IEEE Open Journal of Vehicular Technology最新文献

{"title":"Time Complexity of Training DNNs With Parallel Computing for Wireless Communications","authors":"Pengyu Cong;Chenyang Yang;Shengqian Han;Shuangfeng Han;Xiaoyun Wang","doi":"10.1109/OJVT.2025.3526847","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3526847","url":null,"abstract":"Deep neural networks (DNNs) have been widely used for learning various wireless communication policies. While DNNs have demonstrated the ability to reduce the time complexity of inference, their training often incurs a high computational cost. Since practical wireless systems require retraining due to operating in open and dynamic environments, it is crucial to analyze the factors affecting the training complexity, which can guide the DNN architecture selection and the hyper-parameter tuning for efficient policy learning. As a metric of time complexity, the number of floating-point operations (FLOPs) for inference has been analyzed in the literature. However, the time complexity of training DNNs for learning wireless communication policies has only been evaluated in terms of runtime. In this paper, we introduce the number of serial FLOPs (se-FLOPs) as a new metric of time complexity, accounting for the ability of parallel computing. The se-FLOPs metric is consistent with actual runtime, making it suitable for measuring the time complexity of training DNNs. Since graph neural networks (GNNs) can learn a multitude of wireless communication policies efficiently and their architectures depend on specific policies, no universal GNN architecture is available for analyzing complexities across different policies. Thus, we first use precoder learning as an example to demonstrate the derivation of the numbers of se-FLOPs required to train several DNNs. Then, we compare the results with the se-FLOPs for inference of the DNNs and for executing a popular numerical algorithm, and provide the scaling laws of these complexities with respect to the numbers of antennas and users. Finally, we extend the analyses to the learning of general wireless communication policies. We use simulations to validate the analyses and compare the time complexity of each DNN trained for achieving the best learning performance and achieving an expected performance.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"359-384"},"PeriodicalIF":5.3,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10830510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106231","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":"Enabling Super-Resolution for Automotive Imaging Radars in the Presence of Antenna Calibration Errors","authors":"Ionela-Cristina Voicu;Filip Rosu","doi":"10.1109/OJVT.2025.3526133","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3526133","url":null,"abstract":"Radar is an essential technology for Advanced Driving Assistance Systems (ADAS), used to accurately localize objects even in unfavorable weather conditions. Most radar systems that are now being produced for ADAS provide either 3D or 4D point clouds, containing range, Doppler, azimuth, and elevation information for every detected point target. Out of all dimensions, the azimuth and elevation are estimated using more advanced algorithms than the ones generally used for range and Doppler. This is due to the restricted size of the aperture that can be safely mounted on a vehicle, hence the resolution must be enhanced digitally. When using advanced algorithms challenges such as precise antenna manufacturing are of significant importance, to avoid phase and gain mismatch between the antenna elements along with their inherent coupling. These negative effects lead to a significant degradation in the Direction of Arrival estimation. Super-resolution techniques such as MUSIC and CAPON are widely referenced, however their performance throughout prior work is evaluated in ideal environments and generally with multiple available data acquisition snapshots. In this paper we address the issues faced when applying such algorithms in a radar application and offer a solution based on linear prediction and spatial smoothing to enhance the performance of such algorithms.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"385-395"},"PeriodicalIF":5.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829667","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106232","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":"Need of UAVs and Physical Layer Security in Next-Generation Non-Terrestrial Wireless Networks: Potential Challenges and Open Issues","authors":"Asim Ul Haq;Seyed Salar Sefati;Syed Junaid Nawaz;Albena Mihovska;Michail J. Beliatis","doi":"10.1109/OJVT.2025.3525781","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3525781","url":null,"abstract":"Recent revolutionary advancements in the services as observed with the use cases of Industry 5.0, consumer electronics 2.0/smart devices 2.0, digital healthcare ecosystem, Internet-of-Things (IoT), advanced digital finance/currency, and Non-Terrestrial Network (NTN) expansion, to name a few, have resulted in a spectacular growth in the number of wireless-connected devices. Subsequently, this has drastically increased the demands for network capacity, channel capacity, reliability, privacy, and security provisions. Despite that, the 5th Generation (5G) of wireless communication networks has introduced various innovative services such as Ultra-Reliable Low Latency Communication (URLLCs), Massive Machine Type Communication (mMTCs), and Enhanced Mobile Broadband (eMBB). These services only support isolated operations and the requisite reliable service delivery remains a challenge. The Beyond 5G (B5G)/6th Generation (6G) wireless networks aim at simultaneously providing multiple integrated services through intelligent network operations with ultra-high speed and reliability supporting integrated NTN and terrestrial networks. However, the prospect of such an extensively connected decentralized 3D wireless network also foresees security concerns, underscoring the necessity for seamless and infrastructure-free (decentralized) security solutions. The conventional security mechanisms are considered inadequate to ensure the security provisions of such extensive, decentralized, and heterogeneous networks. Physical Layer Security (PLS) is a promising technique to extend seamless and infrastructure-less security solutions, ensuring the availability, confidentiality, and integrity of legitimate transmissions. This paper provides a comprehensive overview with tutorials and presents the state-of-the-art of PLS, focusing mainly on NTN wireless communications. Furthermore, current research challenges, open issues, and future research directions are also thoroughly discussed in an amalgamation of various emerging 6G technologies. Finally, we provide an overview of implementation challenges in NTN and potential solutions to support the standardization progression of NTN in upcoming releases of 3rd Generation Partnership Project (3GPP).","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"554-595"},"PeriodicalIF":5.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10824882","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403802","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":"The Impact of Rain on Image Quality From Sensors on Connected and Autonomous Vehicles","authors":"Tim Brophy;Darragh Mullins;Robert Cormican;Enda Ward;Martin Glavin;Edward Jones;Brian Deegan","doi":"10.1109/OJVT.2025.3525853","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3525853","url":null,"abstract":"As automated vehicles progress toward increasing levels of autonomy, the need for thorough testing of such systems in all relevant environments increases. These safety-critical systems often rely on visible-spectrum cameras to perceive the environment. Therefore, these systems must perform reliably under a range of adverse weather conditions. This study investigates the impact of rain on the quality of images taken in an experimental setting designed to vary rain intensity in a controlled manner. This study analyzes the impact of rain using low-level metrics such as contrast and spatial frequency response. In addition, overall image quality was evaluated using a range of full-reference image quality metrics. The results show a 45% reduction in SNR at 40 m and 38 mm/h, a 70% maximum decrease in Weber contrast at 30 m and 38 mm/h, and a 42% increase in color error as a result of rain in the environment. Consequently, degradation in image quality is likely to affect subsequent downstream computer vision performance. The results of this study highlight the need for robust testing and optimization of camera systems.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"632-646"},"PeriodicalIF":5.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10824872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535530","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":"Beyond Single-User Scheduling: Exploiting Massive MIMO for Concurrent Data Delivery With Minimum Age of Information","authors":"Muhammad Fahad Ijaz;Umar Rashid;Omer Waqar","doi":"10.1109/OJVT.2024.3523247","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3523247","url":null,"abstract":"With the emergence of real-time applications, modern wireless networks have witnessed the use of Age of Information (AoI) as a critical metric for evaluating the timeliness of data delivery. This paper considers multi-user scheduling, extending beyond traditional single-user scheduling, to exploit the potential of Massive Multiple-Input Multiple-Output (mMIMO) systems for concurrent data delivery over imperfectly known channel state information (CSI). We propose a novel transmission scheduling framework that leverages the spatial multiplexing capabilities of mMIMO to minimize the AoI across multiple users. This results in a joint optimization of multi-user scheduling and power allocation problem for optimum data freshness in a wireless broadcast network. We handle the non-convexity of the resulting problem by utilizing successive convex approximation to specifically reformulate the binary/integer and non-convex constraints of the problem. Extensive simulations demonstrate superior performance of the proposed framework and its solution in terms of AoI compared to existing benchmarks.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"301-314"},"PeriodicalIF":5.3,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818777","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993438","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":"Scalable Cell-Free Massive MIMO With Indoor/Outdoor Users","authors":"Felip Riera-Palou;Miquel Duran;Guillem Femenias","doi":"10.1109/OJVT.2024.3524271","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3524271","url":null,"abstract":"Cell-free networks are expected to be a forthcoming (r)evolutionary step in the coming generation of mobile networks, the so called 6 G. While mobile infrastructure is often assumed to be deployed outdoor by the operators, reality is that most of the traffic has at least one of the communication ends located indoors. This paper introduces the problem of providing wireless service to a heterogeneous population made of indoor and outdoor users using an outdoor cell-free massive MIMO (CF-mMIMO) infrastructure. It is shown how the pervasive max-min criterion (in cell-free setups) that results in near-uniform quality-of-service to all users may lead to catastrophic consequences when some of the users happen to be indoor. This problem is analyzed in both communication directions, uplink and downlink, exposing the similarities and differences of these two scenarios. Direction-specific solutions are then provided that involve improving the channel estimation and connectivity of indoor users and modifying the power allocation so as to somehow compensate for the wall propagation indoor users have to endure. All the techniques introduced satisfy the scalability requirements thus making our proposal realistically implementable.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"332-347"},"PeriodicalIF":5.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818704","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993439","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":"Security Risks and Designs in the Connected Vehicle Ecosystem: In-Vehicle and Edge Platforms","authors":"Marco De Vincenzi;John Moore;Bradley Smith;Sanjay E. Sarma;Ilaria Matteucci","doi":"10.1109/OJVT.2024.3524088","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3524088","url":null,"abstract":"The evolution of Connected Vehicles (CVs) has introduced significant advancements in both in-vehicle and vehicle-edge platforms, creating a highly connected ecosystem. These advancements, however, have heightened exposure to cybersecurity risks. This work reviews emerging security challenges in the CV ecosystem from a new perspective, focusing on the integration of in-vehicle platforms such as the infotainment system and vehicle-edge platforms. By analyzing case studies such as Android Automotive, Message Queuing Telemetry Transport (MQTT), and the Robot Operating System (ROS), we identify the primary security threats, including malware attacks, data manipulation, and Denial of Service (DoS) attacks. The discussion extends to privacy concerns and the lack of trust-building mechanisms in CVs, highlighting how these gaps can be exploited. To mitigate these risks, we retrieve solutions drawn from the broader field of Internet of Things (IoT) security research, including Multi-Factor Authentication (MFA) and trust-based systems. The proposed framework aims to increase the trustworthiness of devices within the CV ecosystem. Finally, we identify future research directions in adaptive mechanisms and cross-domain security.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"442-454"},"PeriodicalIF":5.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818588","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106233","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":"Anomaly Detection in High Mobility MDT Traces Through Self-Supervised Learning","authors":"J. M. Sánchez-Martín;C. Gijón;M. Toril;S. Luna-Ramírez;V. Wille","doi":"10.1109/OJVT.2024.3524057","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3524057","url":null,"abstract":"Radio access network optimization is a critical task in current cellular systems. For this purpose, Minimization of Drive Test (MDT) functionality provides mobile operators with georeferenced network performance statistics to tune radio propagation models in re-planning tools. However, some samples in MDT traces contain critical location errors due to the user equipment's energy-saving, thus making MDT data filtering vital to guarantee an adequate performance of MDT-driven algorithms. Supervised Learning (SL) allows to train automatic systems for detecting abnormal MDT measurements by using a labeled dataset. Unfortunately, labeling MDT data is a labor-intensive task, that can be alleviated by using Self-Supervised Learning (SSL). This work presents a novel SSL method to detect MDT measurements with abnormal position information in road scenarios. For this purpose, a dataset is first labeled by combining unlabeled MDT traces from high-mobility users and freely available land use maps, and then an SL classifier is trained. Model assessment is carried out using MDT data collected in a live Long-Term Evolution (LTE) network. Performance analysis includes the comparison of six well-known SL algorithms and 3 different sets of input features aiming to improve model accuracy, generalizability, and explainability, respectively. Results show that considering predictors regarding positioning error increases model accuracy, whereas omitting this information allows to cover a wider range of terminals. Likewise, Shapley Additive exPlanations (SHAP) analysis proves that the use of high-level predictors significantly improves model explainability.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"396-411"},"PeriodicalIF":5.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818611","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106229","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":"Millimeter-Wave V2X Channel Measurements in Urban Environments","authors":"Andreas F. Molisch;Christoph F. Mecklenbräuker;Thomas Zemen;Ales Prokes;Markus Hofer;Faruk Pasic;Hussein Hammoud","doi":"10.1109/OJVT.2024.3521637","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3521637","url":null,"abstract":"Vehicle-to-everything (V2X) communications is an important part of future driver assistance and traffic control systems that will reduce accidents and congestion. The millimeter-wave (mmWave) band shows great promise to enable the high-data-rate links that are required or at least beneficial for such systems. To design such systems, we first need a detailed understanding of the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2X) propagation channels. This paper provides a systematic account of a series of measurement campaigns for such channels, conducted by the four research institutions of the authors over the past year. After a description of the similarities and differences of the channel sounders used in the campaigns, a description of the measurements in two European and one American city is given, and the scenarios of convoy, opposite-lane passing, and overtaking, are described. This is then followed by key results, presenting both sample results of power delay profiles and delay Doppler (or angular) spectra, as well as the statistical description such as delay spread and size of stationarity region. We also discuss the availability of spatial diversity in V2I connections and the correlation of the channels between different frequency bands.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"520-541"},"PeriodicalIF":5.3,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10814933","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403850","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":"Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks","authors":"Omar S. Aba Hussen;Shaiful J. Hashim;Nasri Sulaiman Member;S.A.R. Alhaddad;Bassam Y. Ribbfors;Masanobu Umeda;Keiichi Katamine","doi":"10.1109/OJVT.2024.3521091","DOIUrl":"https://doi.org/10.1109/OJVT.2024.3521091","url":null,"abstract":"This research optimizes an electric vehicle (EV) sharing system for a university campus, focusing on different demand patterns and peak times within an Intelligent Transportation System (ITS) framework. The main objectives are to reduce the number of unserved demands and operational costs. A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. In addition to conventional decision variables, dynamic dual relocation thresholds and charge levels are introduced as decision variables to enhance optimization. The study compares two scenarios: Equally Distributed Demand (EDD) and Non-Equally Distributed Demand (NEDD), customized for the University Putra Malaysia (UPM) campus. Findings indicate that the NEDD scenario, which concentrates on specific demand areas, effectively decreases unserved demands and operational costs. Additionally, a station-specific approach expanded the solution space, improving adaptability and resulting in notable reductions in operational costs and smaller but meaningful improvements in unserved demands, especially during peak periods. By setting station-specific relocation thresholds and charge levels, resources were deployed efficiently, minimizing unnecessary relocations. The use of dynamic values for dual relocation thresholds and charge-to-work levels further optimized the process, reducing operational costs significantly, with a lesser impact on unserved demands across both scenarios. This research offers valuable insights into the implementation of EV sharing systems in educational institutions, emphasizing the advantages of focused resource allocation and the integration of dynamic decision variables.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"315-331"},"PeriodicalIF":5.3,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10811944","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993437","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}