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Integrated Non-Terrestrial and Terrestrial Quantum Anonymous Networks

IEEE Network 2025年第3期39卷 196-206页

作者： Khan, Awais Bui, Tinh Thanh Rehman, Junaid Ur Chatzinotas, Symeon Cotton, Simon L. Dobre, Octavia A. Duong, Trung Q. Shin, Hyundong Kyung Hee University Department of Electronics and Information Convergence Engineering Gyeonggi-do Yongin-si17104 Korea Republic of King Fahd University of Petroleum and Minerals Department of Electrical Engineering Interdisciplinary Research Center for Intelligent Secure Systems Dhahran Saudi Arabia University of Luxembourg Luxembourg City1855 Luxembourg Memorial University Department of Electrical and Computer Engineering St. John'sNLA1B 3X5 Canada Queen's University Belfast Department of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom

Due to optical fiber limitations for quantum communication, global-scale quantum networks are possible only by integrating non-terrestrial components in the overall network architecture. Quantum networks are expected to support distributed tasks for quantum information processing, such as quantum sensing, control, communication, and computing. These networks enable emerging applications that are uniquely quantum or augmented by quantum mechanics. Leveraging quantum resources, anonymous networking can be enhanced to such an extent that even an adversary with control over all network resources cannot trace the message source, achieving perfect untraceability. To provide this untraceable global connectivity, we demonstrate the integration of non-terrestrial networks (NTNs) and terrestrial networks (TNs) for quantum anonymous communication (QAC), highlighting possible architectures and key challenges in these integrated NTN-TN quantum anonymous networks (QANs). To illustrate and benchmark the design of QAC protocols within integrated networks, we present essential quantum protocols such as anonymous conference key agreement (CKA) and anonymous broadcast. In the first case study, we propose a satellite-to-ground quantum anonymous CKA (QA-CKA) protocol and assess the anonymous key exchange rate. This QA-CKA protocol utilizes low Earth orbit satellites to generate anonymous keys among two distinct TN nodes. In the second case study, we develop an air-to-ground quantum anonymous broadcast (QAB) protocol and examine the anonymous broadcast announcement rate. This QAB protocol exploits unmanned aerial vehicles to enable a broadcasting party to transmit classical information anonymously across two distinct TNs. These QAC protocols are simulated with realistic integrated network parameters to provide practical estimates of achievable performance. Furthermore, we discuss future research directions for enabling integrated NTN-TN QANs. © 1986-2012 IEEE.

关键词： Broadcasting antennas

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Exploring Augmented Reality's Influence on Cognitive Load and Emotional Dynamics within UAV Training Environments

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IEEE Transactions on Learning Technologies 2025年

作者： Rahimi, Fatema Sadeghi-Niaraki, Abolghasem Song, Houbing Wang, Huihui Choi, Soo-Mi Sejong University Department of Computer Science and Engineering Convergence Engineering for Intelligent Drone XR Research Center Seoul Korea Republic of Department of Information Systems BaltimoreMD21250 United States St. Bonaventure University Cybersecurity Program St. BonaventureNY14778 United States

This study investigates the cognitive and emotional processes involved in augmented reality (AR)-based learning. The study looks at learning outcomes, emotional responses, meditation, and attention using a comprehensive approach that includes self-assessment, EEG data gathering, and post-experiment questionnaires. Twelve participants, selected based on their English proficiency and lack of prior knowledge of the course material, engaged in AR-based learning, while a baseline reading condition was included to contextualize cognitive and emotional engagement. The study findings indicate that the AR group's participants demonstrated notably elevated attention and meditation levels, indicating heightened engagement and focus that is advantageous for efficient assimilation and retention of knowledge. Furthermore, AR learners reported feeling less tired and exhausted, which may have mitigated the negative emotional states that are frequently connected to learning activities. However, no significant differences in negative emotions were observed between the reading and AR groups. These results emphasize the value of customized AR environments for education goals and the need for more study to maximize learning outcomes and affective experiences in AR learning contexts. © 2008-2011 IEEE.

关键词： engineering education

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Enhancing Low-Latency and High-Reliability Data Forwarding for In-Vehicle Time-Sensitive Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Sun, Haitong Zhang, Haijun Guan, Wanqing Liu, Xiangnan Ma, Hui Leung, Victor C.M. Hebei Key Laboratory of Space-Air-Ground Intelligent Communication China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden Department of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China

To satisfy the low delay, low jitter, and high success rate requirements for in-vehicle networks, IEEE 802.1 Task Group proposed Time-Sensitive Networking (TSN), which has aroused increasing attention in managing time-critical services in networks. This paper resolves the following issue: how to minimize the worst-case response time (WCRT) of frame forwarding in TSN under no-wait scenarios to guarantee low-latency transmission, stability, and high success rate for in-vehicle TSN networks? Currently, some work resolves this problem by leveraging integer linear programming, and others apply heuristic methods to avoid the time complexity problem, but the success rate is affected since they are prone to get trapped in local optima. To reach a balance between time-complexity and success rate, a scheme named Frame Dynamic Priority Scheduling Mechanism (FDPSM) is proposed, where the frame dynamic priority levels are set up and frames are scheduled accordingly. The target is to maximize the success rate and minimize the WCRT for in-vehicle networks. We evaluate the proposed mechanism from aspects such as traffic forwarding time, size of windows, number of hops, and the network load, together with success rate and the simulation results demonstrate the advantages of the FDPSM for in-vehicle TSN networks. © 2025 IEEE. All rights reserved,

关键词： Integer programming

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Differentially Private Synthetic Adversarial Network Traffic Generation Based on Tabular Diffusion Processes

Differentially Private Synthetic Adversarial Network Traffic...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Minjae Kang Gunhee Cho Sungju Yun Yeonjoon Lee Department of Computer Science and Engineering Major in Bio-Artificial Intelligence Hanyang University Ansan Republic of Korea Department of Intelligent Information Convergence Engineering Hanyang University Ansan Republic of Korea College of Computing Hanyang University Ansan Republic of Korea

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

IDS is becoming increasingly important as networks become more vulnerable to a variety of attacks. However, traditional ML and DL-based IDS have limited accuracy and false positive rates due to the lack of open adversarial network datasets and vendors' concerns regarding potential data leakage during the training process. To address these challenges, VAE and GAN-based network packet generation models have emerged, but they still face issues with low data fidelity. In this context, TabDDPM is a suitable option for generating network packets, as it surpasses VAE and GAN in accurately capturing data distribution characteristics and effectively learning the inherent structure of network packet formats. Despite its potential, research applying TabDDPM to network packet generation has not yet been explored. In this paper, we propose and evaluate DP-NetDDPM, a novel framework that enables adversarial network traffic generation while preserving both fidelity and privacy guarantees. Specifically, we examine the use of diffusion to generate adversarial network packet datasets and compare its performance with baseline models. Our framework focuses on three key criteria: data fidelity, adaptability for machine learning applications, and data privacy. The results show that DP-NetDDPM surpasses traditional models in both fidelity and adaptability, achieving a notable 72% improvement in fidelity and a 45% enhancement in adaptability over baselines.

关键词： Training Adaptation models Privacy Telecommunication traffic Machine learning Network security Generative adversarial networks Data models Faces Payloads

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AI-enabled driver assistance: monitoring head and gaze movements for enhanced safety

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Complex and intelligent Systems 2025年第7期11卷 1-28页

作者： Mudassar Shah, Sayyed Zengkang, Gan Sun, Zhaoyun Hussain, Tariq Zaman, Khalid Alwabli, Abdullah Jaffar, Amar Y. Ali, Farman School of Civil and Transportation Engineering Shenzhen University Guangdong 518060 China School of Computer Science and Technology Zhejiang Gongshang University Hangzhou 310018 China Institute of Intelligent Manufacturing Technology Shenzhen Polytechnic University Guangdong Shenzhen 518000 China Department of Electrical Engineering College of Engineering and Computing in Alqunfudah Umm Al-Qura University Mecca 21955 Saudi Arabia Computer and Network Engineering Department College of Computing Umm Al-Qura University Makkah Saudi Arabia Department of Computer Science and Engineering School of Convergence College of Computing and Informatics Sungkyunkwan University Seoul 03063 South Korea

This paper introduces a real-time head-pose detection and eye-gaze estimation system for Automatic Driver Assistance Technology (ADAT) aimed at enhancing driver safety by accurately collecting and transmitting data on the driver’s head position and eye gaze to mitigate potential risks. Existing methods are constrained by significant limitations, including reduced accuracy under challenging conditions such as varying head orientations and lighting, higher latency in real-time applications (e.g., Faster-RCNN and TPH-YOLOv5), and computational inefficiency, which hinders their deployment in resource-constrained environments. To address these challenges, we propose a novel framework using the Transformer Detection of Gaze Head - YOLOv7 (TDGH-YOLOv7) object detector. The key contributions of this work include the development of a reference image dataset encompassing diverse vertical and horizontal gaze positions alongside the implementation of an optimized detection system that achieves state-of-the-art performance in terms of accuracy and latency. The proposed system achieves superior precision, with a weighted accuracy of 95.02% and Root Mean Square Errors of 2.23 and 1.68 for vertical and horizontal gaze estimation, respectively, validated on the MPII-Gaze and DG-Unicamp datasets. A comprehensive comparative analysis with existing models, such as CNN, SSD, Faster-RCNN, and YOLOv8, underscores the robustness and efficiency of the proposed approach. Finally, the implications of these findings are discussed, and potential avenues for future research are outlined. © The Author(s) 2025.

关键词： Eye gaze estimation Eye tracking Facial detection Gaze Head pose detection

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Adhesive bioelectronics for closed-loop therapy

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Med-X 2025年第1期3卷 1-32页

作者： Jung, Hyunjin Lee, Hyelim Shin, Mikyung Son, Donghee Department of Electrical and Computer Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Center for Neuroscience Imaging Research Institute for Basic Science Suwon Republic of Korea Department of Intelligent Precision Healthcare Convergence Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Biomedical Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Artificial Intelligence System Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea

Wearable and implantable devices mark a major advancement in biomedical engineering, enabling continuous bio-signal monitoring and treatment based on precise feedback. However, traditional rigid bioelectronic devices face challenges in seamlessly interfacing with soft organs, often leading to tissue damage and inflammation. To address these issues, soft bioelectronics that better conform to the body while maintaining performance accuracy have been developed. Despite these advancements, the dynamic nature of body movements and the complex chemical environment in the body can compromise the stability of devices over time. Therefore, recent innovations have focused on ultrathin and stretchable designs that enhance conformal contact through van der Waals forces, as well as the incorporation of adhesive hydrogels, to improve adhesion, even in the presence of biofluids. This review provides a comprehensive overview of the advancements in wearable and implantable bioelectronics aimed at achieving conformal tissue adhesion and long-term stability, covering structural modifications to bilayer designs. Finally, the integration of bioelectronics with closed-loop therapies to significantly enhance treatment efficacy is explored. • Materials strategies and device fabrication/integration processes optimally tailored to various organs are addressed. • Mechanical and electrical characterizations of wearable and implantable adhesive bioelectronics are described, while emphasizing challenges and opportunities in long-term stable tissue interfacing. • Various demonstrations of closed-loop bio-integrated systems using soft stretchable adhesive materials, and their futuristic perspectives are introduced.

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Improved MIMO Signal Detection Based on DNN in MIMO-OFDM System

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computers, Materials & Continua 2022年第2期70卷 3625-3636页

作者： Jae-Hyun Ro Jong-Gyu Ha Woon-Sang Lee Young-Hwan You Hyoung-Kyu Song Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

This paper proposes the multiple-input multiple-output(MIMO)detection scheme by using the deep neural network(DNN)based ensemble machine learning for higher error performance in wireless communication *** the MIMO detection based on the ensemble machine learning,all learning models for the DNN are generated in offline and the detection is performed in online by using already learned *** the offline learning,the received signals and channel coefficients are set to input data,and the labels which correspond to transmit symbols are set to output *** the online learning,the perfectly learned models are used for signal detection where the models have fixed bias and *** performance improvement,the proposed scheme uses the majority vote and the maximum probability as the methods of the model combinations for obtaining diversity gains at the MIMO *** simulation results show that the proposed scheme has improved symbol error rate(SER)performance without additional receive antennas.

关键词： MIMO DNN ensemble machine learning ML

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Joint Scheduling, Computing, and Load Balancing for Time Sensitive Traffic in SDN-Enabled Space-Air-Ground Integrated 6 G Networks: A Federated Reinforcement Learning Approach

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IEEE Transactions on Mobile Computing 2025年

作者： Sun, Haitong Zhang, Haijun Ma, Hui Leung, Victor C.M Hebei Key Laboratory of Space-Air-Ground Intelligent Communication Beijing100083 China University of Science and Technology Beijing Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services Beijing100083 China Shenzhen University Department of Computer Science and Software Engineering Shenzhen518061 China University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Low Earth Orbit (LEO) constellations and Unmanned Aerial Vehicle (UAV) networks enable wide coverage for the sixth generation (6G) mobile communication. However, it is a challenge to achieve high scheduling success rate, ultra-low latency, and efficient load balance in the Space-Air-Ground Integrated 6G Network (SAGGIN). This paper addresses the following issue: How to effectively and orderly transmit time-sensitive traffic in SAGGIN under strict deadlines, limited computational ability, and restrained link capacity? Specifically, this paper uses Software-Defined Networking (SDN) and designs a joint optimization method to enhance the traffic transmission ability of SAGGIN. Considering response time, computing cost, and link capacity in SAGGIN, the scheduling, computing, and load balance issues are modeled as a multi-objective optimization problem that minimizes the worst-case response time and computing cost of data frames while maximizing the network flow. Then, this paper leverages a Federated Reinforcement Learning (FRL) scheme to solve the problem. Results show that the FRL could achieve great scheduling, computing, and load balance performance. Specifically, our method can successfully schedule 80% of the traffic at most when the current network load is around 90%. Furthermore, the computational delay could reduce around 50%. © 2002-2012 IEEE.

关键词： Reinforcement learning

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Efficient Gauss-Seidel Precoding with Parallel Calculation in Massive MIMO Systems

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computers, Materials & Continua 2022年第1期70卷 491-504页

作者： Hyun-Sun Hwang Jae-Hyun Ro Chan-Yeob Park Young-Hwan You Hyoung-Kyu Song Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output(MIMO)*** inter user interference(IUI)which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is *** this paper,the horizontal Gauss-Seidel(HGS)method is proposed as precoding scheme in massive MIMO *** massive MIMO systems,the exact inversion of channel matrix is impractical due to the severe computational ***,the conventionalGauss-Seidel(GS)method is used to approximate the inversion of channel *** GS has good performance by using previous calculation results as ***,the required time for obtaining the precoding symbols is too long due to the sequential process of ***,the HGS with parallel calculation is proposed in this paper to reduce the required *** rows of channel matrix are eliminated for parallel calculation *** addition,HGSuses the ordered channelmatrix to prevent performance degradation which is occurred by parallel *** HGS with proper number of parallelly computed symbols has better performance and reduced required time compared to the traditional GS.

关键词： Massive MIMO GS matrix inversion linear precoding

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Adaptive Relay Selection Scheme for Minimization of the Transmission Time

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computers, Materials & Continua 2021年第10期69卷 1361-1373页

作者： Yu-Jin Na Ji-Sung Jung Young-Hwan You Hyoung-Kyu Song Department of Information and Communication Engineering and Convergence for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering and Convergence for Intelligent DroneSejong UniversitySeoul05006Korea

As the installation of small cells increases,the use of relay also *** relay operates as a base station as well as just an *** the roles and types of relays become more diverse,appropriate relay selection technology is an effective way to improve communication *** researches for relay selection have been studied to secure the reliability of relay *** this paper,the relay selection scheme is proposed for a cooperative system using decode-and-forward(DF)relaying scheme in the mobile communication *** maintain the transmission rate,the proposed scheme classifies a candidate group considering the outage probability of multiple *** the applicable candidate group,the proposed scheme selects the relay considering the amount of data allocated to each ***,the proposed scheme defines the unit transmission time through each user’s data and relay ***,the proposed scheme selects a relay that minimizes the total transmission time through the relay transmission time that calculates the unit transmission time for all *** this adaptive relay selection scheme,an optimal relay can be assigned for each *** the same transmission rate and the amount of data,the proposed scheme improves the performance of transmission time and *** results show that the proposed scheme reduces the total transmission time for the same amount of data and signal to noise ratio(SNR).

关键词： Relay selection cooperative relay MIMO outage probability transmission time

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