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ADMM-Based MIMO Equalization Algorithm for SDM Transmission With High MDL Tolerance

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第5期43卷 1427-1439页

作者： Kamiya, Norifumi NEC Corp Ltd Adv Network Res Labs Kawasaki Kanagawa 2118666 Japan

In this paper, we propose a novel multiple-input multiple-output (MIMO) equalization algorithm for optical space division multiplexing (SDM) systems impaired by mode-dependent loss (MDL). The proposed algorithm is a least mean square (LMS)-like algorithm derived on the basis of the alternating direction method of multipliers (ADMM) framework and consists of an iterative filtering process and filter tap update process. The filtering process is implemented in the frequency domain using the overlap-save technique and the filter update process is a gradient descent-based algorithm which tries to minimize the mean squared error of the equalizer output. The computational complexity of the proposed algorithm increases in proportion to the number of iterations and is the same as that of conventional LMS-based MIMO equalization when the number of iterations is one. We evaluate, through simulations, the bit error rate (BER) performance of the proposed algorithm for a coupled multi-core fiber channel model with significant MDL. The simulation results show that increasing the number of iterations improves the BER performance significantly compared to the conventional LMS-based equalization algorithm. The proposed algorithm offers a good tradeoff between BER performance and computational complexity and enhances the MDL tolerance for SDM systems.

关键词： Vectors Symbols Signal processing algorithms Bit error rate Constraint optimization Computational complexity Adaptive equalizers Propagation losses Frequency-domain analysis Space division multiplexing Coupled space division multiplexing transmission mode-dependent loss MIMO equalization ADMM error back-propagation frequency domain equalization overlap-save method

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Estimating the Feasibility of Images Simulation in Unity 3D for Sub-Pixel processing algorithms

Estimating the Feasibility of Images Simulation in Unity 3D ...

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2023 Wave Electronics and its Application in information and Telecommunication systems, WECONF 2023

作者： Sivov, N. Yu. Shmatko, E.V. Poroykov, A. Yu. National Research University MPEI Department of Physics Named after V.A. Fabrikant Moscow Russia

ISBN: (纸本)9798350348293

Computer image simulation is used in the development of optical measurement systems and processing algorithms. It allows the performance of a system or algorithm to be verified and its measurement uncertainty to be assessed. Modern algorithms make it possible to achieve sub-pixel accuracy in digital image processing. An example of such algorithms is the cross-correlation processing in Particle Image Velocimetry. Often, standard graphics engines such as Unity 3D and Unreal Engine are used to simulate the images. The purpose of this work is to evaluate the possibility of using these tools to generate images for further processing by subpixel resolution algorithms. This paper presents the results of a computational experiment to estimate the maximum spatial resolution for simulations in Unity 3D. A qualitative and quantitative analysis of the results confirms the possibility of using the tested graphics engine for the analysis of subpixel resolution algorithms for digital image processing. © 2023 IEEE.

关键词： Engines

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Decentralized Target Localization in Distributed MIMO Radars 16

Decentralized Target Localization in Distributed MIMO Radars

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16th International Conference on Signal processing systems, ICSPS 2024

作者： Qiu, Qinhui Li, Jie Xi, Feng School of Electronic and Optical Engineering Nanjing University of Science and Technology China

ISBN: (纸本)9781510689251

This paper addresses the problem of target estimation in distributed MIMO radars, focusing on the challenge of requiring a robust fusion center to process all the collected data. To overcome this limitation, we propose a solution based on the Alternating Direction Method of Multipliers (ADMM) that eliminates the need for a centralized fusion center. By leveraging the sparsity of target location information within the detection range, the target localization problem is reformulated as a sparse recovery problem, which is then efficiently solved using ADMM. The key innovation of the proposed approach is the transformation of the average value computation, typically required in centralized methods, into a consensus averaging problem, and subsequently into a consensus optimization problem. This transformation allows for fully decentralized processing, where each node only communicates with its neighboring nodes to reach a consensus on the estimation of target location. Simulation results demonstrate that the proposed distributed algorithm achieves performance comparable to that of semi-distributed algorithms while fully exploiting the advantages of decentralization. © 2025 SPIE.

关键词： Consensus algorithm

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Multi-Agent Cooperation-Based Deep Reinforcement Learning for Multisensor Perception Communication System in HSR Tunnel Scenario

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IEEE TRANSACTIONS ON COMMUNICATIONS 2025年第3期73卷 1816-1832页

作者： Liu, Tanda Hu, Fengye Ling, Zhuang Li, Cheng Liang, Ying-Chang Jilin Univ Coll Commun Engn Changchun 130012 Peoples R China Mem Univ Dept Elect & Comp Engn St John NF A1B 3X5 Canada Mem Univ Dept Comp Sci St John NF A1B 3X5 Canada Univ Elect Sci & Technol China Ctr Intelligent Networking & Commun CINC Chengdu 611731 Peoples R China

The rapid development of High-Speed Railway (HSR) puts higher requirements on comprehensive perception and reliable transmission in tunnel scenarios. To realize efficient and reliable perception information transmission of HSR in the tunnel, we propose a multisensor perception communication system, which consists of an Access Point (AP) deployed on each carriage for perception information transmission and self-powered wireless sensors. The AP remote transmits the perception information through the leaky cable deployed in the tunnel. We construct an optimization problem for minimizing the transmission time of the whole system's perception information in the multi-network system and the adjacent area of the carriage. A Multi-Agent Cooperation-based Deep Reinforcement Learning (MA-CDRL) algorithm is proposed to get the optimal scheduling strategy for reducing the transmission time. We construct the CDRL neural network for the algorithm to introduce the states of other APs, resulting in the system making more efficient transmission strategies. In the simulations, the proposed algorithm gets a better performance than the comparison algorithms and is verified in various dynamic HSR scenarios, such as different travel speeds and sensor distributions.

关键词： Sensors Wireless sensor networks Wireless communication Communication systems optical fiber cables information processing Communication cables High-speed railway (HSR) tunnel scenario multisensor perception communication system multi-agent cooperation-based deep reinforcement learning (MA-CDRL)

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Design and Implementation of Automatic optical Surface Defect Inspection System of Large Aperture Lenses 6

Design and Implementation of Automatic Optical Surface Defec...

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Earth Observing Missions and Sensors: Development, Implementation, and Characterization vi 2024

作者： Tapilouw, Abraham Mario Chang, Yi-Wei Wang, Hau-Wei Chang, Kao-Der Chang, Leh-Rong Chen, Liang-Tang Chen, Chia-Ray Mechanical and Mechatronics Systems Research Labs Industrial Technology Research Institute Taiwan Institute of Space System Engineering National Yang Ming Chiao Tung University Taiwan Taiwan

ISBN: (数字)9781510682771

ISBN: (纸本)9781510682764

Surface quality of optical lenses is an important parameter to achieve optimal imaging quality. Surface imperfections such as scratches, pits, or digs which may be caused during manufacturing or handling induce light scattering and degrade the overall performance of the imaging system. For a lightweight lens, the pockets behind the lens will affect the defect judgment due to excellent optical transmittance. This article discusses the measurement flow of automatic optical inspection for large lenses, defect detection algorithm, and the practicality of application of this technique for inspection of large lenses. Surface defect detection module comprises of high dynamic range camera combined with telecentric imaging lens creating an imaging system with resolution of 2.7 μm. Inspection of the whole surface before and after coating is carried out through concentric scanning and different illustrating angles. The images are captured with a 20% overlap between two consecutive images to ensure complete coverage of the whole surface. Image processing algorithms are applied to detect and classify any surface defects on the surface. Detection results consists of exact size, type, and location of the defects are analyzed by the system and summarized into an inspection report. Compared to classical manual inspection this system provides reproducible and objective detection results and allows users to perform revalidation after measurement is finished. © 2025 SPIE.

关键词： Inspection

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Design and research of electric vehicle DC charging pile monitoring system based on LabviEW 3

Design and research of electric vehicle DC charging pile mon...

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3rd International Conference on Electronic information Engineering and Data processing, EIEDP 2024

作者： Yang, Aihua Fang, Tianke Serrano, Elcid A. Chi, Yusen Liu, Fucai Chen, Zhenxiang School of Information Technology Mapua University Manila Philippines School of Information Media Zhangzhou Vocational College of Science and Technology Fujian Zhangzhou China School of Computing and Information Engineering Xiamen University of Technology Fujian Xiamen China Information Technology Teaching and Research Group Fujian Economic School Fujian Fuzhou China Dean's office Zhangzhou Vocational College of Science and Technology Fujian Zhangzhou China

ISBN: (纸本)9781510680531

With the rise in environmental awareness and the promotion of new energy vehicle policies, the electric vehicle (EV) market is rapidly expanding. Direct current (DC) charging stations, as a crucial infrastructure for electric vehicle charging, have made the design and optimization of their monitoring systems especially important. This study aims to design and implement an efficient and reliable DC charging station monitoring system for electric vehicles using the LabviEW platform. The system primarily achieves real-time data collection, signal processing, State of Charge (SoC) estimation, and user interface optimization. Through Geographic information systems (GIS) and big data analysis, this study also assesses the spatial distribution and accessibility of charging stations to promote the rational layout of charging infrastructure. Experimental results show that the developed monitoring system can effectively improve charging efficiency, reduce system response time, and enhance user experience. Moreover, system performance is further improved through optimization using genetic algorithms and simulated annealing algorithms. The research results provide technical support and practical guidance for the development of electric vehicle charging infrastructure, playing a significant role in promoting the sustainable development of the electric vehicle industry. © 2024 SPIE.

关键词： Genetic algorithms

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Artificial Neural Networks for Downbeat Estimation and Varying Tempo Induction in Music Signals 1

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29th International Conference on Neural information processing

作者： Nadi, Sarah Yao, Jianguo Shanghai Jiao Tong Univ Shanghai Peoples R China

ISBN: (数字)9789819916450

ISBN: (纸本)9789819916443;9789819916450

The human capability to feel the musical downbeat and perceive the beats within a unit of time is intuitive and insensitive to the varying tempo of music audio signals. Yet, this mechanism is not straightforward for automated systems and requires further scientific depiction. As automatic music analysis is a crucial step for music structure discovery and music recommendation, downbeat tracking and varying tempo induction have been persistent challenges in the music information retrieval field. This paper introduces an architecture based on bidirectional long-short-term memory artificial recurrent neural networks to distinguish downbeat instants, supported by a dynamic Bayesian network to jointly infer the tempo estimation and correct the estimated downbeat locations according to the optimal solution. The proposed system outperforms existing algorithms with an achieved F1 score of 88.0%.

关键词： Music information Retrieval Audio Signal processing Artificial Neural Networks Dynamic Bayesian Networks

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HDB-Net: hierarchical dual-branch network for retinal layer segmentation in diseased OCT images

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BIOMEDICAL OPTICS EXPRESS 2024年第9期15卷 5359-5383页

作者： Chen, Yu Zhang, XueHe Yang, Jiahui Han, Gang Zhang, He Lai, MingZhu Zhao, Jie Harbin Inst Technol Sch Mechatron Engn Harbin 150001 Heilongjiang Peoples R China Hainan Normal Univ Sch Math & Stat Haikou 571158 Hainan Peoples R China

optical coherence tomography (OCT) retinal layer segmentation is a critical procedure of the modern ophthalmic process, which can be used for diagnosis and treatment of diseases such as diabetic macular edema (DME) and multiple sclerosis (MS). Due to the difficulties of low OCT image quality, highly similar retinal interlayer morphology, and the uncertain presence, shape and size of lesions, the existing algorithms do not perform well. In this work, we design an HDB-Net network for retinal layer segmentation in diseased OCT images, which solves this problem by combining global and detailed features. First, the proposed network uses a Swin transformer and Res50 as a parallel backbone network, combined with the pyramid structure in UperNet, to extract global context and aggregate multi-scale information from images. Secondly, a feature aggregation module (FAM) is designed to extract global context information from the Swin transformer and local feature information from ResNet by introducing mixed attention mechanism. Finally, the boundary awareness and feature enhancement module (BA-FEM) is used to extract the retinal layer boundary information and topological order from the low-resolution features of the shallow layer. Our approach has been validated on two public datasets, and Dice scores were 87.61% and 92.44, respectively, both outperforming other state-of-the-art technologies.

关键词： Image quality information processing Magnetic resonance imaging Neural networks Refractive index Speckle noise

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Design of PMCW Millimeter Wave Radar algorithms on an Embedded DSP 16

Design of PMCW Millimeter Wave Radar Algorithms on an Embedd...

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16th International Conference on Signal processing systems, ICSPS 2024

作者： Zhao, Jinghao Liu, Qiuming Tan, Bin School of Software engineering Jiangxi University of Science and Technology Nanchang China Nanchang Key laboratory of Virtual Digital Factory and Cultural Communications Nanchang China Jiangxi Provincial Key Laboratory of Electronic Data Control and Forensics China School of Electronics and Information Engineering Jinggangshan University Ji’an China

ISBN: (纸本)9781510689251

The rapid advancements in autonomous driving technology necessitate the extensive deployment of automotive radars operating within the 77-81 GHz millimeter-wave band in the forthcoming years. In contrast to earlier Frequency Modulated Continuous Wave (FMCW) radars, Phase-Modulated Continuous Wave (PMCW) radars exhibit notable improvements in processing speed and flexibility, offering superior range and velocity resolution. These enhancements are critical for the precise detection and interpretation of dynamic and complex traffic scenarios. This paper initially presents the simulation and testing of algorithms for range and speed measurement using single-input single-output (SISO) PMCW millimeter-wave radar. Building upon these results, further simulations incorporating multi-input multi-output (MIMO) systems utilizing Hadamard codes are conducted to augment PMCW radar performance. The final phase of this study involves implementing the relevant signal processing algorithms on a custom-developed digital signal processor (DSP) named SWIFT. Experimental findings demonstrate that PMCW radar significantly mitigates multipath effects and clutter, maintaining high performance in complex environments. Furthermore, the algorithms executed on the DSP meet the anticipated performance standards. The proposed methodology not only validates the theoretical framework but also establishes a foundation for future hardware implementation. © 2025 SPIE.

关键词： Automotive radar

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CROMA: Remote Sensing Representations with Contrastive Radar-optical Masked Autoencoders 37

CROMA: Remote Sensing Representations with Contrastive Radar...

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37th Conference on Neural information processing systems (NeurIPS)

作者： Fuller, Anthony Millard, Koreen Green, James R. Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada Carleton Univ Dept Geog & Environm Studies Ottawa ON Canada

ISBN: (纸本)9781713899921

A vital and rapidly growing application, remote sensing offers vast yet sparsely labeled, spatially aligned multimodal data;this makes self-supervised learning algorithms invaluable. We present CROMA: a framework that combines contrastive and reconstruction self-supervised objectives to learn rich unimodal and multimodal representations. Our method separately encodes masked-out multispectral optical and synthetic aperture radar samples-aligned in space and time-and performs cross-modal contrastive learning. Another encoder fuses these sensors, producing joint multimodal encodings that are used to predict the masked patches via a lightweight decoder. We show that these objectives are complementary when leveraged on spatially aligned multimodal data. We also introduce X- and 2D-ALiBi, which spatially biases our cross- and self-attention matrices. These strategies improve representations and allow our models to effectively extrapolate to images up to 17.6x larger at test-time. CROMA outperforms the current SoTA multispectral model, evaluated on: four classification benchmarks-finetuning (*** arrow 1.8%), linear (*** arrow 2.4%) and nonlinear (*** arrow 1.4%) probing, kNN classification (*** arrow 3.5%), and K-means clustering (*** arrow 8.4%);and three segmentation benchmarks (*** arrow 6.4%). CROMA's rich, optionally multimodal representations can be widely leveraged across remote sensing applications.

关键词： Image enhancement

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