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International Conference on 6G communications Networking and Signal Processing, SGCNSP 2023

作者： Hussain, Aadil Saqib, Najam-Us Mushtaq, Asrar Mehraj Shah, Shahid Communication Control and Learning Lab Department of Electronics and Communication Engineering National Institute of Technology Srinagar Srinagar India

ISBN: (纸本)9789819778751

Under the assumption of receiver noise characteristics, the Gaussian noise models are well-studied in the literature. There are several scenarios where the Gaussian Noise assumption is not valid;common examples include electromagnetic interference channels, underwater acoustic channels, powerline communication channels, and NAND flash memory channels. In this paper, we study non-Gaussian noise models, specifically Laplacian noise (a well-known model for impulsive noise). Diverting from the usual assumption of Gaussian inputs, we take a more practical approach and consider finite alphabet constellations as input and compute achievable rates (by computing mutual information (MI)) for various modulation schemes. It is a well-known result that MI computed for finite constellation does not have any closed form;hence, we use the famous LogSumExp inequality to find the upper bound for MI. Simulation results are compared with the obtained bound, and remarkable accuracy is found at high SNR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gaussian noise (electronic)

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SIE: infrared and visible image fusion based on scene information embedding

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Multimedia Tools and Applications 2025年第3期84卷 1463-1488页

作者： Geng, Yingnan Diao, Weixuan Zhao, Yan Electrical and Information Engineering Changchun Institute of Technology Kuanping Road Jilin Changchun130103 China Information and Control Engineering Jilin Institute of Chemical Technology Chengde Street Jilin Jilin132022 China College of Communication Engineering Jilin University Qianjin Street Jilin Changchun130015 China

In this article, we proposed an infrared and visible image fusion method based on scene information embedding, which is to obtain an fused image with high-quality target information such as pedestrian crossing, vehicles, signs and rich background texture information. First, scene information is described, so as to effectively represent highlight salient target for infrared image and texture detail for visible image. Second, we embed this scene information into multi-scale fusion framework to fuse these information and reconstruct the desired fused image. It is worth noting that scene information is constructed by pre-trained convolutional neural network, where not only information extracted by convolutional neural network is fully utilized, but also training complexity is not increased. In datasets LLVIP, MSRS, M3FD,TNO, RoadScene and elctricity1, the superiority of our proposed algorithm SIE over state-of-the-arts is demonstrated by subjective evaluation and objective evaluation including information entropy (EN), standard deviation (SD), spatial frequency (SF), average gradient (AG), sum of the correlations of differences (SCD) and mutual Information (MI) metrics. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image fusion

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A Low-Cost Robotic Assembly Method for Large Planar Workpieces Using Laser Displacement Sensors and Monocular Vision

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第17期49卷 155-172页

作者： Cao, Xiaobing Xu, Yicen Yao, Yonghong Chen, Sheng School of Control Technology Wuxi Institute of Technology Wuxi Jiangsu214121 China School of Intelligent Equipment and Automotive Engineering Wuxi Institute of Commerce Wuxi Jiangsu214153 China School of Communication and Electronic Engineering East China Normal University Shanghai200062 China

To address the challenges associated with large planar workpieces, such as the side window glass of a train, this paper proposes a practical, intelligent robotic assembly method that utilizes laser displacement sensors (LDSs) and monocular vision. The laser point cloud data is fitted to the equation of the plane of the side window optimally, allowing for the calculation of its plane coefficients and unit normal vector (UNV) using the Lagrange multiplier method. The robot's end flange is adjusted to ensure the camera imaging plane is along with the window plane at a specified distance. Monocular vision is employed to capture the pose features of the upper right corner of the window, facilitating a compensation method for precise assembly. The experimental results show that the robot achieved a positioning accuracy of less than 0.5mm and an orientation accuracy within 1 degree, confirming the effectiveness of the proposed method. In the experiment, the maximum displacement deviation in the X direction is about ± 0.4mm, the maximum offset in the Y and Z directions is about ± 0.3mm, the maximum rotation deviation in the X axis is about 0.6 °, and the minimum rotation deviation in the Y axis is about 0.8 °. All deviations meet the requirements of ± 1 ° attitude correction and ± 0.5mm displacement accuracy, and have good reliability. This method solves the practical problem of assembling large planar workpieces with integrated LDS and monocular vision. This technology involves using laser point cloud data to fit the precise plane equation of the window, determining alignment parameters through Lagrange multiplier method, and adjusting the posture of the end flange of the robot. Monocular vision further assists in extracting positional features, achieving precise real-time posture correction and alignment. This system proposes an effective and low-cost automation that reduces manual intervention and alleviates typical problems of remote processing of large workpieces. © 20

关键词： Lagrange multipliers

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DESIGN AND ANALYSIS OF A SLOTTED PLANAR ANTENNA WITH PARASITIC RING PATCH FOR EFFICIENT 5G MICROWAVE APPLICATIONS

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Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2025年第1期84卷 71-82页

作者： Yadav, Swati Varun Yadav, Manish Varun Gupta, Ridhi Yadav, Dinesh Bhati, Kirti Panwar Ali, Tanweer Singh, Vikas Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal Karnataka India Department of Aeronautical and Automobile Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal Karnataka India Department of Electronics and Communication Engineering Manipal University Jaipur Rajasthan Jaipur India School of Electronics Devi Ahilya University M.P Indore India Department of Electronics and Communication Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal Karnataka India

Design and analysis of a slotted planar antenna with a parasitic ring patch for efficient 5G microwave applications is presented. The antenna design aims to strike a balance between complexity and size efficiency. Its front side features a rectangular patch at the center, comprising L-shaped, T-shaped, and inverse T-shaped elements, alongside four parasitic rings on top. The central feed utilizes a 50-ohm strip line connected to a microstrip line. On the back side, the antenna incorporates three parasitic rings on top, four horizontal strips arranged in an increasing order, and a ground plane with a small rectangular slot. To evaluate its performance, the antenna is simulated using CST Microwave Studio on an FR-4 substrate with overall dimensions measuring 13 × 15 × 1.5 mm3. The results demonstrate an impressive impedance bandwidth of 60.8% and a return loss of –28 dB within the frequency range of 3.2–6 GHz, with a central frequency of 4.6 GHz. Throughout its operational range, the radiation patterns remain constant, exhibiting stable polar patterns and efficient performance with a wide gain of 4.81 dBi and an efficiency of 82%;the proposed antenna proves to be suitable for 5G microwave applications. © 2025 by Begell House, Inc.

关键词： Microwave antennas

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Multi-scale network for single image deblurring based on ensemble learning module

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Multimedia Tools and Applications 2025年第11期84卷 9045-9064页

作者： Wu, WenBo Pan, Yun Su, Na Wang, JingTao Wu, ShaoChuan Xu, ZeKun Yu, YouJian Liu, YaPeng State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China School of Computer and Cyberspace Security Communication University of China Beijing100024 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China College of Computer and Control Engineering Northeast Forestry University Harbin150040 China School of Computer and Information Engineering Tianjin Chengjian University Tianjin300384 China School of Computer Science and Technology Anhui University Hefei230601 China

In this paper, we have identified two primary issues with current multi-scale image deblurring methods. On the one hand, the blurring scale is ignored. On the other hand, the context information of images is not fully utilized, and the spatial detail information of images is lost. To better solve the above problems, on top of that, this paper proposes a multi-scale network for single image deblurring. The designed network contains two parts: 1) Ensemble Learning Model: The Weak Learning Model in this module connects multiple weak learners in series to increase network depth. Moreover, through multi-scale feature ensemble module, the output features and intermediate features of different weak learner are integrated, and finally strong learner is used to enhance the features with semantic information at different scales;2) Spatial Feature Enhancement Module: This module can preserve spatial detail information of images and compensate for the disadvantages of losing image spatial details due to continuous downsampling in the Ensemble Learning Model structure. Our proposed deblurring model has been extensively evaluated on several benchmark datasets, and the model achieves superior performance compared to the most advanced deblurring methods. In particular, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values are 33.57 dB and 0.965 on the GoPro dataset, respectively, with PSNR and SSIM improving by 0.49 dB and 0.002 over NAFNet, and 0.65 dB and 0.004 over Restormer. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Learning systems

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Hyperspectral Image Cross Scene Classification Combined Domain Adaptation with XGBoost

Hyperspectral Image Cross Scene Classification Combined Doma...

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2024 International Conference on Measurement, communication, and Virtual Reality, MCVR 2024

作者： Liu, Chengyang Wu, Haibin Li, Jiarong Liu, Xinyu Yan, Siqi Wang, Aili Heilongjiang Province Key Laboratory of Laser Spectroscopy Technology and Application College of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin150080 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9781510691773

To address the issues of domain discrepancies and limited labeled samples in hyperspectral image classification of cross scene, this paper proposes an ensemble learning framework that integrates eXtreme Gradient Boosting (XGBoost) with confidence domain adaptation strategies to improve classification performance. First, the Houston dataset from different scenes is input separately into a deep embedding model. The hyperspectral images are embedded into a low-dimensional space, ensuring that similar spectra are represented more closely in this space, thereby capturing the intrinsic structure and distribution of the hyperspectral image dataset. Subsequently, these samples are mapped into a discriminator model, where domain adaptation techniques are employed to reduce differences in feature distributions across different scenes. Additionally, confidence-based learning is used to identify and remove noisy samples in the Houston dataset, thereby enhancing the alignment of feature distributions among various scenes. Finally, through ensemble learning, a weighted voting strategy is employed to combine multiple base classifiers into a strong classification model. This approach better captures the complex features within the data, thereby reducing the bias of individual classifiers and enhancing the overall generalization ability and robustness of the model. Experimental results on the Houston dataset demonstrate that the proposed method outperforms popular domain adaptation learning models and traditional methods in terms of classification accuracy and robustness, showcasing its potential and advantages in practical applications. This result confirms the effectiveness of combining XGBoost and confidence domain adaptation strategies in handling hyperspectral image classification. © 2025 SPIE.

关键词： Photointerpretation

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UAV-Assisted IRS System in 5 G and Beyond: Improving Reliability and Enhancing the Network Life Span

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IEEE Transactions on Mobile Computing 2025年

作者： Kumar, Pankaj Goel, Nikita Tolani, Manoj Manipal Institute of Technology Department of Information and Communication Technology Manipal576104 India Manipal Institute of Technology Department of Instrumentation and Control Engineering Manipal576104 India

This paper proposes an unmanned aerial vehicle (UAV)-assisted intelligent reflecting surface (IRS) for device-to-device (D2D) communication in infrastructure-less scenarios. The aim of this paper is to enhance the reliability among D2D ground users (GUs) and extend the lifespan of 5 G and beyond 5 G (B5G) wireless communication system. This work may be applicable for packet delivery in bustling urban areas, especially where ground-to-ground (G2G) links are in deep fade. For modeling air-to-ground (A2G) links among GUs to IRS/UAV and IRS/UAV to GUs, we consider a height-dependent Nakagami-m channel model for small-scale fading and height-dependent path-loss exponent for modeling large-scale fading. The lifespan of the network is improved by proposing height-dependent energy harvesting (EH) at UAV. We derive the cumulative distribution function (CDF) of the signal-to-noise ratio (SNR) whenever the signal reaches the receiving node, either via UAV or via IRS. We also develop the expression of spectral efficiency and derive a closed-form expression of an outage probability by taking the combined effect of the signal for the proposed scenario using decode-and-forward (DF) and amplify-and-forward (AF) relaying at the UAV. Additionally, the statistical parameters such as mean, variance, and probability density function (PDF) of total noise are derived, which is useful at the receiver node for estimating the bit error rate (BER). The analytical result is validated with simulation results, and the work is compared with the existing state-of-the-art. © 2002-2012 IEEE.

关键词： Distribution functions

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Chaotic index modulation and subcarrier intra-block-inter-block shuffling for secure CO-OFDM-PON based on a hybrid 4D chaos

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Optics Express 2025年第10期33卷 21217-21235页

作者： Wang, Yun Pan, Xiaolong Zhang, Qi Xin, Xiangjun Gao, Ran Yao, Haipeng Tian, Feng Wang, Fu Li, Zhipei Liu, Xiangyu Tian, Qinghua Wang, Yongjun Yang, Leijing Zhou, Sitong Li, Zuolin Li, Ying Beijing100876 China Beijing Key Laboratory of Space-round Interconnection and Convergence BUPT Beijing100876 China Beijing100081 China School of Information and Communication Engineering BUPT Beijing100876 China Beijing Institute of Control and Electronic Technology Beijing100038 China Beijing Institute of Remote Sensing Equipment Beijing100039 China

In this paper, a four-dimensional (4-D) encryption scheme with chaotic index modulation (IM) and subcarrier intra-block-inter-block shuffling is proposed to enhance the physical layer security of coherent orthogonal frequency division multiplexing passive optical network (CO-OFDM-PON). The scheme utilizes a hybrid 4-D chaotic scheme consisting of 1-D Cubic chaotic mapping and 3-D T-S Fuzzy chaotic system to generate four dynamic scrambling factors to achieve 4-D ultra-high security encryption of index bits, data bits, intra-subcarrier block, and inter-subcarrier block. Firstly, the chaotic many-to-many mapping rule between index bits and subcarrier activation patterns (SAPs) is constructed based on the IM principle to realize the index bit encryption;secondly, the data bit encryption is realized by heterodyning with chaotic bits. Further, the chaotic shuffling algorithm is proposed to disrupt and rearrange the symbols within and between subcarrier blocks to realize OFDM-IM symbol secondary encryption. To validate the feasibility of the proposed encryption scheme, simulations in a CO-OFDM-PON system evaluate the performance of a 63.76 Gb/s encrypted 16 quadrature amplitude modulation (QAM) OFDM-IM signal over transmission distances of 25 km and 80 km through standard single-mode fiber (SSMF). The results demonstrate that legitimate users can successfully recover the encrypted signals, while eavesdroppers consistently experience a bit error rate (BER) close to 0.5, making it nearly impossible to extract useful information. The initial value sensitive tolerance precision of the key (x0, y0, z0, w0, a1, b1, c1, a2, b2, c2, a3, b3, c3, µ) is (10−15, 10−15, 10−14, 10−16, 10−15, 10−14, 10−15, 10−14, 10−16, 10−16, 10−15, 10−15, 10−15, 10−15), and the key space is as high as 10210. The proposed scheme achieves the scrambling degree (SD) value of 100% under a different number of blocks, which demonstrates its exceptional security and suitability for secure communication appli

关键词： Quadrature amplitude modulation

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Impact of diameter on D-shaped POF sensors for salt detection

Impact of diameter on D-shaped POF sensors for salt detectio...

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International Laser Technology and Optics Symposium 2024, iLATOS2024

作者： Khan, Abdul Ali Thirunavakkarasu, Punithavathi M. bte Saidin, Norazlina Noor, Ahmad Shukri Muhammad Waqas, Nawaf Communication Technology Section Universiti Kuala Lumpur British Malaysian Institute Kuala lumpur53100 Malaysia Faculty of I.C.T BUITEMS Quetta87100 Pakistan Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur53100 Malaysia Department of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia Selangor Malaysia Department of Instrumentation and Control Engineering Universiti Kuala Lumpur British Malaysian Institute Bt. 8 Jalan Sungai Pusu Selangor Gombak53100 Malaysia

This study investigates the relationship between the diameter of a D-shaped plastic optical fiber (POF) sensor and its optical response as a function of varying salt concentrations. A simple and efficient dry etching polishing technique was employed to create D-shaped POF sensors with a range of diameters. All the fabricated sensors were carefully developed to maintain a consistent length of 20 cm with a sensing region of 1cm. To evaluate the optical intensity response, each sensor, with its respective diameter, was examined with the salt concentration ranging from (0 to 5%) examination utilizing a spectrometer. The sensor response was characterized by quantifying the variations observed in the intensity of the optical signal propagating through the sensing region. The sensors having a diameter of 500 μm, 700 μm, and 900 μm had a sensitivity of 149 A.U/%salt, 66 A.U/%salt, and 11.2 A.U/%salt respectively. The sensitivity of the 500 μm diameter sensor increased 13 times approximately as compared to the sensor having diameter of 900 μm. © 2025 institute of Physics Publishing. All rights reserved.

关键词： Dry etching

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OS-SEI: Open-Set Specific Emitter Identification Based on Outlier Exposure and Label Smoothing

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IEEE Internet of Things Journal 2025年

作者： Wang, Juzhen Wang, Hanhong Wang, Wei Zha, Haoran Hangzhou Dianzi University School of Communication Engineering Hangzhou310018 China Binjiang Institute of Artificial Intelligence of Zhejiang University of Technology Hangzhou310052 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China Harbin Engineering University College of Information and Communication Engineering Harbin150009 China

Specific Emitter Identification (SEI), based on the inevitable hardware imperfections of emitters, plays a crucial role in physical layer security, independent of upper-layer cryptographic methods. In recent years, SEI combined with deep learning has demonstrated exceptional performance and considerable potential. However, most SEI methods are designed for closed, independent identically distributed environments, which contrasts with real-world open scenarios. This discrepancy leads to significant security vulnerabilities when deploying models in practical applications. To address this challenge, we propose a novel Open-Set SEI (OS-SEI) framework, Outlier Exposure with Label Smoothing (OELS), which utilizes partial exposure to auxiliary anomalous data during the training phase and introduces specific loss functions to mitigate the open-set risk. By constructing smooth decision boundaries through label smoothing and applying thresholds to class confidence, our SEI framework demonstrates robust open-set authentication capabilities. Extensive experiments conducted on ADS-B and WiFi datasets show that the OELS method achieves outstanding open-set recognition performance, with F1 scores of 83.77% and 93.14% at an openness level of 0.10557. Furthermore, ablation experiments confirm the effectiveness and potential of our framework’s components. By increasing the diversity of auxiliary unknown data, we further improve performance in OS-SEI tasks. © 2014 IEEE.

关键词： Hardware security

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