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Secure communication of Active RIS Assisted NOMA Networks

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arXiv 2024年

作者： Li, Xuehua Pei, Yingjie Yue, Xinwei Liu, Yuanwei Ding, Zhiguo The Key Laboratory of Information and Communication Systems Ministry of Information Industry The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates

As a revolutionary technology, reconfigurable intelligent surface (RIS) has been deemed as an indispensable part of the 6th generation communications due to its inherent ability to regulate the wireless channels. However, passive RIS (PRIS) still suffers from some pressing issues, one of which is that the fading of the entire reflection link is proportional to the product of the distances from the base station to the PRIS and from the PRIS to the users, i.e., the productive attenuation. To tackle this problem, active RIS (ARIS) has been proposed to reconfigure the wireless propagation condition and alleviate the productive attenuation. In this paper, we investigate the physical layer security of the ARIS assisted non-orthogonal multiple access (NOMA) networks with the attendance of external and internal eavesdroppers. To be specific, the closed-form expressions of secrecy outage probability (SOP) and secrecy system throughput are derived by invoking both imperfect successive interference cancellation (ipSIC) and perfect SIC. The secrecy diversity orders of legitimate users are obtained at high signal-to-noise ratios. Numerical results are presented to verify the accuracy of the theoretical expressions and indicate that: i) The SOP of ARIS assisted NOMA networks exceeds that of PRIS-NOMA, ARIS/PRIS-assisted orthogonal multiple access (OMA);ii) Due to the balance between the thermal noise and residual interference, introducing excess reconfigurable elements at ARIS is not helpful to reduce the SOP;and iii) The secrecy throughput performance of ARIS-NOMA networks outperforms that of PRIS-NOMA and ARIS/PRIS-OMA networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Signal to noise ratio

Vector Angular Spectrum Model for light travelling in scattering media

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arXiv 2024年

作者： Liu, Kaige Zhang, Hengkang Liu, Zeqi Zhang, Bin Fu, Xing Yuan, Qiang Liu, Qiang Ministry of Education Beijing100084 China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision Instrument Tsinghua University Beijing100084 China Research Center of Laser Fusion China Academy of Engineering Physics Mianyang621900 China Beijing Institute of Control Engineering Beijing100190 China Beijing Institute of Electronic System Engineering Beijing100854 China

Strongly scattering media disrupt both the wavefront distribution and the polarization state of the incident light field. controlling and effectively utilizing depolarization effects are crucial for optical applications in highly scattering environments, such as imaging through dense fog. However, current simulation models have difficulty simulating the evolution of vector light fields within scattering media, posing challenges for studying vector light fields in strongly scattering environments. Here, we propose the Vector Angular Spectrum (VAS) model for simulating the propagation of vector light fields within scattering media. By introducing the angular spectrum distribution of vector light scattering and polarization conversion mechanisms, this model can simulate the depolarization effects of vector light propagating through strongly scattering media. The VAS model has also been used to investigate the focusing of vector scattered light through scattering media. Furthermore, the simulation results of the model have been validated through experiments. The proposed VAS model is expected to play a role in the theoretical research of vector scattered light and optical applications in strongly scattering environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Vectors

Integrated communication and Learned Recognizer with Customized RIS Phases and Sensing Durations

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arXiv 2025年

作者： Huang, Yixuan Yang, Jie Wen, Chao-Kai Jin, Shi National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan

Future wireless communication networks are expected to be smarter and more aware of their surroundings, enabling a wide range of context-aware applications. Reconfigurable intelligent surfaces (RISs) are set to play a critical role in supporting various sensing tasks, such as target recognition. However, current methods typically use RIS configurations optimized once and applied over fixed sensing durations, limiting their ability to adapt to different targets and reducing sensing accuracy. To overcome these limitations, this study proposes an advanced wireless communication system that multiplexes downlink signals for environmental sensing and introduces an intelligent recognizer powered by deep learning techniques. Specifically, we design a novel neural network based on the long short-term memory architecture and the physical channel model. This network iteratively captures and fuses information from previous measurements, adaptively customizing RIS phases to gather the most relevant information for the recognition task at subsequent moments. These configurations are dynamically adjusted according to scene, task, target, and quantization priors. Furthermore, the recognizer includes a decision-making module that dynamically allocates different sensing durations, determining whether to continue or terminate the sensing process based on the collected measurements. This approach maximizes resource utilization efficiency. Simulation results demonstrate that the proposed method significantly outperforms state-of-the-art techniques while minimizing the impact on communication performance, even when sensing and communication occur simultaneously. Part of the source code for this paper can be accessed at https://***/kiwi1944/CRISense. Copyright © 2025, The Authors. All rights reserved.

关键词： Long short-term memory

A Practical Quantum Network Coding Protocol Based on Non-Maximally Entangled State

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Computers, Materials & Continua 2021年第8期68卷 2651-2663页

作者： Zhen-Zhen Li Zi-Chen Li Xiu-Bo Chen Zhiguo Qu Xiaojun Wang Haizhu Pan School of Information Engineering Beijing Institute of Graphic CommunicationBeijing102600China Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and TechnologyNanjing210044China School of Electronic Engineering Dublin City UniversityDublin9Ireland College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China

In many earlier works,perfect quantum state transmission over the butterfly network can be achieved via quantum network coding protocols with the assist of maximally entangled ***,in actual quantum networks,a maximally entangled state as auxiliary resource is hard to be obtained or easily turned into a non-maximally entangled state subject to all kinds of environmental ***,we propose a more practical quantum network coding scheme with the assist of non-maximally entangled *** this paper,a practical quantum network coding protocol over grail network is proposed,in which the non-maximally entangled resource is assisted and even the desired quantum state can be perfectly *** achievable rate region,security and practicability of the proposed protocol are discussed and *** practical quantum network coding protocol proposed over the grail network can be regarded as a useful attempt to help move the theory of quantum network coding towards practicability.

关键词： Quantum network coding non-maximally entangled state quantum grail network practical protocol

A Heterogeneous Reinforcement Learning Approach for Joint Relay Selection and Power Allocation in Time-Varying Uasns with Energy Harvesting

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SSRN

SSRN 2024年

作者： Han, Song Wang, Ziyuan Li, Aijia Li, Xinbin Liu, Zhixin Yan, Lei Zhang, Tong Wei Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Hebei Province Qinhuangdao066004 China School of Computer and Communication Engineering Northeastern University Hebei Province Qinhuangdao066004 China Department of Technology Northeastern University Shandong Province Qingdao266237 China

In this study, we investigate the joint relay selection and power allocation problem for underwater acoustic communication networks with energy harvesting to maximize the cumulative capacity. We specially formulate a heterogeneous reinforcement learning-based framework. In the different decision layers, the Upper Confidence Bound 1 and enhanced Deep Deterministic Policy Gradient algorithms are employed to efficiently explore the discrete and continuous action spaces, respectively. Therefore, the solving difficulty of the complex hybrid discrete-continuous optimization problem can be significantly mitigated. Furthermore, a circular interaction structure is constructed to facilitate the exchange of decision-making information between the two decision layers. The strongly interdependent relationship of the different substrategies can be comprehensively considered, thereby improving the entire performance of thejoint strategy. Moreover, we propose an adaptive reward function, which can guide the user to balance the instantaneous capacity and interruptions, thereby effectively utilizing the green energy harvesting technology and enhancing long-term cumulative performance. Simulation results verify the effectiveness of our proposed algorithm. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

Key Technologies and Applications of Smart Maintenance for Metro Rails Based on Lifecycle Management 26

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Key Technologies and Applications of Smart Maintenance for M...

26th International Conference on Industrial technology, ICIT 2025

作者： Bai, Lei Li, Qing Wu, Saijia Du, Jinhai Ding, Ming Chi, Chen Engineering Technology Center of Urban Rail Transit Vibration and Noise Control Ministry of Ecology and Environment Beijing Jiuzhouyigui Environmental Technology Co. Ltd. Beiijng China Beijing National Railway Research & Design Institute of Signal & Communication Beiijng China Tianjin Jintie Urban Rail Transit Engineering Co. Ltd Tianjin China

ISBN: (纸本)9798331521950

China's metro system ranks among the top in the world in terms of both its total operational mileage and the scale of planned construction. As the metro system enters a phase where construction and operation are given equal priority, there is an increased demand for improved management capabilities in metro operation and maintenance. This paper investigates the business requirements for lifecycle management of metro rails, exploring key technologies such as coding standards for individual rails, attribute data standards, the implementation of electronic tags, and service life evaluation models. A lifecycle management information system for metro rails has been designed and developed, which supports rail degradation prediction and optimizes maintenance and replacement decisions. This paper focuses on the system's technical architecture and core functionalities. The system has been successfully implemented on the actual lines of Tianjin Metro, effectively meeting operational requirements and yielding positive application outcomes. © 2025 IEEE.

关键词： Information management

Analyzing Generalization in Policy Networks: A Case Study with the Double-Integrator System

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arXiv 2023年

作者： Zhang, Ruining Han, Haoran Lv, Maolong Yang, Qisong Cheng, Jian School of Information and Communication Engineering University of Electronic Science and Technology of China China Glasgow School University of Electronic Science and Technology of China China Air Traffic Control and Navigation College Air Force Engineering University China Xi’an Institute of High-Tech China

Extensive utilization of deep reinforcement learning (DRL) policy networks in diverse continuous control tasks has raised questions regarding performance degradation in expansive state spaces where the input state norm is larger than that in the training environment. This paper aims to uncover the underlying factors contributing to such performance deterioration when dealing with expanded state spaces, using a novel analysis technique known as state division. In contrast to prior approaches that employ state division merely as a post-hoc explanatory tool, our methodology delves into the intrinsic characteristics of DRL policy networks. Specifically, we demonstrate that the expansion of state space induces the activation function tanh to exhibit saturability, resulting in the transformation of the state division boundary from nonlinear to linear. Our analysis centers on the paradigm of the double-integrator system, revealing that this gradual shift towards linearity imparts a control behavior reminiscent of bang-bang control. However, the inherent linearity of the division boundary prevents the attainment of an ideal bang-bang control, thereby introducing unavoidable overshooting. Our experimental investigations, employing diverse RL algorithms, establish that this performance phenomenon stems from inherent attributes of the DRL policy network, remaining consistent across various optimization algorithms. © 2023, CC BY-NC-ND.

关键词： Reinforcement learning

Key Technologies and Applications of Smart Maintenance for Metro Rails Based on Lifecycle Management

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Key Technologies and Applications of Smart Maintenance for M...

IEEE International Conference on Industrial technology (ICIT)

作者： Lei Bai Qing Li Saijia Wu Jinhai Du Ming Ding Chen Chi Engineering Technology Center of Urban Rail Transit Vibration and Noise Control Ministry of Ecology and Environment Beijing Jiuzhouyigui Environmental Technology Co. Ltd. Beiijng China Beijing National Railway Research & Design Institute of Signal & Communication Beiijng China Tianjin Jintie Urban Rail Transit Engineering Co. Ltd Tianjin China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

关键词： Rails Evaluation models Management information systems Near field communication Predictive models Maintenance Safety Standards Monitoring Business

RGB-D Instance Segmentation-based Suction Point Detection for Grasping

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RGB-D Instance Segmentation-based Suction Point Detection fo...

2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Fu, Yeyu Sun, Ting Wang, Li Yu, Shijie Deng, Lei Chen, Baohua Li, Lin Xie, Yusen Deng, Shuixin Yin, Hanxi Beijing Information Science & Technology University Joint International Research Laboratory of Advanced Photonics and Elextronics Beijing China Beijing Institute of Control Engineering Space Optoelectronic Measurement and Perception Lab. Department of Perception Zhong-guancun Open Lab. Beijing China Tsinghua University Department of Automation Beijing China

ISBN: (纸本)9781665481090

Suction is a common way for robots to pick objects in industry, which has higher stability and reliability. However, it is necessary to evaluate the suction position on the object's surface when dealing with objects of different shapes. The previous method decouples it into a two-stage suction point detection and objects classification process, making the task more complex and time-consuming. On the other hand, there are significant challenges in acquiring training data. To address that, we propose an object instance segmentation-based suction grasping point detection method. Instance segmentation, as an object pixel-level perception method, can classify objects and find the orientation of objects in the plane, which is more efficient than simple classification. Specifically, our method generate a suction heatmap and object instance segmentation from RGB-D inputs and find the suction grasping position of each object after candidate points screening. To generate the training data, a heatmap mask based on 2D Gaussian-encoded is used to annotate the suction grasping ground truth. We evaluate each object's predicted suction grasping point results and conduct grasping experiments in real environments. The suction grasping success rate of 94% in dense scenes demonstrates the remarkable performance of the proposed method. © 2022 IEEE.

关键词： Object detection