IEEE Open Journal of Vehicular Technology最新文献

{"title":"Experimental Open-Source-Based Evaluation Platform for Highly Spectral-Efficient 5G With Simplified UTW-OFDM","authors":"Kazuki Takeda;Keiichi Mizutani;Hiroshi Harada","doi":"10.1109/OJVT.2025.3569518","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3569518","url":null,"abstract":"Fifth-generation mobile communication (5G) systems are increasingly being deployed in both commercial and private wireless networks to meet the growing demand for high-speed, reliable connectivity. While 5G systems adopt orthogonal frequency-division multiplexing (OFDM) for its high data rates and spectral efficiency, OFDM is known to generate large out-of-band emissions (OOBE), which must be suppressed to maximize spectrum usage. In this study, to tackle this issue, we propose and develop an experimental 5G full-stack evaluation platform that implements a waveform-shaping function for OFDM signals. The platform utilizes software-defined radio and open-source 5G software compliant with third-generation Partnership Project standards. We implement a simplified universal time-domain windowed OFDM as an application of the waveform shaping. This is a waveform shaping technique that can strongly suppress OOBE by applying a long time-domain window to the conventional cyclic prefix OFDM symbol. The transmission performance of the proposed platform was evaluated using a complete 5G system, which includes a 5G base station, user equipment, and a 5G core network. The effectiveness of the proposed platform is verified through link-level computer simulations. The results demonstrate that the block error rate characteristics exhibited a signal-to-noise power ratio difference of less than 1 dB between the platform and simulations and achieved an OOBE suppression of up to 24 dB at a bandwidth of 40 MHz. Furthermore, connectivity with a commercial 5G device demonstrated the feasibility of achieving OOBE suppression of 22 dB at a bandwidth of 100 MHz with a tolerable decrease of 18% in user throughput.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1426-1437"},"PeriodicalIF":5.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11002599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"URLLC Over Slow Fading Channels: K-Repetition Versus Multi-Connectivity","authors":"Qingjiao Song;Fu-Chun Zheng;Jingjing Luo","doi":"10.1109/OJVT.2025.3569187","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3569187","url":null,"abstract":"In this work, we analyze the performance of the uplink ultra-reliable and low-latency communications (URLLC) for the low-mobility users (UEs) in a factory environment. The <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme is a promising approach for improving URLLC reliability, but most studies so far have been carried out assuming fast fading. A UE with low mobility typically experiences a time-correlated slow fading channel. We therefore consider the effects of time correlation in analyzing the performance of a <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme. On the other hand, multi-connectivity (MC) schemes can overcome such effects and improve reliability through space diversity. We then apply differential modulation to both schemes to support URLLC services, and compare their performance. The simulation results show that such slow fading channels severely decreases the time diversity of a <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme, and the MC scheme outperforms the <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme in terms of reliability and transmission latency.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1280-1286"},"PeriodicalIF":5.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10999067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming Highway Safety With Autonomous Drones and AI: A Framework for Incident Detection and Emergency Response","authors":"Muhammad Farhan;Hassan Eesaar;Afaq Ahmed;Kil To Chong;Hilal Tayara","doi":"10.1109/OJVT.2025.3549387","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3549387","url":null,"abstract":"Highway accidents pose serious challenges and safety risks, often resulting in severe injuries and fatalities due to delayed detection and response. Traditional accident management methods heavily rely on manual reporting, which can be sometime inefficient and error-prone resulting in valuable life loss. This paper proposes a novel framework that integrates autonomous aerial systems (drones) with advanced deep learning models to enhance real-time accident detection and response capabilities. The system not only dispatch the drones but also provide live accident footage, accident identification and aids in coordinating emergency response. In this study we implemented our system in Gazebo simulation environment, where an autonomous drone navigates to specified location based on the navigation commands generated by Large Language Model (LLM) by processing the emergency call/transcript. Additionally, we created a dedicated accident dataset to train YOLOv11 m model for precise accident detection. At accident location the drone provides live video feeds and our YOLO model detects the incident, these high-resolution captured images after detection are analyzed by Moondream2, a Vision language model (VLM), for generating detailed textual descriptions of the scene, which are further refined by GPT 4-Turbo, large language model (LLM) for producing concise incident reports and actionable suggestions. This end-to-end system combines autonomous navigation, incident detection and incident response, thus showcasing its potential by providing scalable and efficient solutions for incident response management. The initial implementation demonstrates promising results and accuracy, validated through Gazebo simulation. Future work will focus on implementing this framework to the hardware implementation for real-world deployment in highway incident system.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"829-845"},"PeriodicalIF":5.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10918802","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cyber Threat Susceptibility Assessment for Heavy-Duty Vehicles Based on ISO/SAE 21434","authors":"Narges Rahimi;Beth-Anne Schuelke-Leech;Mitra Mirhassani","doi":"10.1109/OJVT.2025.3550307","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3550307","url":null,"abstract":"TARA, which stands for Threat Analysis and Risk Assessment, serves as the foundational stage of cybersecurity implementation, particularly in the context of vehicular systems. While various considerations and risk assessment frameworks have been discussed in recent years, there is a notable lack of TARA models specifically designed for heavy-duty (HD) vehicles. The security considerations and vulnerabilities in HD vehicles differ significantly from those in light-duty (LD) vehicles, leading to different security impacts and varying attack feasibility. This makes existing models inadequate for accurately assessing risks in the context of HD vehicles. This study introduces a novel risk assessment model tailored for HD vehicles, addressing gaps in existing TARA frameworks such as EVITA, HEAVENS, and ISO/SAE 21434. The key contribution of this work lies in the customization of impact and feasibility metrics within the ISO/SAE framework to better account for the unique security challenges posed by HD vehicles. Unlike prior models, this approach adapts the impact criteria to reflect the diverse range of security concerns specific to HD vehicles, which have been inadequately addressed in existing frameworks. Additionally, through a comprehensive analysis of threat vectors and vehicle interfaces, the model refines feasibility criteria, ensuring a more accurate and context-aware assessment of security risks. By adopting these enhancements, the proposed model offers more precise risk assessments that align with HD vehicle considerations, helping to prioritize threats and make optimal decisions regarding risk treatment.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"969-990"},"PeriodicalIF":5.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10921673","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Graph Neural Backdoors in Vehicular Networks: Fundamentals, Methodologies, Applications, and Future Perspectives","authors":"Xiao Yang;Gaolei Li;Kai Zhou;Jianhua Li;Xingqin Lin;Yuchen Liu","doi":"10.1109/OJVT.2025.3550411","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3550411","url":null,"abstract":"Advances in Graph Neural Networks (GNNs) have substantially enhanced Vehicular Networks (VNs) across primary domains, encompassing traffic forecasting and management, route optimization and algorithmic planning, and cooperative driving. Despite the boosts of the GNN for VNs, recent research has empirically demonstrated its potential vulnerability to backdoor attacks, wherein adversaries integrate triggers into inputs to manipulate GNNs to generate adversary-premeditated malicious outputs (<italic>e.g.</i>, misclassification of vehicle actions or traffic signals). This susceptibility is attributable to adversarial manipulation attacks targeting the training process of GNN-based VN systems. Although there is a rapid increase in research on GNN backdoors, systematic surveys within this domain remain lacking. To bridge this gap, we present the first survey dedicated to GNN backdoors. We start with outlining the fundamental definition of GNNs, followed by the detailed summarization and categorization of current GNN backdoors and countermeasures based on their technical features and application scenarios. Subsequently, an analysis of the applicability paradigms of GNN backdoors is conducted, and prospective research trends are presented. Unlike prior surveys on vision-centric backdoors, we uniquely investigate GNN-oriented backdoor attacks in VNs, which aims to explore attack surfaces across spatiotemporal vehicular graphs and provide insights to security research.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1051-1071"},"PeriodicalIF":5.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10921674","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DFT-Spread OFDM-Based MIMO Joint Communication and Sensing System","authors":"Max Schurwanz;Jan Mietzner;Peter Adam Hoeher","doi":"10.1109/OJVT.2025.3549918","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3549918","url":null,"abstract":"This paper introduces a joint communication and sensing (JCAS) system design that employs a discrete Fourier transform (DFT)-spread orthogonal frequency-division multiplexing (OFDM) waveform integrated with a multiple-input multiple-output (MIMO) antenna array. This system has been designed with the specific requirements of future remotely piloted or autonomous aircraft systems in urban air mobility (UAM) settings in mind. The objective is to provide high-bandwidth data transmission in conjunction with precise radar sensing, thereby enhancing situational awareness and facilitating efficient spectrum usage. The paper makes a number of significant contributions to the field, including the development of a flexible MIMO DFT-spread OFDM system model and the introduction of a phase compensation term for comprehensive direction-of-arrival estimation. Additionally, the effects of non-linear power amplifiers on system efficacy are analyzed through detailed simulations, providing a rigorous evaluation of the proposed design's practicality and resilience. The numerical analysis establishes a framework for the design of a JCAS system for UAM, taking into account the influence of realistic electronic components and the respective performance requirements for communication and sensing.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"868-880"},"PeriodicalIF":5.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10919057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Max–Min Secrecy Rate and Secrecy Energy Efficiency Optimization for RIS-Aided VLC Systems: RSMA Versus NOMA","authors":"Omar Maraqa;Sylvester Aboagye;Majid H. Khoshafa;Telex M. N. Ngatched","doi":"10.1109/OJVT.2025.3568436","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3568436","url":null,"abstract":"Integrating visible light communication (VLC) with the reconfigurable intelligent surface (RIS) significantly enhances physical layer security by enabling precise directional signal control and dynamic adaptation to the communication environment. These capabilities strengthen the confidentiality and security of VLC systems. This paper presents a comprehensive study on the joint optimization of VLC access point (AP) power allocation, RIS association, and RIS elements orientation angles for secure VLC systems, while considering rate-splitting multiple access (RSMA) and power-domain non-orthogonal multiple access (NOMA) schemes. Specifically, two frameworks are proposed to maximize both the minimum secrecy rate (SR) and the minimum secrecy energy efficiency (SEE) by jointly optimizing power allocation, RIS association, and RIS elements orientation angles for both power-domain NOMA and RSMA-based VLC systems. The proposed frameworks consider random device orientation and guarantee the minimum user-rate requirement. The proposed optimization frameworks belong to the class of mixed integer nonlinear programming, which has no known feasible solution methodology to guarantee the optimal solution. Moreover, the increased degree of freedom and flexibility from the joint consideration of power control, RIS association and element orientation results in a large set of decision variables and constraints, which further complicates the optimization problem. To that end, we utilize a genetic algorithm-based solution method, which through its exploration and exploitation capabilities can obtain a good quality solution. Additionally, comprehensive simulations show that the RSMA scheme outperforms the power-domain NOMA scheme across both the SR and SEE metrics over various network parameters. Furthermore, useful insights on the impact of minimum user rate requirement, number of RIS elements, and maximum VLC AP transmit power on the minimum SR and SEE performances are provided.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1303-1316"},"PeriodicalIF":5.3,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10994327","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ISAC Receiver Design: Joint DoA and Data Estimation in the Presence of Incomplete Signal Observations","authors":"Iman Valiulahi;Christos Masouros;Mahmoud Alaaeldin;Emad Alsusa","doi":"10.1109/OJVT.2025.3544148","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3544148","url":null,"abstract":"Integrated sensing and communication (ISAC) receiver design involves the challenge of jointly estimating the communication signal together with the direction of arrivals (DOAs) of the transmitters. This letter proposes an off-the-grid estimator for the ISAC receiver that jointly estimates the DOAs of <inline-formula><tex-math>$K$</tex-math></inline-formula> transmitters together with the communication data. We focus on the challenging case of incomplete observation, i.e., where only a subset of the received signals in space and time are available. We propose a convex optimization based on the dual of atomic norm minimization (ANM). Though the problem is non-deterministic polynomial time (NP)-hard, we leverage the Schur complement technique to develop semidefinite relaxations (SDRs) to implement it. Moreover, we study a fast algorithm based on the alternating direction method of multipliers (ADMM) technique. Finally, our numerical results explore the feasibility of the joint estimation with incomplete observations, while outperforming classical DOA estimators.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"846-852"},"PeriodicalIF":5.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10918629","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Mobile Network Slicing Through Vehicular Traffic Analysis","authors":"Álvaro Gabilondo;Zaloa Fernández;Ángel Martín;Mikel Zorrilla;Pablo Angueira;Jon montalbán","doi":"10.1109/OJVT.2025.3567116","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3567116","url":null,"abstract":"Network slicing has emerged as a transformative enabler in 5G networks, offering tailored communication services for diverse traffic types on shared network infrastructure. In the context of autonomous driving and smart mobility, the ability to dynamically prioritize and manage sensor data—ranging from high-bandwidth video streams to low-latency text and binary position and coordination messages—plays a pivotal role in ensuring safe and efficient operation. This paper proposes a dynamic mobile network slicing framework designed to analyse vehicular traffic and adapt slicing policies to optimize resource allocation for autonomous driving applications. By leveraging distributed and disaggregated 5G network architectures, the proposed solution ensures seamless propagation of slicing policies across radio access networks (RAN) and core systems building end-to-end network slices. Experimental evaluations in scenarios such as Automated Guided Vehicle (AGV)-assisted operations in industrial environments demonstrate significant performance improvements, including a reduction in packet loss from 65% to 0% under congested network conditions. The results highlight the potential of dynamic slicing to enhance communication reliability and performance in autonomous driving ecosystems, supporting the seamless exchange of diverse sensor data types.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1464-1480"},"PeriodicalIF":5.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10988659","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"UAP: A System Authentication Protocol for UAV Relay Communication by UAV-Assisted","authors":"Chunpeng Liu;Tao Huang;Maode Ma","doi":"10.1109/OJVT.2025.3567079","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3567079","url":null,"abstract":"In recent years, advancements in Unmanned Aerial Vehicle (UAV) technology have led to the emergence of the Internet of Drones (IoD), further enhanced by the capabilities of 5th generation mobile network (5G). UAVs are widely used in various applications, such as disaster assessment, material delivery, and environmental monitoring, due to their flexibility. However, operating in insecure open environments presents significant risks, making it crucial to complete tasks without exposing sensitive information to attackers or unauthorized users. Additionally, the communication range between UAVs and ground stations is often limited, and if a UAV flies beyond this range, the likelihood of mission failure increases substantially. To address these challenges, we propose a UAV-assisted Authentication Protocol (UAP) based on Physical Unclonable Functions (PUFs), leveraging 5G to enable secure relay communication between UAVs and ground stations. We provide formal proof of the protocol's logical correctness and perform cryptanalysis, demonstrating that it effectively resists various security threats, including masquerade and replay attacks. Furthermore, we evaluate the resilience of UAP against multiple security vulnerabilities using the Scyther tool. Finally, we compare our protocol with existing authentication methods in terms of application scenarios, security features, and both computational and communication overhead. We have performed simulations on a Raspberry Pi. The experiments show that UAP has a computational overhead of 0.0826 ms and a communication overhead of 0.0408 ms. The application scenarios and security features of UAP are also considered, making it a solution for UAV applications.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1539-1550"},"PeriodicalIF":5.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10988496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}