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KNIGCN: Key Node Identification in UAV Swarm Networks with Graph Convolution Networks

IEEE Internet of Things Journal 2025年第11期12卷 16227-16242页

作者： Ai, Qixun Hou, Changbo Zhou, Zhichao Wu, Xiangyu Song, Zhen Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Harbin Engineering University College of Information and Communication Engineering Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin150001 China

In the field of Internet of Things (IoT), Unmanned Aerial Vehicle (UAV) swarms are widely used to assist IoT communication due to their simple deployment, high mobility and high cost effectiveness to help improve IoT network coverage and topological flexibility. However, due to the openness of UAV swarm network, UAV nodes are vulnerable to malicious attacks and fail, especially some key nodes, which will seriously degrade the network performance. To solve this problem, a key node identification model based on Graph Convolutional Networks (GCN), named KNIGCN, is proposed. Specifically, the topology model of UAV cluster network is firstly built based on Flying Ad Hoc Network (FANET) communication architecture and Dijkstra's algorithm, then node criticality labels in the network are made by means of traffic statistics, and finally KNIGCN model is used to predict the criticality scores of each node and sort them so as to screen out a certain number of key nodes. The experimental results show that the model has good performance of key node identification. Compared with traditional methods, the proposed method makes a more reasonable judgment of node criticality, and the key nodes identified have a more important impact on network performance. Moreover, the proposed scheme can effectively improve the identification speed of key nodes in large-scale, complex or dynamically changing topology of UAV cluster networks. It can provide an effective scheme for maintaining the security and stability of UAV swarm network communication. © 2014 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Morris-Lecar model with novel fast-slow structure and its FPGA implementation

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Science China Technological Sciences 2025年第5期68卷 215-225页

作者： Xihong YU Lilian HUANG Han BAO Bocheng BAO College of Information and Communication Engineering Key Laboratory of Advanced Marine Communication and Information Technology (Ministry of Industry and Information Technology)National Key Laboratory of Underwater Acoustic TechnologyHarbin Engineering University Wang Zheng School of Microelectronics Changzhou University

The Morris-Lecar model is a neuronal model designed to replicate the oscillatory activity of barnacle giant muscle fibers. This work presents a three-dimensional Morris-Lecar model with a novel fast-slow structure. The model introduces a current containing slow variables, thereby forming a new fast-slow structure with the membrane potential. Numerical results reveal the existence of two independent unstable foci and complex dynamical behaviors that include period-doubling bifurcations and spiking/bursting activities. Two types of bifurcation mechanisms for bursting activities are elucidated through theoretical analysis based on four typical bursting activities. Finally, a digital neuronal circuit was developed based on FPGA, and experimental results show good consistency with numerical results.

关键词： Morris-Lecar model fast-slow structure firing activity bifurcation mechanism digital neuronal circuit

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CMShipReID: A Cross-Modality Ship Dataset for the Reidentification Task

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 10503-10513页

作者： Xu, Congan Gao, Long Liu, Yu Zhang, Qi Su, Nan Zhang, Shaoxuan Li, Tianyu Zheng, Xiaomei Naval Aviation University Yantai264000 China Harbin Engineering University Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology College of Information and Communication Engineering Harbin150009 China

Image-based ship target analysis is an important task for ship monitoring and maritime security. Previous studies achieved remarkable results in ship detection and recognition tasks but mainly relied on single-modality datasets. So far, no ship reidentification dataset has been collected, restricting cross-modality reidentification research. To solve this problem, we construct the first cross-modality ship reidentification dataset, CMShipReID, which contains visible light, near-infrared, and thermal infrared modalities collected by autonomous aerial vehicle. It consists of ten categories, about 138 identifications, and 8337 images. This dataset provides rich and high-quality data support for cross-modal ship reidentification research. We use mainstream reidentification algorithms as benchmarks of this research field. © 2008-2012 IEEE.

关键词： Reamers

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Recticoil for Efficient Compact Inductive Power Transfer

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IEEE Transactions on Power Electronics 2025年第7期40卷 10154-10164页

作者： Yi, Zixuan Qin, Yuanyuan Yang, Xue-Xia Shao, Yaoxia Zeng, Dan Li, Meiling Shanghai University School of Communication and Information Engineering Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science Shanghai200444 China Hangzhou City University School of Information and Electrical Engineering Hangzhou310015 China

The MHz inductive power transfer (IPT) system has broad application prospects due to its high safety, longer transmission distance, and better tolerance for misalignment. However, the increase in frequency will lead to an increased loss of lumped components, such as inductors and capacitors, in peripheral circuits, thereby reducing efficiency. This is currently the bottleneck problem encountered by MHz IPT. To address this key challenge, researchers have tried to remove the lumped components in the peripheral circuit while ensuring the functions of the IPT system. One successful and beneficial attempt is the self-resonant coil, which replaces traditional lumped resonant capacitors with distributed capacitors formed by coil turn-to-turn capacitance, ensuring compensation for leakage inductance and eliminating reactive power. This innovative integration makes efficiency and integration greatly improved. In this article, the novel coil named Recticoil, on which the rectification function is integrated further, is proposed for efficient compact IPT. Recticoil can directly output dc power without additional compensation and rectification circuits. By analyzing a toroidal coil where two separate conductors generate a voltage differential, and incorporating two diodes, resulting in a dc output. Subsequently, the self-resonant coil replaces the toroidal coil to form Recticoil, and the equivalent circuits of Recticoil are given and analyzed. In addition, the analysis and test method of rectification efficiency is given. The experimental results show that the Recticoil achieves a rectification efficiency as high as 97.25% at 6.78 MHz, outperforming both the bridge rectifier and the Class E rectifier. Additionally, the compact construction of Recticoil eliminates the volume of traditional rectifiers. All of these advantages of Recticoil render it a promising candidate for applications in wearables and miniaturized devices. © 1986-2012 IEEE.

关键词： Equivalent circuits

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An HF channel parameter estimation method based on HR-IPFrFT

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Advances in Space Research 2025年第10期75卷 7624-7644页

作者： Guo, Qiang Na, Bo Douplii, Stepan College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Key Laboratory of Advanced Ship Communication and Information Technology Harbin Engineering University Harbin150001 China Universität Münster Röntgenstrasse 7-13 Münster Germany

The long-distance high-frequency (HF) ionospheric channel is characterized by high noise levels and severe signal fading, which seriously affects signal capture and channel parameter extraction. Chirp continuous wave is often applied as a transmitted waveform due to its anti-noise and anti-Doppler advantages. The periodic fractional Fourier transform (PFrFT) algorithm possesses the optimal detection capability for chirp continuous waves. It can achieve periodic energy accumulation at the specific order. This paper proposes a new HF channel parameter estimation method combining their advantages. Firstly, an high-resolution improved periodic fractional Fourier transform (HR-IPFrFT) algorithm is introduced. This algorithm adapts the kernel function to fit the periodic chirp signal and then gives the periodic non-coherent accumulation expression for the discrete HR-IPFrFT. In this expression, two adjustable factors introduced can flexibly adjust the fractional domain range. Further, it is demonstrated that the HR-IPFrFT shows time-shifted and frequency-shifted properties. The parameter estimation method uses a dual-chirp continuous wave as the transmitted signal. By analyzing the variation of the peak position of the received signal in the HR-IPFrFT domain, the channel parameters are accurately extracted. Simulation and experiments show that this method exhibits superior parameter identification and estimation accuracy under low signal-to-noise ratio and severe fading conditions © 2025 COSPAR

关键词： Chirp modulation

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Preamble Design for Joint Frame Synchronization, Frequency Offset Estimation, and Channel Estimation in Upstream Burst-Mode Detection of Coherent PON

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Journal of Lightwave Technology 2025年第9期43卷 4127-4138页

作者： Sun, Yongxin Jiang, Hexun Xu, Yicheng Fu, Mengfan Zhu, Yixiao Yi, Lilin Hu, Weisheng Zhuge, Qunbi Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai200240 China

Coherent optics has shown significant potential as a viable solution for achieving 100 Gb/s and higher speeds in single-wavelength passive optical networks (PON). However, upstream coherent burst-mode detection is a major challenge in deploying coherent optics in access networks. To accelerate digital signal processing (DSP) convergence with minimal preamble length, we propose a novel burst-mode preamble design based on a constant amplitude zero auto-correlation (CAZAC) sequence. This design facilitates comprehensive frequency-domain estimation of various impairments, including state of polarization, chromatic dispersion and differential group delay, providing overall system response information for the equalization pre-convergence. Additionally, this preamble utilizes the same training unit to jointly achieve three key DSP functions: frame synchronization, frequency offset estimation, and channel estimation. This integration contributes to a significant reduction in the preamble length. The feasibility of the proposed preamble with a length of 400 symbols and corresponding DSP was experimentally verified in a 15 Gbaud coherent system using dual-polarization 16 quadrature amplitude modulation. The experimental results based on this scheme showed a superior performance of the convergence acceleration. © 1983-2012 IEEE.

关键词： Frequency domain analysis

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Reconfigurable Fiber-Optic Time Transfer Network Architecture Based on SD-TTU

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IEEE Internet of Things Journal 2025年第11期12卷 15736-15747页

作者： Xie, Kunfeng Yang, Yansong Wang, Long Hu, Liang Chen, Jianping Wu, Guiling Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai200240 China

Network architectural is indispensable for a wide-area and robust fiber-optic time transfer network, however, there is currently a deficiency in effective scheme. This paper proposed a reconfigurable fiber-optic time transfer network architecture based on Software-Defined time transfer units, enhancing the network's capability for flexible resource allocation, automatic protection and restoration. The architecture consists of three layers: (1) Time Transfer Layer for time signal transmission and clock difference cancellation;(2) Monitor & Control Layer for monitoring network states, fault detection, and dynamic reconfiguration of the Software-Defined time transfer units;(3) Service & Configuration Layer for customizable service construction and proactive network reconfiguration. A polymorphic Software-Defined time transfer unit is further designed, which can operate as a master station, intermediate station, and slave station using the same hardware. The proposed architecture and the designed Software-Defined time transfer unit are experimentally demonstrated over chained and ring networks, respectively. Network expansion, contraction, topology reconfiguration, failure and fault recovery are validated. The changes of measured mean clock differences are below 43 ps across different scenarios, verifying the robustness and flexibility of the proposed architecture. © 2014 IEEE.

关键词： Clocks

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RGB-D Rail Surface Defect Inspection Driven by Conditional Diffusion Architecture and Frequency Knowledge

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IEEE Sensors Journal 2025年第10期25卷 18334-18343页

作者： He, Zhihao Li, Gongyang Liu, Zhi Shanghai University School of Communication and Information Engineering Shanghai200444 China Anhui Province Key Laboratory of Machine Vision Detection and Perception Wuhu241000 China Wenzhou Institute of Shanghai University Wenzhou325000 China Shanghai University Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai200444 China

RGB-D Rail Surface Defect Inspection (RSDI) is a critical measure for ensuring transportation safety. It improves inspection accuracy by using depth maps, but the issue of poor-quality depth maps in rail defect datasets is often overlooked. Additionally, the similarity between the foreground and background has always been a persistent challenge in RGB-D RSDI. In this article, we propose a novel network, termed DiffRSDI to overcome these challenges in RGB-D RSDI, which treats RGB-D RSDI as a mask generation task using a conditional diffusion architecture. Specifically, DiffRSDI consists of two key components: Cross-modal Cyclic Enhancement (CCE) module and Frequency-aware Alternate Fusion (FAF) module. CCE module is based on the cyclic enhancement approach, and aims to eliminate interference from poor-quality depth maps and aggregate cross-modal features. FAF module overcomes the similarity between the foreground and background in the frequency-domain, and achieves cross-scale fusion in the fused features. Comprehensive experiments conducted on the NEU RSDDS-AUG dataset confirm that our method achieves superior performance in comparison to 14 related methods. The DiffRSDI code and results are available at https://***/zeroyi37/DiffRSDI. © 2001-2012 IEEE.

关键词： Railroad accidents

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Spatial Super-Channel Provisioning in Fiber Space Division Multiplexing (FSDM) Optical Networks

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Journal of Lightwave Technology 2025年第10期43卷 4591-4606页

作者： Han, Shudan Li, Yongcheng Chang, Zeshan Li, Liangchuan Chang, Tianhai Shen, Gangxiang Soochow University Jiangsu New Optical Fiber Technology and Communication Network Engineering Research Center Suzhou Key Laboratory of Advanced Optical Communication Network Technology School of Electronic and Information Engineering Suzhou215006 China Huawei Technology Shenzhen518129 China

Space Division Multiplexing (SDM) and Spatial Super-Channel (Spa SCh) technology provide scalable solutions to meet the growing capacity demands of optical networks. This study focuses on multi-fiber optical networks integrated with innovative Spa SChs, enabling the creation of various Spa SCh granularities by spatially combining the same spectrum across multiple fibers, a transmission method referred to as Fiber-SDM (FSDM). To assess the performance of the FSDM-based network, we develop an analytical model to predict the blocking probability (BP) of Spa SChs with different granularities. Additionally, we propose an efficient adaptive Routing, Fiber, and Spectrum Assignment (RFSA) algorithm, based on the concepts of Spatial Spectrum Window (SSW) and the SSW plane (SSWP). Simulations are conducted to evaluate lightpath BP, considering the trade-off between system cost and power consumption. The results demonstrate the accuracy of the analytical model in predicting lightpath BP in the FSDM network. Furthermore, the Adaptive SSW Plane (A-SSWP) algorithm outperforms the benchmark RFSA algorithms, achieving the best performance under an optimal Spa SCh configuration. © 1983-2012 IEEE.

关键词： Blocking probability

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Advancing Object Discovery: Unveiling the Power of YOLO in Computer Vision Applications 6th

Advancing Object Discovery: Unveiling the Power of YOLO in C...

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6th International Conference on Intelligent communication, Control and Devices, ICICCD 2024

作者： Vijayalakshmi, A. Ebenezer Abishek, B. Arul Stephen, C. Mohith, K. Sri Niranjan Raja, C.A. Department of Electronics and Communication Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Department of Electronics and Communication Engineering KCG College of Technology Chennai India

ISBN: (纸本)9789819783281

The practical implementations and technological advances of the YOLO method in computer vision for object detection are examined in this article. Santosh Divvala and Joseph Redmon’s YOLO artificial intelligence system can accurately and quickly detect objects in videos and images, eliminating the need for network iterations. Instead of using traditional methods, YOLO directly generates bounding boxes and class probabilities for each object, optimising the procedure. After reading this, the process is clearer. This study examines YOLO’s effectiveness in various situations. This technology has many applications in industrial automation, AR/VR, autonomous vehicles, healthcare, and retail. This article examines YOLO model training and data preparation. COCO datasets are used in this study. The architectural components of YOLO versions 7 and 8 are also examined. The findings show that YOLO v8 is highly accurate in identifying a wide range of objects in real time. This study shows YOLO’s revolutionary potential as object detection software for BV applications, highlighting its outstanding features. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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