Vehicular Communications最新文献_第8页

A privacy-preserving access control protocol for 6G supported intelligent UAV networks 一种支持6G的智能无人机网络隐私保护访问控制协议

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-14 DOI: 10.1016/j.vehcom.2025.100937

Khalid Mahmood , Salman Shamshad , Mohammad Hossein Anisi , Alessandro Brighente , Muhammad Asad Saleem , Ashok Kumar Das

Due to their autonomous operation, high mobility, and real-time communication capabilities, 6G-supported Unmanned Aerial Vehicles (6G-UAVs) (i.e., drones) are increasingly being utilized to enhance data collection and management in Intelligent Transportation Systems (ITSs). Despite their manifold benefits, 6G-supported UAV-based ITS (6G-U-ITS) faces unique security challenges beyond conventional cyber and physical threats. These include real-time authentication, impersonation attacks, physical tampering or cloning and protection against identity spoofing in highly dynamic environments. For instance, an attacker may steal a drone and use its identity to send authenticated malicious messages to the ITS, causing road accidents. Therefore, a secure authentication scheme must ensure resilience against UAV identity theft and unauthorized access while maintaining low-latency and computational efficiency to support the stringent real-time security requirements of 6G-U-ITS. Existing authentication schemes are not specifically designed to address these challenges, making it imperative to develop a lightweight and robust authentication mechanism tailored for 6G-U-ITS. Moreover, most of the existing protocols are vulnerable to physical tampering and impersonation attacks and also require high computation overhead. In this paper, to mitigate these limitations and satisfy the aforementioned requirements, we propose a secure access control protocol for 6G-U-ITS. To the best of our knowledge, this is the first security solution in the literature that can achieve security against UAVs physical attacks. Furthermore, we justify the robustness of the designed protocol against potential attacks through detailed formal and informal security assessment. Via testbed experiments, we show that our protocol achieves 20.66% and 22.82% higher efficiency on communication and computation overhead, respectively, compared to other contemporary competing protocols.

由于其自主操作、高机动性和实时通信能力，6g支持的无人机（即无人机）越来越多地用于增强智能交通系统（ITSs）的数据收集和管理。尽管具有多方面的优势，但6g支持的基于无人机的ITS （6G-U-ITS）面临着传统网络和物理威胁之外的独特安全挑战。这包括实时身份验证、模拟攻击、物理篡改或克隆，以及在高度动态环境中防止身份欺骗。例如，攻击者可能会窃取无人机，并使用其身份向its发送经过身份验证的恶意信息，从而导致交通事故。因此，一个安全的认证方案必须确保对无人机身份盗窃和未经授权访问的弹性，同时保持低延迟和计算效率，以支持6G-U-ITS严格的实时安全要求。现有的身份验证方案并不是专门为解决这些挑战而设计的，因此必须为6G-U-ITS开发一种轻量级且健壮的身份验证机制。此外，大多数现有协议容易受到物理篡改和模拟攻击，并且需要很高的计算开销。在本文中，为了减轻这些限制并满足上述要求，我们提出了一种6G-U-ITS的安全访问控制协议。据我们所知，这是文献中第一个可以实现针对无人机物理攻击的安全解决方案。此外，我们通过详细的正式和非正式的安全评估来证明所设计的协议对潜在攻击的鲁棒性。通过测试实验，我们的协议在通信和计算开销方面分别比其他当代竞争协议提高了20.66%和22.82%。

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引用次数: 0

EGBCR-FANET: Enhanced genghis Khan shark optimizer based Bayesian-driven clustered routing model for FANETs EGBCR-FANET：基于增强成吉思汗鲨鱼优化器的贝叶斯驱动的fanet聚类路由模型

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-13 DOI: 10.1016/j.vehcom.2025.100935

Reham R. Mostafa , Dilna Vijayan , Ahmed M. Khedr

Unmanned Aerial Vehicle (UAV) technology has advanced rapidly, with broad use in both the military and commercial sectors. As a result, multi-UAV networks, also known as Flying Ad Hoc Networks (FANETs), have become a vital part of current communication systems. However, FANETs confront numerous challenges such as limited energy resources, high mobility, frequent topological changes, and inconsistent communication links. These difficulties influence network stability, limit data transmission efficiency, and shorten network longevity. Addressing these issues requires an adaptable routing strategy in FANETs. Cluster-based routing in UAVs is a great way to save energy, increase scalability, and improve network performance. This paper introduces a new clustering and routing framework for FANETs based on the Enhanced Genghis Khan Shark Optimizer (EGKSO). Unlike previous clustering approaches, the suggested solution dynamically selects the appropriate number of clusters while taking node coverage and network bandwidth into account. EGKSO is used to choose energy-efficient and stable cluster heads, resulting in balanced load distribution and a longer network lifetime. A dynamic cluster maintenance technique is proposed to ensure network stability and maintain efficient communication performance. In addition, a Bayesian-inspired next-hop selection model for adaptive routing is presented, allowing probabilistic decision-making to respond to network changes efficiently. This combination of swarm intelligence and probabilistic modeling improves communication reliability, reduces latency, and maximizes energy efficiency. The simulation results show that the suggested method outperforms existing clustering and routing protocols in terms of delivery ratio, energy consumption, latency, and clustering stability. The results demonstrate the efficacy of combining metaheuristic-based clustering with Bayesian-inspired routing, providing a resilient and scalable solution for FANETs in dynamic and resource-constrained contexts.

无人机（UAV）技术发展迅速，在军事和商业领域都有广泛的应用。结果，多无人机网络，也被称为飞行自组织网络（fanet），已经成为当前通信系统的一个重要部分。然而，fanet面临着能源资源有限、移动性高、拓扑变化频繁、通信链路不一致等诸多挑战。这些困难影响网络的稳定性，限制数据传输效率，缩短网络寿命。解决这些问题需要在fanet中采用适应性强的路由策略。无人机中基于集群的路由是一种节省能源、增加可扩展性和提高网络性能的好方法。介绍了一种基于增强型成吉思汗鲨鱼优化器（EGKSO）的fanet聚类和路由框架。与以前的聚类方法不同，建议的解决方案在考虑节点覆盖率和网络带宽的同时动态选择适当数量的集群。利用EGKSO算法选择节能且稳定的簇头，实现负载均衡分配，延长网络寿命。为了保证网络的稳定性和保持高效的通信性能，提出了一种动态集群维护技术。此外，提出了一种贝叶斯启发的自适应路由下一跳选择模型，使概率决策能够有效地响应网络变化。这种群体智能和概率建模的结合提高了通信可靠性，减少了延迟，并最大化了能源效率。仿真结果表明，该方法在投递率、能耗、时延和聚类稳定性等方面都优于现有的聚类和路由协议。结果证明了将基于元启发式的聚类与贝叶斯启发的路由相结合的有效性，为动态和资源受限环境下的fanet提供了弹性和可扩展的解决方案。

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引用次数: 0

Geometric Optimisation of Unmanned Aerial Vehicle Trajectories in Uncertain Environments 不确定环境下无人机轨迹几何优化

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-12 DOI: 10.1016/j.vehcom.2025.100938

J Akshya , M Sundarrajan , S. Amutha , Rajesh Kumar Dhanaraj , Adil O. Khadidos , Alaa O. Khadidos , Shitharth Selvarajan

The problem of efficient trajectory optimisation for Unmanned Aerial Vehicles (UAVS) in dynamic and constrained environments is one where energy efficiency, spatial coverage, and path smoothness need to be balanced. The existing methods, namely RRT*, A*, and Dijkstra, are popular but generally heuristic and do not provide globally optimal solutions. They face significant limitations while dealing with complex geometries, dynamic obstacles, and multi-objective requirements. These challenges call for a mathematically sound framework that seamlessly integrates convex analysis and computational geometry to provide an optimal trajectory planning framework. This research work introduces a convex optimisation framework for UAV trajectory planning which unifies multiple objectives, like minimising energy consumption, maximising spatial coverage, and ensuring the smoothness of the path, into a single convex objective function. More importantly, it indicates that obstacle dynamics and uncertain environmental conditions are handled better by it, so it is relatively easier for safe and efficient navigation. Proven to converge faster and with higher precision than RRT*, A*, and Dijkstra, the approach proposed here enjoys intrinsic convex properties, which ensure global optimality. Qualitative measurements show the efficiency of the proposed framework. The result is energy efficiency of 90%, with 92% coverage, 98% constraint satisfaction, and 95% path smoothness, which is 15-25% better on all metrics than traditional approaches can offer. By bridging between theory in convex optimisation and practice for solving multi-objective problems in a dynamic setting, this study provides a more robust solution for UAV trajectory planning.

在动态和受限环境下，无人机（UAVS）的有效轨迹优化问题是一个需要平衡能源效率、空间覆盖和路径平滑的问题。现有的方法，即RRT*， A*和Dijkstra，是流行的，但通常是启发式的，不能提供全局最优解。在处理复杂的几何形状、动态障碍物和多目标要求时，它们面临着显著的局限性。这些挑战需要一个数学上合理的框架，无缝集成凸分析和计算几何，以提供最佳的轨迹规划框架。本研究提出了一种用于无人机轨迹规划的凸优化框架，该框架将能量消耗最小化、空间覆盖最大化、路径平滑度最大化等多个目标统一为单个凸目标函数。更重要的是，它能更好地处理障碍物动态和不确定的环境条件，相对容易实现安全高效的导航。与RRT*， A*和Dijkstra相比，本文提出的方法收敛速度更快，精度更高，具有内在的凸性，确保了全局最优性。定性测量表明了该框架的有效性。结果是90%的能源效率，92%的覆盖率，98%的约束满意度和95%的路径平滑度，在所有指标上都比传统方法好15-25%。通过将求解动态环境下多目标问题的凸优化理论与实践相结合，本研究为无人机的轨迹规划提供了更为鲁棒的解决方案。

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引用次数: 0

Rigid communication topologies: Impact on stability, safety, energy consumption, passenger comfort, and robustness of vehicular platoons 刚性通信拓扑：对车辆队列稳定性、安全性、能耗、乘客舒适度和鲁棒性的影响

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-12 DOI: 10.1016/j.vehcom.2025.100936

Amir Zakerimanesh , Tony Zhijun Qiu , Mahdi Tavakoli

This paper investigates the impact of rigid communication topologies (RCTs) on the performance of vehicular platoons, aiming to identify beneficial features in RCTs that enhance vehicles behavior. Four performance metrics are introduced, focusing on safety, energy consumption, passenger comfort, and robustness of vehicular platoons. The safety metric is based on momentary distances between neighboring vehicles, their relative velocities, and relative accelerations. Thus, to have access to these relative values, the coupled dynamics between pairs of neighboring vehicles are formulated, considering initial conditions (position, velocity, acceleration), the velocity/acceleration trajectory of the leader vehicle, deployed RCT, and the parity/disparity between vehicles. By decoupling the dynamics using a mapping matrix structured on deployed RCT, the features of the vehicles, and control gains, precise formulations for distance errors, relative velocities, and relative accelerations between all neighboring vehicles, over the travel time, are obtained. Comparing performance metric results across RCTs highlights that downstream information transmission—from vehicles ahead, particularly the leader vehicle, to vehicles behind—significantly enhances platoon stability, safety, energy consumption, and passenger comfort metrics. Conversely, receiving state information from vehicles behind degrades metrics, compromising safety, increasing energy consumption, and reducing passenger comfort. These findings underscore that forward-looking, leader-centric communications between vehicles markedly enhance platoon efficiency and safety.

本文研究了刚性通信拓扑（rct）对车辆队列性能的影响，旨在识别rct中增强车辆行为的有益特征。介绍了四个性能指标，重点是安全性、能耗、乘客舒适度和车辆队列的鲁棒性。安全度量是基于相邻车辆之间的瞬时距离、它们的相对速度和相对加速度。因此，为了获得这些相对值，考虑初始条件（位置、速度、加速度）、领先车辆的速度/加速度轨迹、部署RCT以及车辆之间的宇称/视差，制定了相邻车辆对之间的耦合动力学。通过使用基于部署RCT的映射矩阵解耦动力学、车辆特征和控制增益，获得了所有相邻车辆在行驶时间内的距离误差、相对速度和相对加速度的精确公式。对比rct的性能指标结果可以发现，下游信息传输——从前车，特别是领先车辆，到后车——显著提高了车队的稳定性、安全性、能耗和乘客舒适度指标。相反，从后面的车辆接收状态信息会降低指标，影响安全性，增加能源消耗，降低乘客舒适度。这些发现强调，车辆之间前瞻性的、以领导者为中心的通信显著提高了排的效率和安全性。

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引用次数: 0

An optimal transmit power allocation scheme using UAV position estimation in MmWave NTNs 基于无人机位置估计的毫米波ntn发射功率优化分配方案

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-08 DOI: 10.1016/j.vehcom.2025.100934

Pawan Srivastava, M.P.R.S. Kiran

Non-terrestrial networks (NTNs) typically consist of UAV swarms equipped with multiple sensors that generate massive data, requiring real-time communication to a gateway for further processing. Hence, millimeter-wave (mmWave) communication technologies operating above 24 GHz emerge as a suitable solution for enabling high-speed intra-UAV swarm communication. However, mmWave communication technologies use multiple antenna-based directional beamforming for improved coverage, which leads to higher power consumption and frequent beam training overhead, affecting swarm endurance. To address this, we propose a novel optimal transmit power allocation scheme that enhances swarm endurance and improves throughput by reducing beam training overhead. Firstly, the proposed scheme uses the Kalman filter (in this paper, but not limited to) at the transmitting UAV to estimate the real-time position of the receiving UAV. The estimated position is utilized to calculate path loss and select the optimal transmit power level needed to meet the required received signal power threshold at the receiving UAV. To reduce outages from errors in UAV position estimation, the proposed scheme also adjusts the transmit power level by incorporating an additional buffer distance around the estimated position, thereby enhancing reliability with a minimal increase in transmit power. The performance analysis shows that the proposed scheme achieves an average reliability of more than 99% and power savings of up to 49.4% while increasing the throughput under saturated traffic conditions, thus establishing its effectiveness in mobile UAV swarms. Also, the proposed scheme is compared with three popular mechanisms existing in the literature: 1) baseline approach where constant transmit power is utilized, 2) deep learning (long short-term memory, LSTM) based transmit power allocation, and 3) power allocation using

α - β - γ

filter for receiving UAV position estimation. The performance comparison shows that the proposed scheme offers superior performance in terms of power savings, reliability, throughput, and computational complexity.

非地面网络（NTNs）通常由配备有产生大量数据的多个传感器的无人机群组成，需要与网关进行实时通信以进行进一步处理。因此，工作在24 GHz以上的毫米波（mmWave）通信技术成为实现高速无人机群通信的合适解决方案。然而，毫米波通信技术使用基于多个天线的定向波束形成来提高覆盖范围，这会导致更高的功耗和频繁的波束训练开销，影响群的续航能力。为了解决这个问题，我们提出了一种新的最优发射功率分配方案，通过减少波束训练开销来提高群耐力和吞吐量。首先，该方案在发射无人机上使用卡尔曼滤波器（本文但不限于）来估计接收无人机的实时位置。利用估计位置计算路径损耗，选择满足接收无人机所需接收信号功率阈值所需的最优发射功率电平。为了减少无人机位置估计误差造成的中断，该方案还通过在估计位置周围加入额外的缓冲距离来调整发射功率水平，从而在最小的发射功率增加下提高可靠性。性能分析表明，在饱和交通条件下，该方案在提高吞吐量的同时实现了99%以上的平均可靠性和49.4%的节能，从而确立了其在移动无人机群中的有效性。此外，该方案还与文献中存在的三种流行机制进行了比较：1)使用恒定发射功率的基线方法，2)基于深度学习（长短期记忆，LSTM）的发射功率分配，以及3)使用α - β - γ滤波器接收无人机位置估计的功率分配。性能比较表明，该方案在节能、可靠性、吞吐量和计算复杂度等方面具有较好的性能。

{"title":"An optimal transmit power allocation scheme using UAV position estimation in MmWave NTNs","authors":"Pawan Srivastava, M.P.R.S. Kiran","doi":"10.1016/j.vehcom.2025.100934","DOIUrl":"10.1016/j.vehcom.2025.100934","url":null,"abstract":"<div><div>Non-terrestrial networks (NTNs) typically consist of UAV swarms equipped with multiple sensors that generate massive data, requiring real-time communication to a gateway for further processing. Hence, millimeter-wave (mmWave) communication technologies operating above 24 GHz emerge as a suitable solution for enabling high-speed intra-UAV swarm communication. However, mmWave communication technologies use multiple antenna-based directional beamforming for improved coverage, which leads to higher power consumption and frequent beam training overhead, affecting swarm endurance. To address this, we propose a novel optimal transmit power allocation scheme that enhances swarm endurance and improves throughput by reducing beam training overhead. Firstly, the proposed scheme uses the Kalman filter (in this paper, but not limited to) at the transmitting UAV to estimate the real-time position of the receiving UAV. The estimated position is utilized to calculate path loss and select the optimal transmit power level needed to meet the required received signal power threshold at the receiving UAV. To reduce outages from errors in UAV position estimation, the proposed scheme also adjusts the transmit power level by incorporating an additional buffer distance around the estimated position, thereby enhancing reliability with a minimal increase in transmit power. The performance analysis shows that the proposed scheme achieves an average reliability of more than 99% and power savings of up to 49.4% while increasing the throughput under saturated traffic conditions, thus establishing its effectiveness in mobile UAV swarms. Also, the proposed scheme is compared with three popular mechanisms existing in the literature: 1) baseline approach where constant transmit power is utilized, 2) deep learning (long short-term memory, LSTM) based transmit power allocation, and 3) power allocation using <span><math><mi>α</mi><mo>−</mo><mi>β</mi><mo>−</mo><mi>γ</mi></math></span> filter for receiving UAV position estimation. The performance comparison shows that the proposed scheme offers superior performance in terms of power savings, reliability, throughput, and computational complexity.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"54 ","pages":"Article 100934"},"PeriodicalIF":5.8,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941755","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}

引用次数: 0

DAME-IoV: Dynamic Adaptive Multi-Edge authentication protocol with post-quantum security for Internet of Vehicles 基于后量子安全的车联网动态自适应多边缘认证协议

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-07 DOI: 10.1016/j.vehcom.2025.100933

Iftikhar Rasheed , Hala Mostafa

The Internet of Vehicles (IoV) faces increasing security challenges with the advent of quantum computing, which threatens traditional cryptographic protocols while demanding efficient authentication mechanisms for large-scale vehicle networks. This paper presents DAME-IoV, a Dynamic Adaptive Multi-Edge authentication protocol that provides post-quantum security while leveraging edge computing capabilities for enhanced performance. Our framework introduces three key innovations: (1) a lightweight post-quantum authentication scheme optimized for vehicular networks, featuring lattice-based cryptography with dynamic parameter adjustment; (2) an adaptive security mechanism that dynamically adjusts protection levels based on real-time threat assessment and resource availability; and (3) an efficient edge-assisted processing architecture that enables scalable authentication through intelligent caching and batch verification. We provide formal security proofs demonstrating the protocol's resistance to quantum attacks while maintaining conditional privacy preservation. Extensive experimental evaluation on a prototype implementation shows that DAME-IoV achieves 45% lower computational overhead, 35% reduced memory footprint, and 40% better scaling efficiency compared to existing solutions. Performance analysis under various network conditions demonstrates that our framework maintains authentication latency below 50 ms while supporting over 1000 concurrent vehicle requests. The proposed solution successfully addresses the critical challenges of post-quantum security, scalability, and efficiency in IoV environments, providing a practical foundation for securing next-generation vehicular networks.

随着量子计算的出现，车联网（IoV）面临着越来越大的安全挑战，这对传统的加密协议构成了威胁，同时也需要大规模车辆网络的高效认证机制。本文介绍了DAME-IoV，这是一种动态自适应多边缘认证协议，在利用边缘计算能力增强性能的同时提供后量子安全。我们的框架引入了三个关键创新：(1)针对车载网络优化的轻量级后量子认证方案，具有基于格的动态参数调整加密；(2)基于实时威胁评估和资源可用性动态调整防护等级的自适应安全机制；(3)高效的边缘辅助处理架构，通过智能缓存和批量验证实现可扩展的身份验证。我们提供了正式的安全证明，证明了该协议对量子攻击的抵抗力，同时保持了有条件的隐私保护。对原型实现的广泛实验评估表明，与现有解决方案相比，DAME-IoV的计算开销降低了45%，内存占用减少了35%，扩展效率提高了40%。在各种网络条件下的性能分析表明，我们的框架在支持超过1000个并发车辆请求的同时，将身份验证延迟保持在50毫秒以下。该解决方案成功解决了车联网环境中后量子安全、可扩展性和效率方面的关键挑战，为确保下一代汽车网络的安全提供了实践基础。

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引用次数: 0

Capacity and outage analysis of SM-OTFS system with imperfect CSI in V2V communications V2V通信中CSI不完善的SM-OTFS系统容量及中断分析

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-05 DOI: 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.

随着车联网（IoV）、车对车通信（V2V）等高移动性通信场景的不断出现，高移动性带来的多普勒频移严重、信道时变快，给移动通信带来了更多独特的挑战。同时，移动速度、数据量和服务质量在V2V通信中变得越来越重要。为高移动性用户提供高效、可靠的无线通信服务已成为一个关键问题。基于空间调制（SM）的正交时频空间（OTFS）（SM-OTFS）系统由于OTFS调制具有良好的抗多普勒频移性能和较低的传输复杂度，可以提高V2V通信的可靠性和有效性。考虑到在实际情况中实现完美信道估计的难度较大，本文基于统计概率和时延-多普勒域（DD）输入输出关系，推导并分析了理想脉冲和不完全信道状态信息（CSI）情况下SM-OTFS系统的容量和中断性能。我们的理论分析和推导得到了数值结果的验证。此外，我们还演示了可解析多径数量、信道估计误差和不同移动速度对SM-OTFS系统在V2V通信中的性能的影响。

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引用次数: 0

Beamforming design and trajectory optimization for integrated sensing and communication supported by multiple UAVs based on DRL 基于DRL的多无人机集成传感与通信波束形成设计与轨迹优化

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-05-05 DOI: 10.1016/j.vehcom.2025.100932

Zekun Lu, Linbo Zhai, Wenjie Zhou, Kai Xue, Xingxia Gao

With the rapid development of Unmanned aerial vehicle (UAV) technology and the high flexibility and maneuverability of UAV itself, UAV will play a very important role in the development of integrated sensing and communication (ISAC) in the future. In this paper, the communication and sensing system supported by multiple UAVs is studied. And we propose a new ISAC balance mode (BISAC). In this mode, the sensing time is set reasonably according to the number of potential targets (PTs) and sensing requirements while the UAV is communicating with ground equipment (GEs), so as to reduce the interaction between communication and sensing and improve the utilization of resources. We also introduce the Age of Information (AoI) to measure the freshness of GEs' data information in order to reduce the delay. Therefore, our goal is to minimize the Average AoI of GEs by jointly optimizing UAV trajectory, user association, target sensing selection and communication and sensing beamforming while maintaining communication quality and sensing requirements. In order to obtain long-term AoI performance and effectively solve non-convex problems with continuous and discrete variables, we propose a deep reinforcement learning (DRL) algorithm based on a combination of deep deterministic policy gradient (DDPG) and Dueling Double Deep Q networks (D3QN). Continuous and discrete variables in the system are processed by invoking a DDPG and D3QN. Specifically, we have improved DDPG's actor-critic structure by incorporating D3QN, which utilizes the actor portion of DDPG to search for optimal communication and sensing beams. At the same time, the critic part of DDPG is combined with D3QN to select the optimal flight direction of UAV. Simulation results show that the proposed DDPG-D3QN algorithm has better stability, faster convergence rate, and higher reward than existing DRL-based methods.

随着无人机（UAV）技术的快速发展和无人机本身的高灵活性和机动性，无人机将在未来集成传感与通信（ISAC）的发展中发挥非常重要的作用。本文研究了多架无人机支持的通信与传感系统。提出了一种新的ISAC平衡模式（BISAC）。该模式在无人机与地面设备通信时，根据潜在目标数量和传感需求合理设置传感时间，减少通信与传感之间的交互，提高资源利用率。为了减少延迟，我们还引入了信息时代（Age of Information, AoI）来度量ge数据信息的新鲜度。因此，我们的目标是在保持通信质量和传感要求的前提下，通过联合优化无人机轨迹、用户关联、目标传感选择以及通信和传感波束形成，使GEs的平均AoI最小化。为了获得长期的AoI性能并有效解决连续变量和离散变量的非凸问题，我们提出了一种基于深度确定性策略梯度（DDPG）和Dueling Double deep Q网络（D3QN）相结合的深度强化学习（DRL）算法。通过调用DDPG和D3QN来处理系统中的连续变量和离散变量。具体来说，我们通过加入D3QN改进了DDPG的actor-critic结构，D3QN利用DDPG的actor部分来搜索最佳的通信和传感波束。同时，将DDPG的关键部分与D3QN相结合，选择无人机的最优飞行方向。仿真结果表明，与现有基于drl的算法相比，本文提出的DDPG-D3QN算法具有更好的稳定性、更快的收敛速度和更高的奖励。

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引用次数: 0

On the performance of a UAV-based Malaga-distributed FSO/FSO communication system with NOMA 基于NOMA的无人机马拉加分布式FSO/FSO通信系统性能研究

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-04-29 DOI: 10.1016/j.vehcom.2025.100930

Aanchal Gupta , Divya Dhawan , Neena Gupta , Hemani Kaushal

Non-Orthogonal Multiple Access (NOMA) is an efficient communication technique that can offer improved spectral efficiency, ultra-low latency and massive connectivity and its integration with Free Space Optical (FSO) communication can improve the network capacity to a great extent. In this manuscript, an Unmanned Aerial Vehicle (UAV) is employed as a relay in an FSO/FSO downlink network, comprising of two users, user 1, U1 and user 2, U2, using Amplify-and-Forward (AF) protocol. UAVs can prove to be assets in disaster-struck situations (during natural disasters such as earthquakes, floods, etc.), when all terrestrial communication is at halt. The performance of this system is determined in the presence of atmospheric attenuation, Malaga (

M

) turbulence fading, pointing errors and Angle-of-Arrival (AoA) fluctuations. Heterodyne detection (HD) technique is used for information detection at the users for providing improved sensitivity and Signal-to-Noise Ratio (SNR). The closed-form expressions for Outage Probability (OP), Ergodic Capacity and Bit Error Rate (BER) are derived in terms of Meijer-G function and OP is analyzed with respect to different weather conditions, turbulence levels, pointing error coefficients, NOMA coefficients and Field-of-View (FoV) angles. It is observed that at an SNR of 0 dB, the outage at U1 and U2 is 0.5489 and 0.7423, respectively. A comparison of OP is presented for the cases of HD and Intensity Modulation/Direct Detection (IM/DD) techniques and for NOMA and Orthogonal Multiple Access (OMA) technologies. Ergodic Capacity is analyzed for different turbulence strengths and pointing error values and it can be noticed that it is enhanced by reducing the turbulence strength and pointing error impairment. BER is observed for different modulation schemes and it is found to be

7.7 \times 10^{- 3}

,

1.9 \times 10^{- 2}

,

7.9 \times 10^{- 2}

and

2.8 \times 10^{- 2}

, for QPSK, 8-PSK, 16-PSK and 16-QAM, respectively, at an SNR of 30 dB. In addition, BER is analyzed for clear, rainy and foggy weather along with different pointing errors and turbulence regimes. Monte-Carlo simulations are also carried out in order to validate the correctness of the obtained analytical results.

非正交多址（NOMA）是一种高效的通信技术，能够提供更高的频谱效率、超低延迟和海量连接，它与自由空间光通信（FSO）相结合，可以在很大程度上提高网络容量。在本文中，使用一架无人机（UAV）作为FSO/FSO下行网络中的中继，该网络由两个用户组成，用户1 U1和用户2 U2，使用放大转发（AF）协议。在所有地面通信中断的情况下，无人机可以被证明是灾害袭击的资产（在地震、洪水等自然灾害期间）。该系统的性能是在大气衰减、马拉加(M)湍流衰落、指向误差和到达角（AoA）波动的情况下确定的。外差检测（HD）技术用于用户处的信息检测，以提高灵敏度和信噪比。用Meijer-G函数导出了停运概率（OP）、遍历容量（Ergodic Capacity）和误码率（BER）的封闭表达式，并分析了OP在不同天气条件、湍流程度、指向误差系数、NOMA系数和视场角（FoV）的影响。可以观察到，在信噪比为0 dB时，U1和U2的中断分别为0.5489和0.7423。比较了高清和强度调制/直接检测（IM/DD）技术以及NOMA和正交多址（OMA）技术的OP。分析了不同湍流强度和指向误差值下的遍历能力，发现减小湍流强度和指向误差值可以提高遍历能力。在30 dB的信噪比下，QPSK、8-PSK、16-PSK和16-QAM的误码率分别为7.7×10−3、1.9×10−2、7.9×10−2和2.8×10−2。此外，还分析了晴空、雨天和雾天以及不同指向误差和湍流状态下的误码率。为了验证所得分析结果的正确性，还进行了蒙特卡罗仿真。

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引用次数: 0

A QoS-aware adaptive cross-layer cyber-attack detection algorithm for vehicular networks 一种基于qos感知的自适应跨层网络攻击检测算法

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications

Pub Date : 2025-04-28 DOI: 10.1016/j.vehcom.2025.100929

Avneet Kaur , Makhduma F. Saiyed , Irfan Al-Anbagi , M. Shamim Hossain

Securing data transmission and detecting cyber-attacks in consumer Vehicular Ad hoc Networks (VANETs) pose significant challenges due to the highly dynamic topology of the network and frequent mobility of nodes. These characteristics enable attackers to exploit vulnerabilities and evade detection, making real-time attack detection complex while maintaining the Quality of Service (QoS). In this paper, we propose an Adaptive Cross-layer Cyber-attack Detection (ACCD) algorithm that dynamically detects and isolates malicious nodes while optimizing traffic routing based on application-specific requirements. The proposed algorithm uses a cross-layer traffic-aware approach to classify data flows into security-critical and delay-sensitive applications, ensuring optimal routing through the selection of Ant Colony Optimization (ACO) and Ad hoc On-Demand Multipath Distance Vector (AOMDV) protocols. The integration of pre-route authentication (PRA) enhances malicious node isolation, reducing the impact of selective forwarding and blocking attacks. Simulation results show that ACCD achieves lower end-to-end delay and higher Packet Delivery Ratio (PDR) while effectively balancing network security and performance.

由于网络的高度动态拓扑结构和节点的频繁移动，消费者车辆自组织网络（VANETs）中的数据传输安全和网络攻击检测面临着重大挑战。这些特征使攻击者能够利用漏洞并逃避检测，使实时攻击检测变得复杂，同时保持服务质量（QoS）。在本文中，我们提出了一种自适应跨层网络攻击检测（ACCD）算法，该算法可以动态检测和隔离恶意节点，同时根据特定应用需求优化流量路由。该算法采用跨层流量感知方法将数据流划分为安全关键型和延迟敏感型应用，通过选择蚁群优化（ACO）和Ad hoc按需多路径距离矢量（AOMDV）协议确保最优路由。集成了PRA (pre-route authentication)，增强了对恶意节点的隔离，减少了选择性转发和阻断攻击的影响。仿真结果表明，ACCD在有效平衡网络安全和性能的同时，实现了更低的端到端时延和更高的包投递率（PDR）。

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引用次数: 0