Pub Date : 2025-10-01Epub Date: 2025-07-02DOI: 10.1016/j.vehcom.2025.100951
Tong Wang
In multi-UAV-assisted air-ground integrated in-band full-duplex (IBFD) OFDMA networks, both uplink and downlink performances are critical and must be simultaneously considered. This study addresses effective resource allocation in such networks to maximize the total system uplink and downlink rates by jointly optimizing subcarrier assignment and power control. Given the significant trade-off between uplink and downlink transmissions owing to self-interference in IBFD systems and intercell interference, we formulate the resource allocation problem as a multi-objective optimization problem (MOOP), aiming to jointly maximize the uplink and downlink performances. To achieve Pareto optimal solutions, we employ the weighted Tchebycheff technique to transform the MOOP into a single-objective optimization problem (SOOP) and solve it using Successive Convex Approximation (SCA) within a Block Coordinate Descent (BCD) framework. This approach iteratively optimizes the subcarrier assignment and power control and effectively manages the trade-offs between uplink and downlink rates. The proposed method demonstrates the ability to achieve an efficient balance in resource allocation. Simulation results show that our method can obtain Pareto optimal solutions, demonstrating favorable performance trade-offs and fairness under various interference conditions, thereby improving the overall system performance in multi-UAV-assisted air-ground integrated OFDMA networks.
{"title":"Multi-objective resource allocation for UAV-assisted air-ground integrated full-duplex OFDMA networks","authors":"Tong Wang","doi":"10.1016/j.vehcom.2025.100951","DOIUrl":"10.1016/j.vehcom.2025.100951","url":null,"abstract":"<div><div>In multi-UAV-assisted air-ground integrated in-band full-duplex (IBFD) OFDMA networks, both uplink and downlink performances are critical and must be simultaneously considered. This study addresses effective resource allocation in such networks to maximize the total system uplink and downlink rates by jointly optimizing subcarrier assignment and power control. Given the significant trade-off between uplink and downlink transmissions owing to self-interference in IBFD systems and intercell interference, we formulate the resource allocation problem as a multi-objective optimization problem (MOOP), aiming to jointly maximize the uplink and downlink performances. To achieve Pareto optimal solutions, we employ the weighted Tchebycheff technique to transform the MOOP into a single-objective optimization problem (SOOP) and solve it using Successive Convex Approximation (SCA) within a Block Coordinate Descent (BCD) framework. This approach iteratively optimizes the subcarrier assignment and power control and effectively manages the trade-offs between uplink and downlink rates. The proposed method demonstrates the ability to achieve an efficient balance in resource allocation. Simulation results show that our method can obtain Pareto optimal solutions, demonstrating favorable performance trade-offs and fairness under various interference conditions, thereby improving the overall system performance in multi-UAV-assisted air-ground integrated OFDMA networks.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"55 ","pages":"Article 100951"},"PeriodicalIF":5.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-06-06DOI: 10.1016/j.vehcom.2025.100945
Peng Chen , Ting Zhou , Zhimin Chen , Fan Meng , Jun Liu
To enable the next generation of connected autonomous vehicles, the millimeter wave (mmWave)-based integrated sensing and communication (ISAC) system will be a critical technology in future vehicle-to-everything (V2X) networks. However, the rapid mobility of vehicles and the narrow beamwidth of mmWave signals present significant challenges for beam alignment, and point-target modeling methods often lead to substantial overhead, high latency, and complications. To address these issues, in this paper, a hybrid analog-digital (HAD) multi-input multi-output (MIMO) ISAC framework is adopted for the mmWave-based V2X network to reduce hardware costs and power consumption. Then, considering the narrow beamwidth of the mmWave system, the vehicle is modeled as an extended surface target with multiple scattering points, and a new association technique for these points is developed to improve prediction accuracy. Hence, a deep learning (DL)-based beamforming prediction network, namely beamforming prediction network (BFP-Net), is designed according to the ISAC signal beam prediction protocol and enables roadside units (RSUs) to transmit ISAC signals effectively for both downlink communication and sensing operations. The BFP-Net leverages a convolutional neural network long-short-term memory (CNN-LSTM) architecture to capture spatial and temporal correlations, providing enhanced modeling capabilities for beam prediction. Moreover, for highly dynamic vehicles, the BFP-Net predicts optimal beams for future time slots by extracting features from the received echo signals and eliminates the repetitive beam training inherent in the traditional communication protocol. Simulation results demonstrate that the proposed method significantly outperforms extended Kalman filter (EKF)-based methods in the mmWave V2X scenario, achieving higher beam gains and better performance for high-speed vehicles, and substantially reduces the overhead associated with beam training compared to the conventional neural network relying on pilot signals.
{"title":"BFP-Net: A DL-based ISAC beamforming prediction method for extended vehicle","authors":"Peng Chen , Ting Zhou , Zhimin Chen , Fan Meng , Jun Liu","doi":"10.1016/j.vehcom.2025.100945","DOIUrl":"10.1016/j.vehcom.2025.100945","url":null,"abstract":"<div><div>To enable the next generation of connected autonomous vehicles, the millimeter wave (mmWave)-based integrated sensing and communication (ISAC) system will be a critical technology in future vehicle-to-everything (V2X) networks. However, the rapid mobility of vehicles and the narrow beamwidth of mmWave signals present significant challenges for beam alignment, and point-target modeling methods often lead to substantial overhead, high latency, and complications. To address these issues, in this paper, a hybrid analog-digital (HAD) multi-input multi-output (MIMO) ISAC framework is adopted for the mmWave-based V2X network to reduce hardware costs and power consumption. Then, considering the narrow beamwidth of the mmWave system, the vehicle is modeled as an extended surface target with multiple scattering points, and a new association technique for these points is developed to improve prediction accuracy. Hence, a deep learning (DL)-based beamforming prediction network, namely beamforming prediction network (BFP-Net), is designed according to the ISAC signal beam prediction protocol and enables roadside units (RSUs) to transmit ISAC signals effectively for both downlink communication and sensing operations. The BFP-Net leverages a convolutional neural network long-short-term memory (CNN-LSTM) architecture to capture spatial and temporal correlations, providing enhanced modeling capabilities for beam prediction. Moreover, for highly dynamic vehicles, the BFP-Net predicts optimal beams for future time slots by extracting features from the received echo signals and eliminates the repetitive beam training inherent in the traditional communication protocol. Simulation results demonstrate that the proposed method significantly outperforms extended Kalman filter (EKF)-based methods in the mmWave V2X scenario, achieving higher beam gains and better performance for high-speed vehicles, and substantially reduces the overhead associated with beam training compared to the conventional neural network relying on pilot signals.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"55 ","pages":"Article 100945"},"PeriodicalIF":5.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-08-21DOI: 10.1016/j.vehcom.2025.100967
Tanja Pavleska , Massimiliano Masi , Giovanni Paolo Sellitto , Helder Aranha
Cooperative Intelligent Transport Systems (C-ITS) involve a complex network of diverse components that communicate with each other and with their environment. These systems are essential for improving transport efficiency, enabling smoother movement of people and goods, and supporting economic growth. However, due to their highly connected nature, C-ITS face major challenges related to cybersecurity and interoperability—both of which are directly linked to safety. Managing evolving software and standards while ensuring security places a heavy burden on architects, security experts, and organizational stakeholders.
In this work, we propose a methodology to support the secure design and deployment of C-ITS systems. The approach is based on established standards and adaptable to other critical sectors, such as healthcare, energy and smart cities, but is here tailored to the specific context of the transport domain. Our main contribution is a governance-based framework for secure deployment of standards, aimed at addressing the problem of standards maintenance, interoperability, and architectural sustainability. We demonstrate its application through a real-world use case involving secure vehicle-to-infrastructure (V2I) communication.
{"title":"Architecture-based governance for secure-by-design Cooperative Intelligent Transport Systems","authors":"Tanja Pavleska , Massimiliano Masi , Giovanni Paolo Sellitto , Helder Aranha","doi":"10.1016/j.vehcom.2025.100967","DOIUrl":"10.1016/j.vehcom.2025.100967","url":null,"abstract":"<div><div>Cooperative Intelligent Transport Systems (C-ITS) involve a complex network of diverse components that communicate with each other and with their environment. These systems are essential for improving transport efficiency, enabling smoother movement of people and goods, and supporting economic growth. However, due to their highly connected nature, C-ITS face major challenges related to cybersecurity and interoperability—both of which are directly linked to safety. Managing evolving software and standards while ensuring security places a heavy burden on architects, security experts, and organizational stakeholders.</div><div>In this work, we propose a methodology to support the secure design and deployment of C-ITS systems. The approach is based on established standards and adaptable to other critical sectors, such as healthcare, energy and smart cities, but is here tailored to the specific context of the transport domain. Our main contribution is a governance-based framework for secure deployment of standards, aimed at addressing the problem of standards maintenance, interoperability, and architectural sustainability. We demonstrate its application through a real-world use case involving secure vehicle-to-infrastructure (V2I) communication.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"55 ","pages":"Article 100967"},"PeriodicalIF":6.5,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144885569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-07-05DOI: 10.1016/j.vehcom.2025.100953
Peng Wang , Huizhi Tang , Demin Li , Yihong Zhang , Xuemin Chen
Integrated Sensing and Communication (ISAC) systems are advantageous for enhancing both communication and sensing capabilities, but their performance is significantly impacted by signal blockages in dynamic vehicular environments. An Unmanned Aerial Vehicle (UAV)-mounted Intelligent Reflective Surface (IRS) for air-to-ground communication and sensing can significantly enhance coverage and deployment flexibility. However, the additional power consumption of the UAV-mounted IRS (UIRS) remains a challenge. To mitigate this, we propose a novel UIRS-assisted ISAC system that aims to maximize communication energy efficiency (EE) while meeting sensing quality-of-service (QoS) requirements by optimizing the UAV trajectory, IRS passive beamforming, and base station (BS) active beamforming. Due to the complex and dynamic nature of wireless channels, acquiring Channel State Information (CSI) is challenging, especially with the UAV's mobility and the passive mode of IRS. Therefore, statistical CSI is adopted in the proposed scheme. The optimization problem is reformulated into a tractable form and solved by decomposing it into three subproblems, which include using the Dinkelbach transformation for fractional programming in EE calculation, Successive Convex Approximation (SCA) for UAV trajectory optimization, and Semi-Definite Relaxation (SDR) for both active and passive beamforming designs. An alternating optimization (AO)-based framework iteratively solves all subproblems, with proven algorithm convergence and computational efficiency. Simulation results demonstrate that the proposed UIRS-assisted ISAC system significantly improves both communication and sensing performance compared to benchmark schemes.
{"title":"Energy efficiency optimization for UAV-mounted IRS assisted ISAC systems under statistical CSI","authors":"Peng Wang , Huizhi Tang , Demin Li , Yihong Zhang , Xuemin Chen","doi":"10.1016/j.vehcom.2025.100953","DOIUrl":"10.1016/j.vehcom.2025.100953","url":null,"abstract":"<div><div>Integrated Sensing and Communication (ISAC) systems are advantageous for enhancing both communication and sensing capabilities, but their performance is significantly impacted by signal blockages in dynamic vehicular environments. An Unmanned Aerial Vehicle (UAV)-mounted Intelligent Reflective Surface (IRS) for air-to-ground communication and sensing can significantly enhance coverage and deployment flexibility. However, the additional power consumption of the UAV-mounted IRS (UIRS) remains a challenge. To mitigate this, we propose a novel UIRS-assisted ISAC system that aims to maximize communication energy efficiency (EE) while meeting sensing quality-of-service (QoS) requirements by optimizing the UAV trajectory, IRS passive beamforming, and base station (BS) active beamforming. Due to the complex and dynamic nature of wireless channels, acquiring Channel State Information (CSI) is challenging, especially with the UAV's mobility and the passive mode of IRS. Therefore, statistical CSI is adopted in the proposed scheme. The optimization problem is reformulated into a tractable form and solved by decomposing it into three subproblems, which include using the Dinkelbach transformation for fractional programming in EE calculation, Successive Convex Approximation (SCA) for UAV trajectory optimization, and Semi-Definite Relaxation (SDR) for both active and passive beamforming designs. An alternating optimization (AO)-based framework iteratively solves all subproblems, with proven algorithm convergence and computational efficiency. Simulation results demonstrate that the proposed UIRS-assisted ISAC system significantly improves both communication and sensing performance compared to benchmark schemes.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"55 ","pages":"Article 100953"},"PeriodicalIF":5.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01Epub Date: 2025-07-02DOI: 10.1016/j.vehcom.2025.100950
Wenjie Zhou, Tian Zhang, Zekun Lu, Linbo Zhai
As the Internet of Things (IoT) drives the development of Vehicular Edge Computing (VEC), there is a surge in computational demand from emerging in-vehicle applications. Most existing studies do not fully consider the frequent changes in network topology under high mobility of vehicles and the underutilization of idle resources by single-hop offloading. To this end, we propose a task offloading scheme for vehicular edge computing based on multi-hop offloading. The scheme allows task vehicles to offload tasks to service vehicles with excess idle resources outside the communication range, and adapts to dynamic changes in network topology by introducing the concept of neighboring vehicle connection time. This study aims to minimize the delayed energy consumption utility value of the task under the conditions of satisfying the maximum task delay limit, vehicle computational and storage resource constraints. In response to this NP-hard problem, a two-stage reinforcement learning strategy MOCDD (combining Deep Q Network (DQN) and Deep Deterministic Policy Gradient (DDPG)) is proposed to divide the mixed action space into pure discrete and pure continuous action space to determine task migration, executive decision and vehicle transmission power. Simulation results verify the effectiveness of the proposed scheme.
{"title":"Deep reinforcement learning based migration and execution decisions for multi-hop task offloading in mobile vehicle edge computing","authors":"Wenjie Zhou, Tian Zhang, Zekun Lu, Linbo Zhai","doi":"10.1016/j.vehcom.2025.100950","DOIUrl":"10.1016/j.vehcom.2025.100950","url":null,"abstract":"<div><div>As the Internet of Things (IoT) drives the development of Vehicular Edge Computing (VEC), there is a surge in computational demand from emerging in-vehicle applications. Most existing studies do not fully consider the frequent changes in network topology under high mobility of vehicles and the underutilization of idle resources by single-hop offloading. To this end, we propose a task offloading scheme for vehicular edge computing based on multi-hop offloading. The scheme allows task vehicles to offload tasks to service vehicles with excess idle resources outside the communication range, and adapts to dynamic changes in network topology by introducing the concept of neighboring vehicle connection time. This study aims to minimize the delayed energy consumption utility value of the task under the conditions of satisfying the maximum task delay limit, vehicle computational and storage resource constraints. In response to this NP-hard problem, a two-stage reinforcement learning strategy MOCDD (combining Deep Q Network (DQN) and Deep Deterministic Policy Gradient (DDPG)) is proposed to divide the mixed action space into pure discrete and pure continuous action space to determine task migration, executive decision and vehicle transmission power. Simulation results verify the effectiveness of the proposed scheme.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"55 ","pages":"Article 100950"},"PeriodicalIF":5.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-05DOI: 10.1016/j.vehcom.2025.100963
Naeem Ahmed, Farman Ali, Qingzhe Deng, Qiuming Zhu, Xiaomin Chen, Boyu Hua, Junwei Bao, Kai Mao
Unmanned aerial vehicles (UAVs) are increasingly integrated into maritime communication systems, presenting unique challenges due to complex maritime scenario. By considering six-dimensional (6D) motion of both UAV and ship alongside sea cluttering and wave shadowing phenomena, this paper presents a novel non-stationary 6D geometry-based multiple-input multiple-output (MIMO) channel model for UAV to ship (U2S) communications for maritime scenario. Besides, the dynamic interactions between UAV and ship motions and maritime environments are also described in the proposed model. The time-variant channel coefficient and channel parameters like, path loss (PL), shadow fading (SF), Doppler frequencies, wave shadowing, sea cluttering, time-variant distances, time-variant delay, time-variant power, time-variant angles, are derived and analyzed thoroughly in this proposed method. Additionally, the theoretical and statistical properties like, probability density function (PDF), autocorrelation function (ACF), level crossing rate (LCR), Doppler power spectral density (DPSD), and signal to clutter noise ratio (SCNR) are investigated with the effect of sea cluttering and wave shadowing. Finally, the validation of the channel model and its theoretical derivations highlight its suitability for evaluating and designing U2S communication systems in maritime environments. The suggested model can be useful for improving U2S communication systems, to enhance reliability and performance in maritime communication environments.
{"title":"Impact of sea cluttering and wave shadowing on U2S MIMO channel model incorporating UAV-ship 6D motion in maritime environments","authors":"Naeem Ahmed, Farman Ali, Qingzhe Deng, Qiuming Zhu, Xiaomin Chen, Boyu Hua, Junwei Bao, Kai Mao","doi":"10.1016/j.vehcom.2025.100963","DOIUrl":"https://doi.org/10.1016/j.vehcom.2025.100963","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are increasingly integrated into maritime communication systems, presenting unique challenges due to complex maritime scenario. By considering six-dimensional (6D) motion of both UAV and ship alongside sea cluttering and wave shadowing phenomena, this paper presents a novel non-stationary 6D geometry-based multiple-input multiple-output (MIMO) channel model for UAV to ship (U2S) communications for maritime scenario. Besides, the dynamic interactions between UAV and ship motions and maritime environments are also described in the proposed model. The time-variant channel coefficient and channel parameters like, path loss (PL), shadow fading (SF), Doppler frequencies, wave shadowing, sea cluttering, time-variant distances, time-variant delay, time-variant power, time-variant angles, are derived and analyzed thoroughly in this proposed method. Additionally, the theoretical and statistical properties like, probability density function (PDF), autocorrelation function (ACF), level crossing rate (LCR), Doppler power spectral density (DPSD), and signal to clutter noise ratio (SCNR) are investigated with the effect of sea cluttering and wave shadowing. Finally, the validation of the channel model and its theoretical derivations highlight its suitability for evaluating and designing U2S communication systems in maritime environments. The suggested model can be useful for improving U2S communication systems, to enhance reliability and performance in maritime communication environments.","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"14 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144900736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blockchain Networks (BCNs) have become critical in various applications, and ensuring their security against cyber threats is essential for maintaining their reliability and confidentiality. This paper investigates the crucial role of Intrusion Detection Systems (IDS) in enhancing the security of BCNs, particularly in the context of real-time vehicle monitoring. The study begins with a thorough overview of blockchain technology, highlighting key security challenges such as vulnerabilities in smart contracts, the risk of 51% attack, and regulatory compliance issues. It emphasizes the need for robust security measures, with IDS emerging as a vital defense mechanism. IDS employs advanced techniques, including signature-based detection, anomaly detection, and behavioral analysis, to monitor network traffic and user activities, thereby improving the resilience of BCNs by identifying and addressing potential threats in real-time. For real-time vehicle monitoring, IDS is essential for ensuring the integrity and security of data, preventing unauthorized access, and maintaining user trust in blockchain-enabled transportation systems. This paper provides a comprehensive analysis of IDS's role in securing blockchain networks for real-time vehicle monitoring, offering valuable insights into enhancing the security of these systems in a dynamic cyber environment.
{"title":"Blockchain-enabled intrusion detection systems for real-time vehicle monitoring","authors":"Mritunjay Shall Peelam, Vinay Chamola, Brijesh Kumar Chaurasia","doi":"10.1016/j.vehcom.2025.100961","DOIUrl":"https://doi.org/10.1016/j.vehcom.2025.100961","url":null,"abstract":"Blockchain Networks (BCNs) have become critical in various applications, and ensuring their security against cyber threats is essential for maintaining their reliability and confidentiality. This paper investigates the crucial role of Intrusion Detection Systems (IDS) in enhancing the security of BCNs, particularly in the context of real-time vehicle monitoring. The study begins with a thorough overview of blockchain technology, highlighting key security challenges such as vulnerabilities in smart contracts, the risk of 51% attack, and regulatory compliance issues. It emphasizes the need for robust security measures, with IDS emerging as a vital defense mechanism. IDS employs advanced techniques, including signature-based detection, anomaly detection, and behavioral analysis, to monitor network traffic and user activities, thereby improving the resilience of BCNs by identifying and addressing potential threats in real-time. For real-time vehicle monitoring, IDS is essential for ensuring the integrity and security of data, preventing unauthorized access, and maintaining user trust in blockchain-enabled transportation systems. This paper provides a comprehensive analysis of IDS's role in securing blockchain networks for real-time vehicle monitoring, offering valuable insights into enhancing the security of these systems in a dynamic cyber environment.","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"15 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144900737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-05-05DOI: 10.1016/j.vehcom.2025.100931
Zhiquan Bai , Runlai Wang , Yingchao Yang , Huili Hu , Jingxin Li , Xiao Zhou , Chengyou Wang , Jian Dai
With the continuous emergence of high-mobility communication scenarios, such as the Internet of Vehicles (IoV) and Vehicle to Vehicle (V2V) communications, more unique challenges have appeared in mobile communications, due to the severe Doppler frequency shift and fast time-varying channel caused by high mobility. Meanwhile, the moving speed, data volume, and quality of service are becoming more and more important in V2V communications. Providing efficient and reliable wireless communication services to high-mobility users has become a critical issue. Spatial modulation (SM) based orthogonal time frequency space (OTFS) (SM-OTFS) system can improve the reliability and effectiveness of V2V communications because of the excellent Doppler shift resistance of OTFS modulation and the low complexity of SM transmission. In this paper, considering the case that achieving perfect channel estimation is really challenging in actual situation, we derive and analyze the capacity and outage performance of the SM-OTFS system under the circumstance of ideal pulse and imperfect channel state information (CSI) based on the statistical probability and the delay-Doppler domain (DD) input-output relationship. Our theoretical analysis and derivation are approved by the numerical results. Moreover, we also demonstrate the effect of the number of resolvable multipaths, the error of channel estimation, and the different moving speeds on the performance of the SM-OTFS system in V2V communications.
{"title":"Capacity and outage analysis of SM-OTFS system with imperfect CSI in V2V communications","authors":"Zhiquan Bai , Runlai Wang , Yingchao Yang , Huili Hu , Jingxin Li , Xiao Zhou , Chengyou Wang , Jian Dai","doi":"10.1016/j.vehcom.2025.100931","DOIUrl":"10.1016/j.vehcom.2025.100931","url":null,"abstract":"<div><div>With the continuous emergence of high-mobility communication scenarios, such as the Internet of Vehicles (IoV) and Vehicle to Vehicle (V2V) communications, more unique challenges have appeared in mobile communications, due to the severe Doppler frequency shift and fast time-varying channel caused by high mobility. Meanwhile, the moving speed, data volume, and quality of service are becoming more and more important in V2V communications. Providing efficient and reliable wireless communication services to high-mobility users has become a critical issue. Spatial modulation (SM) based orthogonal time frequency space (OTFS) (SM-OTFS) system can improve the reliability and effectiveness of V2V communications because of the excellent Doppler shift resistance of OTFS modulation and the low complexity of SM transmission. In this paper, considering the case that achieving perfect channel estimation is really challenging in actual situation, we derive and analyze the capacity and outage performance of the SM-OTFS system under the circumstance of ideal pulse and imperfect channel state information (CSI) based on the statistical probability and the delay-Doppler domain (DD) input-output relationship. Our theoretical analysis and derivation are approved by the numerical results. Moreover, we also demonstrate the effect of the number of resolvable multipaths, the error of channel estimation, and the different moving speeds on the performance of the SM-OTFS system in V2V communications.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100931"},"PeriodicalIF":5.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-05-22DOI: 10.1016/j.vehcom.2025.100942
Suhui Liu , Liquan Chen , Liqun Chen , Yu Wang , Yaqing Zhu
Vehicle-to-infrastructure (V2I) communication is the basis for vehicles to obtain information about the road ahead. The confidentiality and reliability of V2I communication guarantee traffic safety and smooth flow. Authenticated key agreement (AKA) is the most commonly used technique to establish secure communication channels. Signature-based AKA inevitably exposes the identity information of vehicles, while Encryption-based AKA can bring deniability and high privacy, which means no adversary can know who sent the AKA message. Certificateless encryption (CLE) can simultaneously solve burdensome certificate management and key escrow. However, existing certificateless cryptography requires two loosely combined public keys to represent a device and does not consider the physical security of storing secret keys locally. This paper first designed an improved CLE scheme with one-device-one-public-key, and performance comparisons show that the proposed CLE has optimal storage and computation performance. Considering that rare work was put on encryption-based AKA, this paper proposed a deniable and privacy-preserving certificateless AKA for V2I communication by incorporating Physically Unclonable Function (PUF)-secured key management to prevent physical leakage of keys, named CLE-AKA-PUF. Feature comparison illustrates that CLE-AKA-PUF supports key escrow-free, dual authentication, physical security, deniability, and high privacy. Security proofs and performance analysis demonstrate the practicability and efficiency of CLE-AKA-PUF.
{"title":"CLE-based authenticated key agreement with PUF-secured key for vehicle-to-infrastructure","authors":"Suhui Liu , Liquan Chen , Liqun Chen , Yu Wang , Yaqing Zhu","doi":"10.1016/j.vehcom.2025.100942","DOIUrl":"10.1016/j.vehcom.2025.100942","url":null,"abstract":"<div><div>Vehicle-to-infrastructure (V2I) communication is the basis for vehicles to obtain information about the road ahead. The confidentiality and reliability of V2I communication guarantee traffic safety and smooth flow. Authenticated key agreement (AKA) is the most commonly used technique to establish secure communication channels. Signature-based AKA inevitably exposes the identity information of vehicles, while Encryption-based AKA can bring deniability and high privacy, which means no adversary can know who sent the AKA message. Certificateless encryption (CLE) can simultaneously solve burdensome certificate management and key escrow. However, existing certificateless cryptography requires two loosely combined public keys to represent a device and does not consider the physical security of storing secret keys locally. This paper first designed an improved CLE scheme with one-device-one-public-key, and performance comparisons show that the proposed CLE has optimal storage and computation performance. Considering that rare work was put on encryption-based AKA, this paper proposed a deniable and privacy-preserving certificateless AKA for V2I communication by incorporating Physically Unclonable Function (PUF)-secured key management to prevent physical leakage of keys, named CLE-AKA-PUF. Feature comparison illustrates that CLE-AKA-PUF supports key escrow-free, dual authentication, physical security, deniability, and high privacy. Security proofs and performance analysis demonstrate the practicability and efficiency of CLE-AKA-PUF.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100942"},"PeriodicalIF":5.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-04-24DOI: 10.1016/j.vehcom.2025.100928
M. Ajin, R.S. Shaji
Currently, the use of Vehicular Ad-Hoc Networks (VANETs) has gained significant attention in toll management systems and traffic control. VANETs facilitate effective communication by connecting Roadside Units (RSUs) and vehicles. VANETs can ease decision-making for drivers, meanwhile, they carry some problems with security since they often modify topology. In VANET, the Sybil attack is a specific attack, that might generate traffic congestion and affect transportation safety services. Different Mechanisms have been implemented to discover various attacks in VANET, yet VANET meets diverse attacks. Therefore, this research article developed an effective Sybil attack detection model namely Adaptive Bald Eagle Search Optimization (ABESO) based Multi-agent-Deep Q Neural network (MA-DQN). The principal objective of the ABESO based DQN is to enhance the security level of VANET by identifying the Sybil Attacks. In this, clustering and effective cluster head selection are performed to discover the Sybil attacks. In the suggested ABESO based DQN algorithm, robust clustering is carried out, in which vehicle nodes of VANET are clustered through the utilization of the BIRCH clustering technique. Our proposed ABESO based DQN algorithm augments the overall network efficiency by effective cluster head selection. Taylor-based Waterwheel Plant (TWP) is exploited in the cluster head selection and diminishes the overhead in the network. In the proposed model, the MDQN-based approach selects the features and ABESO based DQN delivers an optimal output, i.e., it discovers normal and Sybil attacks. Experimental results are carried out on the basis of the sybil attack detection dataset that holds multiple data regarding attacks. The detection results affirm that the efficiency of the proposed ABESO based DQN approach is superior and outperformed previous methods.
{"title":"Enhancing security in vanets: Adaptive Bald Eagle Search Optimization based multi-agent deep Q neural network for Sybil attack detection","authors":"M. Ajin, R.S. Shaji","doi":"10.1016/j.vehcom.2025.100928","DOIUrl":"10.1016/j.vehcom.2025.100928","url":null,"abstract":"<div><div>Currently, the use of Vehicular Ad-Hoc Networks (VANETs) has gained significant attention in toll management systems and traffic control. VANETs facilitate effective communication by connecting Roadside Units (RSUs) and vehicles. VANETs can ease decision-making for drivers, meanwhile, they carry some problems with security since they often modify topology. In VANET, the Sybil attack is a specific attack, that might generate traffic congestion and affect transportation safety services. Different Mechanisms have been implemented to discover various attacks in VANET, yet VANET meets diverse attacks. Therefore, this research article developed an effective Sybil attack detection model namely Adaptive Bald Eagle Search Optimization (ABESO) based Multi-agent-Deep Q Neural network (MA-DQN). The principal objective of the ABESO based DQN is to enhance the security level of VANET by identifying the Sybil Attacks. In this, clustering and effective cluster head selection are performed to discover the Sybil attacks. In the suggested ABESO based DQN algorithm, robust clustering is carried out, in which vehicle nodes of VANET are clustered through the utilization of the BIRCH clustering technique. Our proposed ABESO based DQN algorithm augments the overall network efficiency by effective cluster head selection. Taylor-based Waterwheel Plant (TWP) is exploited in the cluster head selection and diminishes the overhead in the network. In the proposed model, the MDQN-based approach selects the features and ABESO based DQN delivers an optimal output, i.e., it discovers normal and Sybil attacks. Experimental results are carried out on the basis of the sybil attack detection dataset that holds multiple data regarding attacks. The detection results affirm that the efficiency of the proposed ABESO based DQN approach is superior and outperformed previous methods.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100928"},"PeriodicalIF":5.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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