residual energy of the CV, ensuring its arrival near the CV prior to the energy depletion of the CV and the formation of an ISN. Then, instead of the CV, the AUV directly collects data from the CV-associated sensor nodes while the CV harvests energy. The CV replenishes its energy by harnessing ambient underwater sources and subsequently reintegrates into the network after attaining sufficient energy recharge. In this study, we evaluate the performance of the proposed protocol by comparing it with the Q-learning-based topology-aware routing protocol, a hybrid data-collection scheme, stratification-based data-collection scheme, and Q-learning- based energy-efficient and lifetime-aware routing protocol in terms of the lifetime of the network, lifetime of the CVs, energy consumption, end-to-end delay, and packet delivery ratio.

关键词： Autonomous underwater vehicle (AUV) Chapman-Kolmogorov equation Data-collection Cut-vertex Isolated sub-network Underwater wireless sensor networks

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Research on electro-optical chaotic communication based on optical feedback mutual injection

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OPTICS communicationS 2025年 583卷

作者： Mo, Ke-Yuan Huang, Yu-Gang Li, Zhao-Yun Tao, Zhi-Yong Fan, Ya-Xian Guilin Univ Elect Technol Guangxi Key Lab Wireless Wideband Commun & Signal Guilin 541004 Peoples R China China Elect Technol Grp Corp Res Inst 34 Guilin 541004 Peoples R China Guilin Univ Elect Technol Acad Marine Informat Technol Beihai 536000 Peoples R China

In this paper, an electro-optical chaotic communication scheme based on optical feedback inter-injection is proposed, which employs two inter-injection structures consisting of intensity-modulated and phase-modulated feedback branches and introduces optical feedback at the intensity-modulated end to realize a chaotic signal output with high complexity. Simulation results show that when the feedback gain coefficient is 0.6, the alignment entropy of the system reaches more than 0.9, which possesses optical chaotic signal output characteristics with high complexity, and when the feedback gain coefficient is lower than 0.1, the output time series starts bifurcation behavior, which does not require very large feedback gain coefficients under the condition of which the system time-delay characteristics can be hidden. At the same time, the scheme has less influence on the synchronization by the feedback gain coefficient mismatch and higher sensitivity to the time delay mismatch parameter, which indicates that the scheme can enhance the robustness of the system while improving the high security of the system when the time delay is used as the key.

关键词： Optical feedback Mutual injection Chaotic communication Delay feature hiding

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Energy Consumption Minimizing Through an Efficient UAV Trajectory in Maritime communications

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IEEE TRANSACTIONS ON VEHICULAR technology 2025年第4期74卷 6756-6760页

作者： Xin, Yuanxue Ma, Lin Zhang, Jun Shi, Pengfei You, Xiaohu Hohai Univ Coll Informat Sci & Engn Jiangsu Key Lab Power Transmiss & Distribut Equipm Nanjing 213000 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Jiangsu Key Lab Wireless Commun Nanjing 210003 Peoples R China Hohai Univ Coll Artificial Intelligence & Automat Nanjing 213000 Jiangsu Peoples R China Southeast Univ Sch Informat Sci & Engn Nanjing 211189 Jiangsu Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 211189 Peoples R China

In this paper, we propose a maritime unmanned aerial vehicle (UAV) flight trajectory strategy which minimizes the energy consumption while guaranteeing the Quality of Service (QoS) for vessel users. In particular, a realistic flying model for the UAV with acceleration and deceleration stages during the entire flight is considered. To ensure communication coverage and maintain the QoS for each vessel user, a flying-hovering scheme with a QoS-ensured hovering points (QHP) algorithm is presented. Furthermore, the successive convex approximation (SCA) technique is employed to minimize the sum energy consumption concerning the non-uniform velocity trajectory for the UAV. Numerical results demonstrate that the proposed joint optimization strategy effectively reduces the system energy consumption while ensuring the quality of service for vessel users.

关键词： Autonomous aerial vehicles Energy consumption Quality of service Trajectory wireless communication Rotors Signal to noise ratio Propulsion Optimization communication system security UAV communication suboptimal fermat points hovering points UAV trajectory design

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Wi-Fitness: Improving Wi-Fi Sensing With Video Perception for Smart Fitness

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IEEE INTERNET OF THINGS JOURNAL 2025年第3期12卷 2876-2889页

作者： Wei, Mengli Zhao, Daguo Zhang, Lei Wang, Cheng Zhang, Yonggang Wang, Qi Fan, Xiaochen Zhong, Yaping Mao, Shiwen Wuhan Sports Univ Sports Big Data Res Ctr Wuhan 430079 Peoples R China Tianjin Univ Coll Intelligence & Comp Tianjin 300050 Peoples R China Tianjin Univ Tianjin Key Lab Adv Network Technol & Applicat Tianjin 300050 Peoples R China Qilu Univ Technol Shandong Acad Sci Key Lab Comp Power Network & Informat Secur Minist Educ Jinan Peoples R China Tongji Univ Minist Educ Key Lab Embedded Syst & Serv Comp Shanghai 200092 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engineer Minist Educ Changchun 130012 Peoples R China Tiangong Univ Sch Elect & Informat Engn Tianjin 300387 Peoples R China Tiangong Univ Tianjin Key Lab Optoelect Detect Technol & Syst Tianjin 300387 Peoples R China Tsinghua Univ Inst Elect & Informat Technol Tianjin Tianjin 300467 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Auburn Univ Dept Elect & Comp Engn Auburn AL 36849 USA

With advancements in AI, smart home gyms are becoming increasingly popular for providing fitness assistance in indoor environments. In this research, we propose a layer-by-layer framework, called Wi-Fitness, which bridges video perception with Wi-Fi sensing for smart fitness. At the data preprocessing layer, the singular value decomposition-based channel state information denoising mechanism is leveraged to do the Wi-Fi data calibration. Diverse and high-quality training samples are generated by a random quantization-based data augmentation method. At the bimodal fusion layer, the heterogeneity between the Wi-Fi and video is mitigated by the local attention mechanism and the bimodal feature integration mechanism. For the video modality, the attention-based spatio-temporal graph convolutional network (AST-GCN Net) is proposed to refine spatial information. The spatio-temporal semantic alignment module is proposed to transfer spatial information from video to Wi-Fi and maintain temporal consistency across modalities. The fitness assessment layer provides exercise visualization. The generalization of Wi-Fitness is enhanced by layer-by-layer collaboration. Wi-Fitness demonstrates its effectiveness by achieving an average F1-Score of 92.68% in three typical indoor environments.

关键词： wireless fidelity sensors Feature extraction Sports Semantics Behavioral sciences Skeleton Privacy wireless sensor networks Training Action recognition channel state information (CSI) multimodal skeleton Wi-Fi

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A Novel WiFi-Based Temporal Precision Detection System With Enhanced CSI Sampling

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IEEE wireless communicationS LETTERS 2025年第1期14卷 128-132页

作者： Huang, Jin Tian, Yue Hu, Xuejie Li, Zhidu Xiamen Univ Technol Fujian Key Lab Commun Network & Informat Proc Xiamen 361024 Peoples R China Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China

Integrated sensing and communication (ISAC) has emerged as a prominent research focus in the domains of 5G-Advanced (5G-A), 6G, and wireless fidelity (WiFi). As a passive sensing technology, WiFi-based human detection has garnered widespread attention due to its privacy, unobtrusiveness, and convenience in practical applications. This letter introduces a WiFi-based human intrusion detection system utilizing channel state information (CSI). By refining the CSI phase sampling points through the proposed sequence particle filter (SPF) CSI sampling method, the system reduces the amount of data needed for real-time sensing. A comprehensive preprocessing procedure is presented to filter out noise interference and mitigate channel fading during CSI collection. The proposed human intrusion detection algorithm accurately identifies fluctuations in the CSI phase time series, thereby determining the presence of a human and the exact moments of intrusion.

关键词： sensors wireless communication wireless fidelity Sampling methods Intrusion detection Bandwidth wireless sensor networks Real-time systems Particle filters OFDM Integrated sensing and communication channel state information WiFi human intrusion detection

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UAV communication in Space-Air-Ground Integrated networks (SAGINs): Technologies, Applications, and Challenges

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DRONES 2025年第2期9卷 108-108页

作者： Zhang, Peiying Chen, Shengpeng Zheng, Xiangguo Li, Peiyan Wang, Guilong Wang, Ruixin Wang, Jian Tan, Lizhuang China Univ Petr East China Qingdao Inst Software Coll Comp Sci & Technol Qingdao 266580 Peoples R China Shandong Key Lab Intelligent Oil & Gas Ind Softwar Qingdao 266580 Peoples R China Qilu Univ Technol Key Lab Comp Power Network & Informat Secur Minist EducShandong Comp Sci Ctr Natl Supercomp Ctr JinanShandong Acad Sci Jinan 250014 Peoples R China China Univ Petr East China Coll Sci Qingdao 266580 Peoples R China Shandong Fundamental Res Ctr Comp Sci Shandong Prov Key Lab Comp Power Internet & Serv C Jinan 250014 Peoples R China

With the continuous advancement of 6G technology, SAGINs provide seamless coverage and efficient connectivity for future communications by integrating terrestrial, aerial, and satellite networks. Unmanned aerial vehicles (UAVs), owing to their high maneuverability and flexibility, have emerged as a critical component of the aerial layer in SAGINs. In this paper, we systematically review the key technologies, applications, and challenges of UAV-assisted SAGINs. First, the hierarchical architecture of SAGINs and their dynamic heterogeneous characteristics are elaborated on, and this is followed by an in-depth discussion of UAV communication. Subsequently, the core technologies of UAV-assisted SAGINs are comprehensively analyzed across five dimensions-routing protocols, security control, path planning, resource management, and UAV deployment-highlighting the progress and limitations of existing research. In terms of applications, UAV-assisted SAGINs demonstrate significant potential in disaster recovery, remote network coverage, smart cities, and agricultural monitoring. However, their practical deployment still faces challenges such as dynamic topology management, cross-layer protocol adaptation, energy-efficiency optimization, and security threats. Finally, we summarize the applications and challenges of UAV-assisted SAGINs and provide prospects for future research directions.

关键词： 6G wireless communication Space-Air-Ground Integrated networks unmanned aerial vehicle

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