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Secure Beamforming Design for IRS-ISAC Systems with a Hardware-Efficient Hybrid Beamforming Architecture

IEEE Transactions on Vehicular technology 2025年

作者： Xiong, Weijie Zhao, Zhenglan Lin, Jingran Xiao, Zhiling Li, Qiang University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100083 China Tianfu Jiangxi Laboratory Sichuan Chengdu641419 China

In this paper, we employ a hardware-efficient hybrid beamforming (HB) architecture to achieve balanced performance in an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system. We consider a scenario where a multi-antenna, dual-function base station (BS) performs secure beamforming for a multi-antenna legitimate receiver while simultaneously detecting potential targets. Our objective is to maximize the communication secrecy gap by jointly optimizing the analog and digital beamformers, IRS reflection coefficients, and radar scaling factor, subject to constraints on beampattern similarity, total transmit power budget, and the constant modulus of both the analog beamformer and IRS reflection coefficients. This secrecy gap maximization problem is generally non-convex. To address this, we incorporate the exterior penalty method by adding the radar constraint as a penalty term in the objective function. We then propose an efficient approach based on the penalty dual decomposition (PDD) framework to solve the reformulated problem, featuring closed-form solutions at each step and guaranteeing convergence to a stationary point. Simulation results validate the effectiveness of the proposed algorithm and demonstrate the superiority of the IRS-ISAC system with HB architecture in balancing performance and hardware costs. © 1967-2012 IEEE.

关键词： Convex optimization

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Load Balancing Routing Algorithm for LEO Satellite Networks Based on Ant Colony Optimization

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Internet technology Letters 2025年第3期8卷

作者： Zhi, Ruxin Wang, Jiahui Xu, Zhan Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

To address the problem of the unbalanced load and optimize the traffic distribution of large-scale low earth orbit (LEO) satellite networks, this paper proposes a load-balancing routing algorithm for LEO satellite networks based on ant colony optimization. The algorithm establishes the global optimal initial path through the improved ant colony algorithm to bypass the network bottleneck, makes local adjustments to cope with burst traffic changes to avoid congestion, and optimizes the "inferior" paths through regular rerouting to improve the overall network performance. The results show that the algorithm performs well in terms of packet loss rate, throughput, and load balancing, which can effectively alleviate the link utilization imbalance problem and provide a more stable and efficient service for the satellite network. Among them, the packet loss rate is reduced by 7.8%, and the load distribution index is improved by 30%. © 2025 The Author(s). Internet technology Letters published by John Wiley & Sons Ltd.

关键词： Ant colony optimization

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A Cross-Task Transfer SAR Target Recognition Method Based on AMFFNet and IACGAN

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Wan, Xunyang Du, Xiaolin Cui, Guolong Chen, Xiaolong Zheng, Jibin Yantai University School of Computer and Control Engineering Yantai264005 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Naval Aviation University Yantai264001 China Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China

Convolutional neural networks (CNN) have shown excellent capability in synthetic aperture radar (SAR) target recognition. However, obtaining sufficient training samples for improving network recognition is difficult due to the deficiency of labeled SAR image data. To tackle the problem, a cross-task transfer method for SAR target recognition is proposed in this paper, which is based on a designed attention multi-scale feature fusion network (AMFFNet) and an improved auxiliary classifier generative adversarial network (IACGAN). In this method, firstly, a data augmentation method based on you only cut twice (YOCT) is devised for expanding the training samples. Secondly, the partial weight parameters of AMFFNet are initialized by the pre-trained IACGAN discriminator. Finally, AMFFNet is fine-tuned using the training samples. Additionally, on the network structure of AMFFNet, multi-scale features are extracted by adopting a multi-scale depth separable convolution module, which allows the model to acquire more informative features. Attention mechanisms are employed in this network to enhance its ability to capture important features while reducing the effects of noise. A multi-level feature fusion structure is used to further raise the representational capability of the model. Experimental results on multiple open-source real SAR datasets show that the proposed method can achieve better recognition performance under different percentages of training data, and the effectiveness and superiority of the method are confirmed by its robustness to noise. © 1965-2011 IEEE.

关键词： Convolutional neural networks

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Breather dynamics in an optomechanical array with staggered coupling

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Physical Review A 2025年第3期111卷 033502-033502页

作者： Yuan Zhao Yiheng Hou Yu Wang Zhuo Fan Wei Peng Qin Zhou Siliu Xu Shihua Chen Key Laboratory of Optoelectronic Sensing and Intelligent Control Hubei University of Science and Technology Xianning 437100 China School of Biomedical Engineering and Imaging Xianning Medical College Hubei University of Science and Technology Xianning 437100 China School of Electronic and Information Engineering Hubei University of Science and Technology Xianning 437100 China Research Center of Nonlinear Science School of Mathematics and Physical Sciences Wuhan Textile University Wuhan 430200 China School of Physics and Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing 211189 China

We present an approach toward generating highly controllable breathers, using an array of staggered optomechanical cavities that feature alternating coupling strengths. Four different types of breather states as well as stable two-soliton states are demonstrated to form in such an optomechanical array, thanks to the interplay between the photon-hopping induced tunneling effect and the photon-phonon coupling in the optomechanical cell. It is seen that both their photonic and phononic wave components manifest quasi-periodic oscillatory patterns and coherent localization. We unveil that such breather dynamics can be well controlled by adjusting the coupling strength, the cavity field decay, and the number of array cells. As a result, we observe an unusual odd-even lattice effect in that stable breathers are only available when the cell number is even. We anticipate that these findings from the staggered optomechanical configuration may expand the realm of cavity optomechanics, yielding promising applications such as on-chip manipulation of light propagation.

关键词： Solitons

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Joint Vehicle Pairing, Spectrum Assignment and Power control for Sum-Rate Maximization in NOMA-Based V2X Underlaid Cellular Networks

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IEEE Internet of Things Journal 2025年

作者： Xue, Tong Zhang, Haixia Ding, Hui Yuan, Dongfeng Shandong University of Science and Technology College of Electronic and Information Engineering Shandong Qingdao266590 China Shandong Key Laboratory of Intelligent Communication and Sensing-Computing Integration Shandong Jinan250061 China Shandong University School of Control Science and Engineering Shandong Jinan250061 China

Vehicle-to-everything (V2X) underlaid cellular networks in underlaid mode suffers catastrophic co-channel interference caused by spectrum sharing, results in a reduced system sum-rate. To cope with this, this work studies a social-mobility-aware non-orthogonal multiple access (NOMA)-enabled V2X underlaid cellular network to mitigate the co-channel interference and improve the sum-rate. By jointly optimizing vehicle pairing and resources, a sum-rate maximization problem is formulated under the diverse quality of service requirements of both cellular and vehicular users. The formulated problem is proved to be a non-deterministic polynomial-time (NP)-hard problem, and is difficult to solve. As an alternative, we propose a NOMA-based joint vehicle pairing, spectrum assignment and power control algorithm (NOMA-JVP-SA-PCA), with which the original problem is decomposed into two disjoint subproblems, i. e., 1) joint vehicle pairing and spectrum assignment subproblem, and 2) power control subproblem. Dealing the first subproblem, we propose a heuristic social-mobility-aware vehicle pairing algorithm (HSMA-VPA) and a revised Kuhn-munkres-based spectrum assignment algorithm (KM-SAA) to acquire the vehicle pairing and spectrum assignment solutions. Then, solving the second subproblem, a closed-form power solution is obtained utilizing a three-dimensional geometric power control approach (3D-PCA). Finally, we solve the original problem through an iterative method. Simulation results show that the proposed NOMA-JVP-SA-PCA effectively enhances the sum-rate and outperforms the baseline algorithms around 24%-53% within a specific range. © 2014 IEEE.

关键词： Polynomial approximation

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Large Language Model as a Catalyst: A Paradigm Shift in Base Station Siting Optimization

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IEEE Transactions on Cognitive communications and Networking 2025年

作者： Wang, Yanhu Afzal, Muhammad Muzammil Li, Zhengyang Zhou, Jie Feng, Chenyuan Guo, Shuaishuai Quek, Tony Q. S. Shandong University School of Control Science and Engineering Jinan250062 China EURECOM Department of Communication Systems Sophia Antipolis06410 France Singapore University of Technology and Design Singapore487372 Singapore Kyung Hee University Department of Electronic Engineering Yongin17104 Korea Republic of

Traditional base station siting (BSS) methods rely heavily on drive testing and user feedback, which are laborious and require extensive expertise in communication, networking, and optimization. As large language models (LLMs) and their associated technologies advance, particularly in the realms of prompt engineering and agent engineering, network optimization will witness a revolutionary approach. This approach entails the strategic use of well-crafted prompts to infuse human experience and knowledge into these sophisticated LLMs, and the deployment of autonomous agents as a communication bridge to seamlessly connect the machine language based LLMs with human users using natural language. Furthermore, our proposed framework incorporates retrieval-augmented generation (RAG) to enhance the system's ability to acquire domain-specific knowledge and generate solutions, thereby enabling the customization and optimization of the BSS process. This integration represents the future paradigm of artificial intelligence (AI) as a service and AI for more ease. This research first develops a novel LLM-empowered BSS optimization framework, and heuristically proposes three different potential implementations: the strategies based on Prompt-optimized LLM (PoL), LLM-empowered autonomous BSS agent (LaBa), and Cooperative multiple LLM-based autonomous BSS agents (CLaBa). Through evaluation on real-world data, the experiments demonstrate that prompt-assisted LLMs and LLM-based agents can generate more efficient and reliable network deployments, noticeably enhancing the efficiency of BSS optimization and reducing trivial manual participation. © 2015 IEEE.

关键词： Systems analysis

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Experimental demonstration of 8190-km long-haul semiconductor-laser chaos synchronization induced by digital optical communication signal

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光：科学与应用（英文版） 2025年第2期14卷 333-343页

作者： Anbang Wang Junli Wang Lin Jiang Longsheng Wang Yuncai Wang Lianshan Yan Yuwen Qin Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education of ChinaGuangdong University of TechnologyGuangzhou 510006China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceTaiyuan 030024China Institute of Advanced Photonics Technology School of Information EngineeringGuangdong University of TechnologyGuangzhou 510006China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceTaiyuan 030024China College of Physics and Optoelectronics Taiyuan University of TechnologyTaiyuan 030024China Center for Information Photonics and Communications Southwest Jiaotong UniversityChengdu 610031China Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education of ChinaGuangdong University of TechnologyGuangzhou 510006China Institute of Advanced Photonics Technology School of Information EngineeringGuangdong University of TechnologyGuangzhou 510006China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangdong University of TechnologyGuangzhou 510006China

Common-signal-induced synchronization of semiconductor lasers have promising applications in physical-layer secure transmission with high speed and compatibility with the current fiber ***,we propose an ultra-long-distance laser synchronization scheme by utilizing random digital optical communication signal as the common drive *** utilizing the long-haul optical coherent communication techniques,high-fidelity fiber transmission of the digital drive can be achieved and thus ultra-long-distance synchronization is *** were implemented with distributed feedback lasers injected by a random-digital phase-modulated drive *** show that high-quality synchronization can be achieved as the drive signal rate is larger than the laser relaxation frequency and the transmission bit error ratio is below a critical *** synchronization over 8191-km fiber transmission was experimentally *** to traditional common-signal-induced synchronization using analog drive signal such as chaos,the distance is increased by 8 times,and complicated hardware devices for channel impairment compensation are no longer *** addition,the proposed method does not sacrifice communication capacity like traditional methods which need a channel to transmit analog drive *** is therefore believed that this common-digital-signal induced laser synchronization paves a way for secure backbone and submarine transmission.

关键词： communication semiconductor synchronization signal digital chaos laser demonstration experimental induced

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Polarized Modulation for RIS-Aided Vehicular communication Networks

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IEEE Internet of Things Journal 2025年

作者： Shang, Pingping Xie, Longhui Li, Jun Feng, Li Hai, Han Xu, Binbin Li, Jie Yu, Ling Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China Hubei University of Technology Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430068 China Guangzhou University Research Center of Intelligent Communication Engineering School of Electronics and Communication Engineering Guangzhou510006 China Key Laboratory of On-Chip Communication and Sensor Chip of Guangdong Higher Education Institutes Guangzhou510006 China Donghua University School of Information Science and Technology Shanghai201620 China Maritime Communication Research Institute Wuhan430068 China Guangdong Provincial Hospital of Chinese Medicine Guangzhou510120 China State Key Laboratory of Traditional Chinese Medicine Syndrome Guangzhou510120 China

The reconfigurable intelligent surface (RIS) stands as an emergent technique poised to revolutionize future vehicular communication. In order to facilitate the application of RIS in vehicular communication, this paper proposes two effective RIS-aided schemes tailored for polarization modulation (PM) aiming to achieve remarkable spectral efficiency. Specifically, Scheme I proposes a novel index modulation (IM) aided PM-RIS framework that innovatively encodes information across three distinct dimensions, the indices of dual-polarized antennas (DP-AEs), PM symbols and the reflecting surface indices of the RIS. Scheme II employs a deep neural network method to analyze the channel state information (CSI) for transmit antenna selection, that enhances the reliability and interference immunity in dynamic conditions while reducing computational complexity. Furthermore, a stepwise estimation (SE) method is introduced at the detection stage, which significantly reduces the complexity associated with information decoding. The simulation results highlight the superiority of the proposed system. Compared with traditional PM systems, it demonstrates enhanced performance in terms of spectral efficiency, channel stability, and bit error rate (BER). © 2014 IEEE.

关键词： Signal modulation

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Unsupervised Feature Enrichment and Fidelity Preservation Learning Framework for Skeleton-based Action Recognition

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IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Li, Chuankun Li, Shuai Gao, Yanbo Gao, Xingyu Chen, Ping Li, Jian Li, Wanqing North University of China State Key Laboratory of Dynamic Testing Technology School of Information and Communication Engineering Taiyuan030051 China Shandong University School of Control Science and Engineering School of Software Jinan250100 China Chinese Academy of Sciences Institute of Microelectronics Beijing100029 China University of Wollongong Advanced Multimedia Research Lab WollongongNSW2522 Australia

Unsupervised skeleton-based action recognition has achieved remarkable progress recently. Existing unsupervised learning methods suffer from severe overfitting problem, and thus small networks are used, significantly reducing the representation capability. To address this problem, the overfitting mechanism behind the unsupervised learning for skeleton-based action recognition is first investigated. It is observed that skeleton is already a relatively high-level and low-dimension feature, but not in the same manifold as the features for action recognition. Simply applying the existing unsupervised learning method tends to produce features that discriminate the different samples rather than action classes, resulting in the overfitting problem. To address this problem, this paper proposes an Unsupervised spatial-temporal Feature Enrichment and Fidelity Preservation (U-FEFP) learning framework to generate rich distributed features that contain all the information of a skeleton sample. A spatial-temporal feature transformation subnetwork is developed using channel-wise topology refinement graph convolutional block and graph convolutional gated recurrent unit block as the basic feature extraction network. The unsupervised Bootstrap Your Own Latent-based learning is utilized to generate rich distributed features, and the unsupervised pretext task-based learning is employed to preserve the information contained in the skeleton. The two unsupervised learning ways are collaborated as U-FEFP to produce robust and discriminative representations. Experimental results on four widely used benchmarks, namely NTU-RGB+D-60, PKU-MMD, NTU-RGB+D-120 and UAV-Human dataset, demonstrate that the proposed U-FEFP obtains the best result compared with the state-of-the-art unsupervised learning methods. © 1991-2012 IEEE.

关键词： Convolution

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A Novel Consecutive Artificial Noise Secrecy Enhancing Scheme for RIS Aided MIMO System With Imperfect CSI

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IEEE Transactions on Vehicular technology 2025年

作者： Shang, Pingping Tao, Zhuofan Xie, Zhonghui Huang, Min Sui, He Li, Jun Hai, Han Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China Hubei University of Technology Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430068 China Civil Aviation University of China College of Aeronautical Engineering Tianjin300399 China Guangzhou University School of Electronics and Communication Engineering Guangzhou510006 China Donghua University College of Information Science and Technology Shanghai201620 China

Reconfigurable intelligent surface (RIS) is a technology with great promise, which is widely used in wireless networks to improve the coverage and enhance the performance. However, security concerns pose a major challenge for wireless networks, especially given inevitable errors in channel estimation. This paper proposes a high spectrum efficiency security scheme using generalized spatial modulation (GSM) and space-time block coding (STBC) for scenarios with imperfect channel state information (CSI). In this scheme, GSM uses RIS block indices as unique identifiers, ideal for secure scenarios. It operates by activating different RIS blocks over two time slots to reflect unmodulated carrier signals, while STBC is designed based on the phase shifts of the RIS. To ensure secure communication, a low-complexity continuous artificial noise (CAN) is transmitted with STBC signals to interfere with eavesdroppers and prevent them from decoding the signals. The ergodic secrecy rate is deduced, and the bit error rate (BER) is validated through experiments. The simulation results indicate that the proposed solution can remarkably improves the security performance of the RIS-assisted wireless communication systems. © 1967-2012 IEEE.

关键词： Space-time block coding (STBC)

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