车联网泛在感知、潜在通信、融合计算、内生安全综述：最新进展与未来方向

于刊; 李东; 张奇勋; 马丁友; 冯志勇; 禹继国

doi:10.11959/j.issn.1000-436x.2024153

您当前的位置：

首页 >

文章列表页 >

车联网泛在感知、潜在通信、融合计算、内生安全综述：最新进展与未来方向

综述 | 更新时间：2024-12-24

- 车联网泛在感知、潜在通信、融合计算、内生安全综述：最新进展与未来方向
- Survey of ubiquitons sensing, potential communication, integrated computing, and inherent security for Internet of vehicles: latest developments and future directions
- 通信学报 2024年45卷第11期页码：223-243
- 作者机构：
  
  1.澳门科技大学计算机科学与工程学院，澳门 999078
  2.北京邮电大学信息与通信工程学院，北京 100876
  3.电子科技大学计算机科学与工程学院，四川成都 611731
- 作者简介：
  
  [ "于刊（1990- ），男，山东潍坊人，北京邮电大学在站博士后，主要研究方向为车联网通感算安一体化、无线物理层安全等。" ]
  [ "李东（1982- ），男，中国澳门人，博士，澳门科技大学教授，主要研究方向为面向绿色物联网的反向散射通信技术、智能反射面辅助通信技术、无线人工智能等。" ]
  [ "张奇勋（1983- ），男，辽宁沈阳人，北京邮电大学教授、博士生导师，主要研究方向为异构无线网络认知组网、6G通感一体化技术、车联网宽带通信与资源优化的理论与方法。" ]
  [ "马丁友（1993- ），男，河北石家庄人，博士，北京邮电大学讲师，主要研究方向为通信感知一体化、雷达系统、雷达信号处理。" ]
  [ "冯志勇（1971- ），女，北京人，博士，北京邮电大学教授、博士生导师，主要研究方向为认知无线网络频谱感知与动态频谱资源管理、感知通信计算融合的智能车联网等。" ]
  [ "禹继国（1972- ），男，山东泰安人，博士，电子科技大学教授、博士生导师，主要研究方向为无线网络、物联网、网络与数据安全及隐私保护、区块链与分布式账本技术、分布式计算等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(62301076;62341101;62401077;62272256;62202250);澳门青年学者基金资助项目(AM2023015);国家自然科学基金创新群体基金资助项目(62321001);国家重点研发计划基金资助项目(2022YFB4300403);澳门科学技术发展基金资助项目(0188/2023/RIA3)
- DOI：10.11959/j.issn.1000-436x.2024153
  中图分类号： TN92
- 收稿日期：2024-04-15，
  
  修回日期：2024-07-31，
  
  纸质出版日期：2024-11-25
- 稿件说明：
移动端阅览
于刊,李东,张奇勋等.车联网泛在感知、潜在通信、融合计算、内生安全综述：最新进展与未来方向[J].通信学报,2024,45(11):223-243.

YU Kan,LI Dong,ZHANG Qixun,et al.Survey of ubiquitons sensing, potential communication, integrated computing, and inherent security for Internet of vehicles: latest developments and future directions[J].Journal on Communications,2024,45(11):223-243.
于刊,李东,张奇勋等.车联网泛在感知、潜在通信、融合计算、内生安全综述：最新进展与未来方向[J].通信学报,2024,45(11):223-243. DOI： 10.11959/j.issn.1000-436x.2024153.

YU Kan,LI Dong,ZHANG Qixun,et al.Survey of ubiquitons sensing, potential communication, integrated computing, and inherent security for Internet of vehicles: latest developments and future directions[J].Journal on Communications,2024,45(11):223-243. DOI： 10.11959/j.issn.1000-436x.2024153.

摘要

毫米波频段的通信与感知面临两方面挑战：感通干扰制约彼此性能，耦合作用规律及解耦方法尚不成熟；毫米波强指向性特点导致信息传输存在安全隐患。针对智能交通系统感通算融合网络的物理层安全问题，定义泛在感知、潜在通信、融合计算与内生安全的概念，刻画四者的耦合作用关系；梳理感通算安的研究现状及局限性，阐述资源优化分配、感通耦合干扰认知与建模、感通安性能制约机理等的可行思路。

Abstract

Communication and sensing in the millimeter-wave (mmWave) frequency band face two major challenges. Interference between sensing and communication limits their respective performances

and the coupling mechanisms and decoupling methods are still underdeveloped. The strong directionality of mmWave leads to potential security risks in information transmission. To address the physical layer security in the ISAC network of intelligent transportation systems

the concepts of ubiquitous sensing

potential communication

integrated computing

and inherent security

and characterizes the coupling relationships among them were defined. The current research and limitations of sensing

communication

computation

and security were reviewed

and feasible approaches for resource optimization

cognitive modeling of sensing-communication coupling interference

and the mechanisms constraining the performance of sensing-communication enabled security were presented.

关键词

Keywords

references

周一青 , 王露 , 原进宏 , 等 . 基于感通算融合的导轨式自动驾驶系统—无线虚拟导轨 [J ] . 中国科学(信息科学) , 2023 , 53 ( 6 ): 1050 - 1077 .

ZHOU Y Q , WANG L , YUAN J H , et al . Autonomous driving with virtual rail-a wireless tracked and controlled self-driving vehicle system based on the integration of communication, sensing, and computing [J ] . Scientia Sinica (Informationis) , 2023 , 53 ( 6 ): 1050 - 1077 .

LIU J H , ZHOU Y Q , LIU L . Communication delay-aware cooperative adaptive cruise control with dynamic network topologies-a convergence of communication and control [J ] . Digital Communications and Networks , 2023

孙茜 , 田霖 , 周一青 , 等 . 面向B5G和6G的边缘计算与网络切片资源管理 [J ] . 电信科学 , 2021 , 37 ( 6 ): 55 - 65 .

SUN Q , TIAN L , ZHOU Y Q , et al . Resource management in sliced networks with mobile edge computing for B5G and 6G [J ] . Telecommunications Science , 2021 , 37 ( 6 ): 55 - 65 .

LI Y F , LIU Q , ZHUANG W H , et al . Dynamic heterogeneous redundancy-based joint safety and security for connected automated vehicles: preliminary simulation and field test results [J ] . IEEE Vehicular Technology Magazine , 2023 , 18 ( 2 ): 89 - 97 .

QI Y L , ZHOU Y Q , LIU Y F , et al . Traffic-aware task offloading based on convergence of communication and sensing in vehicular edge computing [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 24 ): 17762 - 17777 .

YU X H , LI D , WANG Z D , et al . An integrated new deep learning framework for reliable CSI acquisition in connected and autonomous vehicles [J ] . IEEE Network , 2023 , 37 ( 4 ): 216 - 222 .

董梦圆 , 付宇钏 , 牛晓健 . 6G车联网中的通感算融合: 现状与挑战 [J ] . 无线电通信技术 , 2023 , 49 ( 1 ): 37 - 45 .

DONG M Y , FU Y C , NIU X J . Integration of sensing, communication, computing for 6G Internet of vehicles: current status and challenges [J ] . Radio Communications Technology , 2023 , 49 ( 1 ): 37 - 45 .

马小婷 . 车辆编队网络中资源分配与调度优化研究 [D ] . 北京 : 北京交通大学 , 2022 .

MA X T . Research on resource allocation and scheduling optimization in vehicle formation network [D ] . Beijing : Beijing Jiaotong University , 2022 .

康宇 , 刘雅琼 , 赵彤雨 , 等 . AI算法在车联网通信与计算中的应用综述 [J ] . 电信科学 , 2023 , 39 ( 1 ): 1 - 19 .

KANG Y , LIU Y Q , ZHAO T Y , et al . A survey on AI algorithms applied in communication and computation in Internet of vehicles [J ] . Telecommunications Science , 2023 , 39 ( 1 ): 1 - 19 .

GE X H , LI Z P , LI S K . 5G software defined vehicular networks [J ] . IEEE Communications Magazine , 2017 , 55 ( 7 ): 87 - 93 .

马忠贵 , 李卓 , 梁彦鹏 . 自动驾驶车联网中通感算融合研究综述与展望 [J ] . 工程科学学报 , 2023 , 45 ( 1 ): 137 - 149 .

MA Z G , LI Z , LIANG Y P . Overview and prospect of communication-sensing-computing integration for autonomous driving in the Internet of vehicles [J ] . Chinese Journal of Engineering , 2023 , 45 ( 1 ): 137 - 149 .

尉志青 , 牛阳阳 , 王溢 , 等 . 通信感知一体化干扰管理: 现状与展望 [J ] . 北京邮电大学学报 , 2022 , 45 ( 6 ): 31 - 39, 88 .

WEI Z Q , NIU Y Y , WANG Y , et al . Integrated sensing and communication interference management: recent advances and future trends [J ] . Journal of Beijing University of Posts and Telecommunications , 2022 , 45 ( 6 ): 31 - 39, 88 .

张嘉慧 , 王新奕 , 费泽松 , 等 . 6G通感融合网络中的物理层安全: 机遇与挑战 [J ] . 移动通信 , 2023 , 47 ( 3 ): 55 - 61 .

ZHANG J H , WANG X Y , FEI Z S , et al . Physical layer security in 6G integrated sensing and communication systems: opportunities and challenges [J ] . Mobile Communications , 2023 , 47 ( 3 ): 55 - 61 .

PENG H X , YE Q , SHEN X S . SDN-based resource management for autonomous vehicular networks: a multi-access edge computing approach [J ] . IEEE Wireless Communications , 2019 , 26 ( 4 ): 156 - 162 .

WU H Q , CHEN J Y , ZHOU C H , et al . Resource management in space-air-ground integrated vehicular networks: SDN control and AI algorithm design [J ] . IEEE Wireless Communications , 2020 , 27 ( 6 ): 52 - 60 .

LU H M , ZHANG Y , LI Y J , et al . User-oriented virtual mobile network resource management for vehicle communications [J ] . IEEE Transactions on Intelligent Transportation Systems , 2021 , 22 ( 6 ): 3521 - 3532 .

MAHMOOD A , BUTLER B , JENNINGS B . Towards efficient network resource management in SDN-based heterogeneous vehicular networks [C ] // Proceedings of the 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC) . Piscataway : IEEE Press , 2018 : 813 - 814 .

ALOMARI A , SUBRAMANIAM S K , SAMIAN N , et al . Resource management in SDN-based cloud and SDN-based fog computing: taxonomy study [J ] . Symmetry , 2021 , 13 ( 5 ): 734 .

TRUONG N B , LEE G M , GHAMRI-DOUDANE Y . Software defined networking-based vehicular Adhoc network with fog computing [C ] // Proceedings of the 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM) . Piscataway : IEEE Press , 2015 : 1202 - 1207 .

LIN C , HAN G J , QI X Y , et al . A distributed mobile fog computing scheme for mobile delay-sensitive applications in SDN-enabled vehicular networks [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 5 ): 5481 - 5493 .

GOUDARZI S , ANISI M H , AHMADI H , et al . Dynamic resource allocation model for distribution operations using SDN [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 2 ): 976 - 988 .

LIU Y B , HUO L J , ZHANG X T , et al . A multi-objective resource pre-allocation scheme using SDN for intelligent transportation system [J ] . IEEE Transactions on Intelligent Transportation Systems , 2024 , 25 ( 1 ): 571 - 586 .

ZHANG K , MAO Y M , LENG S P , et al . Mobile-edge computing for vehicular networks: a promising network paradigm with predictive off-loading [J ] . IEEE Vehicular Technology Magazine , 2017 , 12 ( 2 ): 36 - 44 .

DAI Y Y , XU D , MAHARJAN S , et al . Artificial intelligence empowered edge computing and caching for Internet of vehicles [J ] . IEEE Wireless Communications , 2019 , 26 ( 3 ): 12 - 18 .

REN Y L , YU X M , CHEN X Y , et al . Vehicular network edge intelligent management: a deep deterministic policy gradient approach for service offloading decision [C ] // Proceedings of the 2020 International Wireless Communications and Mobile Computing (IWCMC) . Piscataway : IEEE Press , 2020 : 905 - 910 .

WANG K , WANG X F , LIU X . A high reliable computing offloading strategy using deep reinforcement learning for IoVs in edge computing [J ] . Journal of Grid Computing , 2021 , 19 ( 2 ): 15 .

GUO H Z , LIU J J , REN J , et al . Intelligent task offloading in vehicular edge computing networks [J ] . IEEE Wireless Communications , 2020 , 27 ( 4 ): 126 - 132 .

LIU Y J , WANG D , SONG B , et al . Green heterogeneous computing powers allocation using reinforcement learning in SDN-IoV [J ] . IEEE Transactions on Green Communications and Networking , 2023 , 7 ( 2 ): 983 - 995 .

LIU T , TANG L , WANG W L , et al . Resource allocation in DT-assisted Internet of vehicles via edge intelligent cooperation [J ] . IEEE Internet of Things Journal , 2022 , 9 ( 18 ): 17608 - 17626 .

BRAUN M , TANBOURGI R , JONDRAL F K . Co-channel interference limitations of OFDM communication-radar networks [J ] . EURASIP Journal on Wireless Communications and Networking , 2013 , 2013 ( 1 ): 207 .

BROOKER G M . Mutual interference of millimeter-wave radar systems [J ] . IEEE Transactions on Electromagnetic Compatibility , 2007 , 49 ( 1 ): 170 - 181 .

AL-HOURANI A , EVANS R J , KANDEEPAN S , et al . Stochastic geometry methods for modeling automotive radar interference [J ] . IEEE Transactions on Intelligent Transportation Systems , 2018 , 19 ( 2 ): 333 - 344 .

FANG Z X , WEI Z Q , CHEN X , et al . Stochastic geometry for automotive radar interference with RCS characteristics [J ] . IEEE Wireless Communications Letters , 2020 , 9 ( 11 ): 1817 - 1820 .

HUANG J X , FEI Z S , WANG T X , et al . V2X-communication assisted interference minimization for automotive radars [J ] . China Communications , 2019 , 16 ( 10 ): 100 - 111 .

CHU P , ZHANG J A , WANG X X , et al . Interference characterization and power optimization for automotive radar with directional antenna [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 4 ): 3703 - 3716 .

SIT Y L , REICHARDT L , STURM C , et al . Extension of the OFDM joint radar-communication system for a multipath, multiuser scenario [C ] // Proceedings of the 2011 IEEE RadarCon (RADAR) . Piscataway : IEEE Press , 2011 : 718 - 723 .

TAN J B , DAI L L . Wideband beam tracking in THz massive MIMO systems [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 6 ): 1693 - 1710 .

WANG X Y , FEI Z S , GUO J , et al . RIS-assisted spectrum sharing between MIMO radar and MU-MISO communication systems [J ] . IEEE Wireless Communications Letters , 2021 , 10 ( 3 ): 594 - 598 .

HE Y H , CAI Y L , MAO H , et al . RIS-assisted communication radar coexistence: joint beamforming design and analysis [J ] . IEEE Journal on Selected Areas in Communications , 2022 , 40 ( 7 ): 2131 - 2145 .

AN K , LIN M , OUYANG J , et al . Secure transmission in cognitive satellite terrestrial networks [J ] . IEEE Journal on Selected Areas in Communications , 2016 , 34 ( 11 ): 3025 - 3037 .

DU J , JIANG C X , ZHANG H J , et al . Secure satellite-terrestrial transmission over incumbent terrestrial networks via cooperative beamforming [J ] . IEEE Journal on Selected Areas in Communications , 2018 , 36 ( 7 ): 1367 - 1382 .

LI B , FEI Z S , CHU Z , et al . Robust chance-constrained secure transmission for cognitive satellite–terrestrial networks [J ] . IEEE Transactions on Vehicular Technology , 2018 , 67 ( 5 ): 4208 - 4219 .

INTERDONATO G , KARLSSON M , BJÖRNSON E , et al . Local partial zero-forcing precoding for cell-free massive MIMO [J ] . IEEE Transactions on Wireless Communications , 2020 , 19 ( 7 ): 4758 - 4774 .

YU K , YU J G , LUO C W . The impact of mobility on physical layer security of 5G IoT networks [J ] . IEEE/ACM Transactions on Networking , 2023 , 31 ( 3 ): 1042 - 1055 .

CHU J J , LIU R , LI M , et al . Joint secure transmit beamforming designs for integrated sensing and communication systems [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 4 ): 4778 - 4791 .

YU K , FENG Z Y , YU J G , et al . Secure ultra-reliable and low latency communication in UAV-enabled NOMA wireless networks [J ] . IEEE Transactions on Vehicular Technology , 2024 , 73 ( 10 ): 14908 - 14922 .

ZHANG C , LIU Y L , CHEN H H . Deep learning based joint beamforming design in IRS-assisted secure communications [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 12 ): 16861 - 16865 .

YIN Z S , JIA M , CHENG N , et al . UAV-assisted physical layer security in multi-beam satellite-enabled vehicle communications [J ] . IEEE Transactions on Intelligent Transportation Systems , 2022 , 23 ( 3 ): 2739 - 2751 .

LI J T , HAN S , TAI X X , et al . Physical layer security enhancement for satellite communication among similar channels: relay selection and power allocation [J ] . IEEE Systems Journal , 2020 , 14 ( 1 ): 433 - 444 .

LI Y B , ZHANG H J , LONG K P . Joint resource, trajectory, and artificial noise optimization in secure driven 3-D UAVs with NOMA and imperfect CSI [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 11 ): 3363 - 3377 .

LI Y X , WANG W , LIU M Q , et al . Joint trajectory and power optimization for jamming-aided NOMA-UAV secure networks [J ] . IEEE Systems Journal , 2023 , 17 ( 1 ): 732 - 743 .

郑欣宇 . 无人机中继辅助NOMA通信系统的物理层安全性能研究 [D ] . 重庆 : 西南大学 , 2022 .

ZHENG X Y . Research on physical layer security performance of UAV relay-assisted NOMA communication system [D ] . Chongqing : Southwest University , 2022 .

TIAN W , DING X F , LIU G J , et al . A UAV-assisted secure communication system by jointly optimizing transmit power and trajectory in the Internet of things [J ] . IEEE Transactions on Green Communications and Networking , 2023 , 7 ( 4 ): 2025 - 2037 .

NGUYEN P X , NGUYEN V D , NGUYEN H V , et al . UAV-assisted secure communications in terrestrial cognitive radio networks: joint power control and 3D trajectory optimization [J ] . IEEE Transactions on Vehicular Technology , 2021 , 70 ( 4 ): 3298 - 3313 .

LIU Z X , ZHU B , XIE Y A , et al . UAV-aided secure communication with imperfect eavesdropper location: robust design for jamming power and trajectory [J ] . IEEE Transactions on Vehicular Technology , 2024 , 73 ( 5 ): 7276 - 7286 .

GUO D L , TANG L , ZHANG X G , et al . Joint optimization of trajectory and jamming power for multiple UAV-aided proactive eavesdropping [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 5 ): 5770 - 5785 .

ABDALLA A S , BEHFARNIA A , MAROJEVIC V . UAV trajectory and multi-user beamforming optimization for clustered users against passive eavesdropping attacks with unknown CSI [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 11 ): 14426 - 14442 .

PANG X W , ZHAO N , TANG J , et al . IRS-assisted secure UAV transmission via joint trajectory and beamforming design [J ] . IEEE Transactions on Communications , 2022 , 70 ( 2 ): 1140 - 1152 .

LIU X , YU Y F , PENG B , et al . RIS-UAV enabled worst-case downlink secrecy rate maximization for mobile vehicles [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 5 ): 6129 - 6141 .

WANG Q , ZHOU F H , HU R Q , et al . Energy efficient robust beamforming and cooperative jamming design for IRS-assisted MISO networks [J ] . IEEE Transactions on Wireless Communications , 2021 , 20 ( 4 ): 2592 - 2607 .

GUO H Y , YANG Z , ZOU Y L , et al . Joint reconfigurable intelligent surface location and passive beamforming optimization for maximizing the secrecy-rate [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 2 ): 2098 - 2110 .

QIN X T , SONG Z Y , HOU T W , et al . Joint optimization of resource allocation, phase shift, and UAV trajectory for energy-efficient RIS-assisted UAV-enabled MEC systems [J ] . IEEE Transactions on Green Communications and Networking , 2023 , 7 ( 4 ): 1778 - 1792 .

ZHANG X Q , ZHANG H J , DU W B , et al . IRS empowered UAV wireless communication with resource allocation, reflecting design and trajectory optimization [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 10 ): 7867 - 7880 .

LI S , DU H Q , ZHANG D Y , et al . Joint UAV trajectory and beamforming designs for RIS-assisted MIMO system [J ] . IEEE Transactions on Vehicular Technology , 2024 , 73 ( 4 ): 5378 - 5392 .

LI R W , GUO B , TAO M X , et al . Joint design of hybrid beamforming and reflection coefficients in RIS-aided mmWave MIMO systems [J ] . IEEE Transactions on Communications , 2022 , 70 ( 4 ): 2404 - 2416 .

WEI Z X , LIU F , MASOUROS C , et al . Toward multi-functional 6G wireless networks: integrating sensing, communication, and security [J ] . IEEE Communications Magazine , 2022 , 60 ( 4 ): 65 - 71 .

WEI Z X , MASOUROS C , LIU F . Secure directional modulation with few-bit phase shifters: optimal and iterative-closed-form designs [J ] . IEEE Transactions on Communications , 2021 , 69 ( 1 ): 486 - 500 .

SU N C , LIU F , WEI Z X , et al . Secure dual-functional radar-communication transmission: exploiting interference for resilience against target eavesdropping [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 9 ): 7238 - 7252 .

XU D F , YU X H , NG D W K , et al . Robust and secure resource allocation for ISAC systems: a novel optimization framework for variable-length snapshots [J ] . IEEE Transactions on Communications , 2022 , 70 ( 12 ): 8196 - 8214 .

ZHANG Z , DAI L , CHEN X , et al . Active RIS vs. passive RIS: which will prevail in 6G? [J ] . arXiv Preprint , arXiv: 2103.15154 , 2021 .

SALEM A A , ISMAIL M H , IBRAHIM A S . Active reconfigurable intelligent surface-assisted MISO integrated sensing and communication systems for secure operation [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 4 ): 4919 - 4931 .

BINH T H , SON D B , VO H , et al . Reinforcement learning for optimizing delay-sensitive task offloading in vehicular edge–cloud computing [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 2 ): 2058 - 2069 .

ALAM M Z , JAMALIPOUR A . Multi-agent DRL-based Hungarian algorithm (MADRLHA) for task offloading in multi-access edge computing Internet of vehicles (IoVs) [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 9 ): 7641 - 7652 .

HAZARIKA B , SINGH K , PAUL A , et al . Hybrid machine learning approach for resource allocation of digital twin in UAV-aided Internet-of-vehicles networks [J ] . IEEE Transactions on Intelligent Vehicles , 2024 , 9 ( 1 ): 2923 - 2939 .

SUN F , ZHANG Z J , ZEADALLY S , et al . Edge computing-enabled Internet of vehicles: towards federated learning empowered scheduling [J ] . IEEE Transactions on Vehicular Technology , 2022 , 71 ( 9 ): 10088 - 10103 .

YAO L , XU X L , BILAL M , et al . Dynamic edge computation offloading for Internet of vehicles with deep reinforcement learning [J ] . IEEE Transactions on Intelligent Transportation Systems , 2023 , 24 ( 11 ): 12991 - 12999 .

XIONG K , LENG S P , HUANG C W , et al . Intelligent task offloading for heterogeneous V2X communications [J ] . IEEE Transactions on Intelligent Transportation Systems , 2021 , 22 ( 4 ): 2226 - 2238 .

AHSAN KAZMI S M , DANG T N , YAQOOB I , et al . A novel contract theory-based incentive mechanism for cooperative task-offloading in electrical vehicular networks [J ] . IEEE Transactions on Intelligent Transportation Systems , 2022 , 23 ( 7 ): 8380 - 8395 .

YIN L X , LUO J , QIU C X , et al . Joint task offloading and resources allocation for hybrid vehicle edge computing systems [J ] . IEEE Transactions on Intelligent Transportation Systems , 2024 , PP( 99 ): 1 - 14 .

GENG L W , ZHAO H B , WANG J Y , et al . Deep-reinforcement-learning-based distributed computation offloading in vehicular edge computing networks [J ] . IEEE Internet of Things Journal , 2023 , 10 ( 14 ): 12416 - 12433 .

XIAO T T , CHEN C , WAN S H . Mobile-edge-platooning cloud: a lightweight cloud in vehicular networks [J ] . IEEE Wireless Communications , 2022 , 29 ( 3 ): 87 - 94 .

WANG L , LIANG H B , ZHAO D M . Deep-reinforcement-learning-based computation offloading and power allocation within dynamic platoon network [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 6 ): 10500 - 10512 .

YANG C , LOU W , LIU Y , et al . Resource allocation for edge computing-based vehicle platoon on freeway: a contract-optimization approach [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 12 ): 15988 - 16000 .

LIU C H , ZHAO M D , WANG H C , et al . Stackelberg-game computation offloading scheme for parked vehicle-assisted VEC and experiment analysis [J ] . IEEE Transactions on Intelligent Vehicles , 2024 , PP( 99 ): 1 - 12 .

YU K , ZHU F Z , LIU X W , et al . Delay-effective task offloading technology in Internet of vehicles: from the perspective of the vehicle platooning [J ] . arXiv Preprint , arXiv: 2405.16060 , 2024 .

LIU X W , WANG Y , YU K , et al . An multi-resources integration empowered task offloading in Internet of vehicles: from the perspective of wireless interference [J ] . arXiv Preprint , arXiv: 2405.16078 , 2024 .

XIAO Z Y , CAO S Q , ZHU L P , et al . Channel estimation for movable antenna communication systems: a framework based on compressed sensing [J ] . IEEE Transactions on Wireless Communications , 2024 , PP(99): 1.

ZHU L P , MA W Y , ZHANG R . Modeling and performance analysis for movable antenna enabled wireless communications [J ] . IEEE Transactions on Wireless Communications , 2024 , 23 ( 6 ): 6234 - 6250 .

ZHU L P , MA W Y , ZHANG R . Movable antennas for wireless communication: opportunities and challenges [J ] . IEEE Communications Magazine , 2024 , 62 ( 6 ): 114 - 120 .

MA W Y , ZHU L P , ZHANG R . MIMO capacity characterization for movable antenna systems [J ] . IEEE Transactions on Wireless Communications , 2024 , 23 ( 4 ): 3392 - 3407 .

FENG Z Y , ZHAO Y J , YU K , et al . Movable antenna empowered physical layer security without eve’s CSI: joint optimization of beamforming and antenna positions [J ] . arXiv Preprint , arXiv: 2405.16062 , 2024 .

OGONJI M M , OKEYO G , WAFULA J M . A survey on privacy and security of Internet of Things [J ] . Computer Science Review , 2020 , 38 : 100312 .

GONG T Y , ZHU L , YU F R , et al . Edge intelligence in intelligent transportation systems: a survey [J ] . IEEE Transactions on Intelligent Transportation Systems , 2023 , 24 ( 9 ): 8919 - 8944 .

CAI X L , ZHOU L L , LI F , et al . An incentive mechanism for vehicular crowdsensing with security protection and data quality assurance [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 8 ): 9984 - 9998 .

ZHOU H L , ZHENG Y F , HUANG H J , et al . Toward robust hierarchical federated learning in Internet of vehicles [J ] . IEEE Transactions on Intelligent Transportation Systems , 2023 , 24 ( 5 ): 5600 - 5614 .

HU X Y , LI R Q , WANG L C , et al . A data sharing scheme based on federated learning in IoV [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 9 ): 11644 - 11656 .

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据