计算机科学 ›› 2023, Vol. 50 ›› Issue (1): 285-293.doi: 10.11896/jsjkx.211000164

• 计算机网络 • 上一篇    下一篇

蜂窝车联网连通性研究综述与展望

代亮, 吴益钵, 汪贵平   

  1. 长安大学电子与控制工程学院 西安 710064
    长安大学车联网教育部-中国移动联合实验室 西安 710064
  • 收稿日期:2021-10-22 修回日期:2022-10-30 出版日期:2023-01-15 发布日期:2023-01-09
  • 通讯作者: 代亮(ldai@chd.edu.cn)
  • 基金资助:
    国家重点研发计划(2021YFB2601401)

Review and Prospect of Connectivity Research on Cellular-V2X

DAI Liang, WU Yibo, WANG Guiping   

  1. School of Electronics and Control Engineering,Chang'an University,Xi'an 710064,China
    The Joint Laboratory for Internet of Vehicles,Ministry of Education-China Mobile Communications Corporation,Chang'an University,Xi'an 710064,China
  • Received:2021-10-22 Revised:2022-10-30 Online:2023-01-15 Published:2023-01-09
  • About author:AI Liang,born in 1981,assistant professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include theory and application of Internet of vehicles.
  • Supported by:
    National Key Research and Development Program of China(2021YFB2601401).

摘要: 作为未来自动驾驶汽车的核心技术之一,蜂窝车联网(Cellular-V2X,C-V2X)在快速普及应用的同时,还面临着一系列与网络连通性相关的发展痛点,如车辆移动性、网络覆盖、频谱资源等问题。C-V2X车路协同连通性直接反映了C-V2X网络联网车辆的整体性能,对于保证信息在C-V2X网络内实现远距离、自适应、低时延、高可靠传输具有重要意义。不同于传统的蜂窝移动通信网络,C-V2X联网车辆具有移动速度快、节点间链路持续时间短暂、无线通信环境可预测性强、移动模型受限于道路拓扑等特点,在高效利用频谱进行通信的同时,还具有自组织网络的无中心和自组织等诸多特性。首先简要介绍了C-V2X的优点与特点,包括C-V2X的进展与结构体系;然后介绍了C-V2X车联网中车路协同连通性的定义及相关发展约束,在此基础上对C-V2X网络连通性研究中基于交通场景、通信方式选择、路侧单元(Road Side Unit,RSU)位置部署、功率控制、模型驱动的研究方法进行了总结与分类;最后探讨了C-V2X的发展趋势,对其未来应用进行展望。

关键词: 蜂窝车联网, 连通性, 通信方式, 功率控制, 模型驱动

Abstract: As one of the core technologies of future autonomous vehicles,Cellular-V2X(C-V2X) faces a series of developing pain points related to network connectivity,such as mobility,coverage and spectrum,while rapidly popularizing its application.The connectivity of C-V2X based cooperative vehicle-infrastructure system directly reflects the overall performance of C-V2X network connected vehicles,which is of great significance to ensure information can achieve long-distance,adaptive,low latency and high reliable transmission.Different from the traditional cellular mobile communication network,C-V2X networking vehicles have the characteristics of high moving speed,short link duration between nodes,strong predictability of wireless communication environment,and mobility model limited by road topology.To make efficient use of spectrum for communication,C-V2X networking vehicles also have the characteristics of no center and self-organization of ad hoc network.Firstly,the advantages and characteristics of C-V2X are briefly introduced,including the progress and structure of C-V2X.On this basis,research on connectivity of C-V2X network are summarized and classified based on transportation scenarios,communication mode selection,road side unit(RSU) location deployment,power control and model driven.Finally,the development trends of connectivity for C-V2X are discussed and its future application is prospected.

Key words: Cellular-V2X, Connectivity, Communication mode, Power control, Model driven

中图分类号: 

  • TP393
[1]CHEN S,HU J,SHI Y,et al.A Vision of C-V2X:Technologies,Field Testing,and Challenges With Chinese Development[J].IEEE Internet of Things Journal,2020,7(5):3872-3881.
[2]CHEN S,HU J,SHI Y,et al.Vehicle-to-Everything(v2x)Services Supported by LTE-Based Systems and 5G[J].IEEE Communications Standards Magazine,2017,1(2):70-76.
[3]CHEN S,LI Q,WANG Y,et al.C-V2X equipment identification management and authentication mechanism[J].China Communications,2020,18(8):297-306.
[4]SARRIGIANNIS I,CONTRERAS M,RAMANTAS K,et al.Fog-Enabled Scalable C-V2X Architecture for Distributed 5G and Beyond Applications[J].IEEE Network,2020,34(5):120-126.
[5]FU S,ZHANG W,JIANG Z.A network-level connected autonomous driving evaluation platform implementing C-V2X techno-logy[J].China Communications,2021,18(6):77-88.
[6]JI B,ZHANG X,MUMTAZ S,et al.Survey on the Internet of Vehicles:Network Architectures and Applications[J].IEEE Communications Standards Magazine,2020,4(1):34-41.
[7]SAAD M,KHAN M,SHAH S,et al.Advancements in Vehicular Communication Technologies:C-V2X and NR-V2X Comparison[J].IEEE Communications Magazine,2021,59(8):107-113.
[8]JAYAWEERA S,MANOSHA S,RAJATHEVA N,et al.Co-Existence of ITS-G5 and C-V2X at an Urban Road Intersection[C]//2021 Joint European Conference on Networks and Communications & 6G Summit(EuCNC/6G Summit).Porto:IEEE Press,2021:253-258.
[9]ECKERMANN F,WIETFELD C.SDR-based Open-Source C-V2X Traffic Generator for Stress Testing Vehicular Communication[C]//2021 IEEE 93rd Vehicular Technology Conference(VTC2021-Spring).Helsinki:IEEE Press,2021:1-5.
[10]PAN B,WU H.Success Probability Analysis of Cooperative C-V2X Communications[J].IEEE Transactions on Intelligent Transportation Systems,2022,23(7):7170-7183.
[11]KUTILA M,PYYKONEN P,HUANG Q,et al.C-V2X Supported Automated Driving[C]//2019 IEEE International Confe-rence on Communications Workshops(ICC Workshops).Shanghai:IEEE Press,2019:1-5.
[12]CHETLUR V,DHILLON H.Coverage and Rate Analysis of Downlink Cellular Vehicle-to-Everything(C-V2X) Communication[J].IEEE Transactions on Wireless Communications,2020,19(3):1738-1753.
[13]BAZZI A,ZANELLA A,SARRIS I,et al.Co-channel Coexistence:Let ITS-G5 and Sidelink C-V2X Make Peace[C]//2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility(ICMIM).Linz:IEEE Press,2020:1-4.
[14]SABEEH S,WESOŁOWSKI K.C-V2X Mode 4 Resource Allocation in High Mobility Vehicle Communication[C]//2020 IEEE 31st Annual International Symposium on Personal,Indoor and Mobile Radio Communications.London:IEEE Press,2020:1-6.
[15]MOLINA-MASEGOSA R,SEPULCRE M,GOZALVEZ J.Geo-Based Scheduling for C-V2X Networks[J].IEEE Transactions on Vehicular Technology,2019,68(9):8397-8407.
[16]BAZZI A,CAMPOLO C,MOLINAROA,et al.On WirelessBlind Spots in the C-V2X Sidelink[J].IEEE Transactions on Vehicular Technology,2020,69(8):9239-9243.
[17]CHEN Q,JIANG H,YU G.Service Oriented Resource Management in Spatial Reuse-Based C-V2X Networks[J].IEEE Wireless Communications Letters,2020,9(1):91-94.
[18]SCHWIND A,HOFMANN W,BUDDAPPAGARI S,et al.Bi-static Reflectivity Patterns of Vulnerable Road Users in the C-V2X Frequency Range[C]//2020 IEEE Radar Conference(RadarConf20).Florence:IEEE Press,2020:1-6.
[19]GILL K,HEATH K N,CHUKE S,et al.Bumblebee-Inspired C-V2X Dynamic Spectrum Access Testbed Using Open Air Interface[C]//2020 IEEE 91st Vehicular Technology Conference(VTC2020-Spring).Antwerp:IEEE Press,2020:1-5.
[20]SEHLA K,NGUYEN T,PUJOLLE G,et al.A New Clustering-based Radio Resource Allocation Scheme for C-V2X[C]//2021 Wireless Days(WD).Paris:IEEE Press,2021:1-8.
[21]HE X,LV J,ZHAO J,etal.Design and Analysis of a Short-Term Sensing-Based Resource Selection Scheme for C-V2X Networks[J].IEEE Internet of Things Journal,2020,7(11):11209-11222.
[22]WIJESIRI G P,HAAPOLA J,SAMARASINGHE T.A Dis-crete-Time Markov Chain Based Comparison of the MAC Layer Performance of C-V2X Mode 4 and IEEE 802.11p[J].IEEE Transactions on Communications,2021,69(4):2505-2517.
[23]YANG M X,YU R D,LIU Y H,et al.Traffic Statistics and Analysis of Transmitter in C-V2X Communication[C]//2021 IEEE 93rd Vehicular Technology Conference(VTC2021-Spring).Helsinki:IEEE Press,2021:1-5.
[24]POLI F,DENIS B,MANNONI V,et al.Evaluation of C-V2X Sidelink for Cooperative Lane Merging in a Cross-Border Highway Scenario[C]//2021 IEEE 93rd Vehicular Technology Conference(VTC2021-Spring).Helsinki:IEEE Press,2021:1-5.
[25]HUANG Z,LI Y,CHEN R,et al.Clustering Analysis of Multipath Components in Urban Road Scenario for C-V2X Propagation Channels[C]//2018 12th International Symposium on Antennas,Propagation and EM Theory(ISAPE).Hangzhou:IEEE Press,2018:1-3.
[26]ZHANG M,DOU Y,CHONG P,et al.Fuzzy Logic-Based Resource Allocation Algorithm for V2X Communications in 5G Cellular Networks[J].IEEE Journal on Selected Areas in Communications,2021,39(8):2501-2513.
[27]IZYDORCZYK T,TAVARES F,BERARDINELLI G,et al.Performance Evaluation of Multi-Antenna Receivers for Vehicular Communications in Live LTE Networks[C]//2019 IEEE 89th Vehicular Technology Conference(VTC2019-Spring).Kuala Lumpur:IEEE Press,2019:1-6.
[28]GIBELLINI L,MERANI M.Out-of-Coverage Multi-Hop Road Safety Message Distribution via LTE-A Cellular V2V(C-V2V)[C]//2018 IEEE 88th Vehicular Technology Conference(VTC-Fall).Chicago:IEEE Press,2018:1-6.
[29]LI Y,MOSAVAT-JAHROMI H,CAI L,et al.GNC-MAC:Grouping and Network Coding-assisted MAC for Reliable Group-casting in V2X[C]//2020 IEEE 92nd Vehicular Technology Conference(VTC2020-Fall).Victoria:IEEE Press,2020:1-6.
[30]GONZALEZ-MARTÍN M,SEPULCRE M,MOLINA-MASEGOSA R,et al.Analytical Models of the Performance of C-V2X Mode 4 Vehicular Communications[J].IEEE Transactions on Vehicular Technology,2019,68(2):1155-1166.
[31]BUTE M,FAN P,LIU G,et al.A Collaborative Task Offloading Scheme in Vehicular Edge Computing[C]//2021 IEEE 93rd Vehicular Technology Conference(VTC2021-Spring).Helsinki:IEEE Press,2021:1-5.
[32]HAN X,LI X,LUO C,et al.Incentive Mechanism with the Caching Strategy for Content Sharing in Vehicular Networks[C]//2019 IEEE Globecom Workshops(GC Wkshps).Waikoloa:IEEE Press,2019:1-6.
[33]WEN X,CHEN J,HU Z,et al.A p-Opportunistic Channel Access Scheme for Interference Mitigation Between V2V and V2I Communications[J].IEEE Internet of Things Journal,2020,7(5):3706-3718.
[34]WANG Z,ZHEN J,WU Y.Analysis of the Downlink Connectivity Probability within the Two-Hop Coverage of an RSU in VANET[C]//2017 IEEE 85th Vehicular Technology Confe-rence(VTC Spring).Sydney:IEEE Press,2017:1-5.
[35]LI C X,ZHEN A R,ZENG F T,et al.Access and connectivity probability for V2X communication networks[C]//2017 13th IEEE International Conference on Electronic Measurement & Instruments(ICEMI).Yangzhou:IEEE Press,2017:260-264.
[36]ZHAO J,CHEN Y,GONG Y.Study of Connectivity Probability of Vehicle-to-Vehicle and Vehicle-to-Infrastructure Communication Systems[C]//2016 IEEE 83rd Vehicular Technology Conference(VTC Spring).Nanjing:IEEE Press,2016:1-4.
[37]WANG Z,ZHENG J,WU Y,et al.A centrality-based RSU deployment approach for vehicular ad hoc networks[C]//2017 IEEE International Conference on Communications(ICC).Paris:IEEE Press,2017:1-5.
[38]CHENG H,FEI X,BOUKERCHE A,et al.Hotspot discovery algorithms in coverage selection model over VANETs[C]//2014 IEEE Global Communications Conference.Austin:IEEE Press,2014:143-148.
[39]LLOYD S.Least squares quantization in PCM[J].IEEE Transa-ctions on Information Theory.IEEE Press,1982,28(2):129-137.
[40]FREY B,DUECK D.Clustering by passing messages between data points[J].Science,2007,315:972-976.
[41]JIANG P,LI P,ZHANG T,et al.Roadside Units Placement for Traffic Flows Coverage Requirement in Vehicular Networks[C]//2018 IEEE International Conference on Smart Cloud(SmartCloud).New York:IEEE Press,2018:145-152.
[42]ZHENG H,CHANG W,WU J.Coverage and distinguishability requirements for Traffic Flow Monitoring Systems[C]//2016 IEEE/ACM 24th International Symposium on Quality of Service(IWQoS).Beijing:IEEE Press,2016:1-10
[43]ZHU J Y,HUANG C H,FANG X Y.RSU deployment planning based on approximation algorithm in urban VANET[J].Journal on Communications,2018,39(1):78-89.
[44]PATIL P,GOKHALE A.Voronoi-based placement of road-side units to improve dynamic resource management in Vehicular Ad Hoc Networks[C]//2013 International Conference on Collaboration Technologies and Systems(CTS).San Diego:IEEE Press,2013:389-396.
[45]PATIL P,GOKHALE A.Maximizing Vehicular Network Con-nectivity through an Effective Placement of Road Side Units Using Voronoi Diagrams[C]//2012 IEEE 13th International Conference on Mobile Data Management.Bengaluru:IEEE Press,2012:274-275.
[46]KIM D,VELASCO Y,WANG W,et al.A New Comprehensive RSU Installation Strategy for Cost-Efficient VANET Deployment[J].IEEE Transactions on Vehicular Technology,2017,66(5):4200-4211.
[47]LIN C,DENG D.Optimal Two-Lane Placement for Hybrid VANET-Sensor Networks[J].IEEE Transactions on Industrial Electronics,2015,62(12):7883-7891.
[48]LIN C,DENG D.Optimal Two-Lane Placement for Hybrid VANET-Sensor Networks[J].IEEE Transactions on Industrial Electronics,2015,62(12):7883-7891.
[49]TAO J,ZHU L,WANG X,et al.RSU deployment scheme with power control for highway message propagation in VANETs[C]//2014 IEEE Global Communications Conference.Austin:IEEE Press,2014:169-174.
[50]KANG B,JUNG S,BAHK S.Sensing-Based Power Adaptation for Cellular V2X Mode 4[C]//2018 IEEE International Symposium on Dynamic Spectrum Access Networks(DySPAN).Seoul:IEEE Press,2018:1-4.
[51]SAIFUDDIN M,ZAMAN M,TOGHI B,et al.PerformanceAnalysis of Cellular-V2X with Adaptive & Selective Power Control[C]//2020 IEEE 3rd Connected and Automated Vehicles Symposium(CAVS).Victoria:IEEE Press,2020:1-7.
[52]WEN Q,HU B.Joint Optimal Relay Selection and Power Control for Reliable Broadcast Communication in Platoon[C]//2020 IEEE 92nd Vehicular Technology Conference(VTC2020-Fall).Victoria:IEEE Press,2020:1-6.
[53]SIAL M,DENG Y,AHMED J,et al.Stochastic Geometry Modeling of Cellular V2X Communication Over Shared Channels[J].IEEE Transactions on Vehicular Technology,2019,68(12):11873-11887.
[54]CHETLUR V,DHILLON H.Coverage Analysis of a Vehicular Network Modeled as Cox Process Driven by Poisson Line Process[J].IEEE Transactions on Wireless Communications,2018,17(7):4401-4416.
[55]CHETLUR V,DHILLON H.Coverage and Rate Analysis ofDownlink Cellular Vehicle-to-Everything(C-V2X) Communication[J].IEEE Transactions on Wireless Communications,2020,19(3):1738-1753.
[56]CHETLUR V,DHILLON H S.Success Probability and Area Spectral Efficiency of a VANET Modeled as a Cox Process[J].IEEE Wireless Communications Letters,2018,7(5):856-859.
[57]CHO Y,HUANG K,CHAE C.V2X Downlink Coverage Analysis with a Realistic Urban Vehicular Model[C]//2018 IEEE Globecom Workshops(GC Wkshps).Abu Dhabi:IEEE Press,2018:1-6.
[58]CHOI C,BACCELLI F.An Analytical Framework for Coverage in Cellular Networks Leveraging Vehicles[J].IEEE Transactions on Communications,2018,66(10):4950-4964.
[59]AMMAR H A,AJAMI A,ARTAIL H.A Poisson Line Process-Based Framework for Determining the Needed RSU Density and Relaying Hops in Vehicular Networks[J].IEEE Transactions on Wireless Communications,2020,19(10):6643-6659.
[60]XIANG C C,LI Y Y,FENG L,et al.Near-optimal Vehicular Crowdsensing Task Allocation Empowered by Deep Reinforcement Learning[J].Chinese Journal of Computers,2022,45(5):918-934.
[61]XIANG C C,LI Y Y,ZHOU Y L,et al.A Comparative Approach to Resurrecting the Market of MOD Vehicular Crowdsensing[C]//IEEE International Conference on Compu-ter Communications.2022:1-10.
[62]HU J,CHEN S,ZHAO L,et al.Link Level Performance Comparison between LTE V2X and DSRC[J].Journal of Communications and Information Networks,2017,2(2):101-112.
[63]XIANG C C,ZHOU Y L,DAI H P,et al.Reusing Delivery Drones for Urban Crowdsensing[J].IEEE Transactions on Mobile Computing.doi:10.1109/TMC.2021.3127212.
[64]FAN X C,XIANG C C,CHEN C,et al.BuildSenSys:Reusing Building Sensing Data for Traffic Prediction With Cross-Domain Learning[J].IEEE Transactions on Mobile Computing,2021,20(6):2154-2171.
[65]CHEN S,LIANG Y,SUN S,et al.Vision,Requirements,and Technology Trend of 6G:How to Tackle the Challenges of System Coverage,Capacity,User Data-Rate and Movement Speed[J].IEEE Wireless Communications,2020,27(2):218-228.
[1] 王昌晶, 丁希龙, 陈茜, 罗海梅, 左正康.
基于模型驱动的Web服务建模与三阶段模型转换方法
Web Service Modeling Based on Model-driven and Three-stage Model Transformation Method
计算机科学, 2022, 49(11A): 211100055-14. https://doi.org/10.11896/jsjkx.211100055
[2] 陈港, 孟相如, 康巧燕, 翟东.
基于最小生成树的vSDN故障快速恢复算法
vSDN Fault Recovery Algorithm Based on Minimum Spanning Tree
计算机科学, 2022, 49(11A): 211200034-7. https://doi.org/10.11896/jsjkx.211200034
[3] 袁昕旺, 谢智东, 谭信.
无人机边缘计算中的资源管理优化研究综述
Survey of Resource Management Optimization of UAV Edge Computing
计算机科学, 2022, 49(11): 234-241. https://doi.org/10.11896/jsjkx.211100015
[4] 黄双芹, 刘英博, 黄向生.
模型驱动开发工具的自动化测试技术研究
Research on Automatic Testing Technology of Model Driven Development Tools
计算机科学, 2021, 48(6A): 568-571. https://doi.org/10.11896/jsjkx.201000139
[5] 程云飞, 田红心, 刘祖军.
NOMA系统异构网络中联合用户关联和功率控制协同优化
Collaborative Optimization of Joint User Association and Power Control in NOMA Heterogeneous Network
计算机科学, 2021, 48(3): 269-274. https://doi.org/10.11896/jsjkx.191100213
[6] 孙海华, 周思源, 谭国平, 张芝.
基于随机几何的无线中继网络上行链路精细化性能分析
Fine-grained Performance Analysis of Uplink in Wireless Relay Network Based on Stochastic Geometry
计算机科学, 2021, 48(2): 64-69. https://doi.org/10.11896/jsjkx.200800205
[7] 李智, 邓杰, 杨溢龙, 韦尚锋.
从信息物理融合系统问题模型到UML用例图的变换方法
Transformational Approach from Problem Models of Cyber-Physical Systems to Use Case Diagrams in UML
计算机科学, 2020, 47(12): 65-72. https://doi.org/10.11896/jsjkx.201200044
[8] 钟旭东,何元智,任保全,董飞鸿.
基于合作博弈的认知卫星网络信道分配与上行功率控制算法
Channel Allocation and Power Control Algorithm for Cognitive Satellite Networks Based on Cooperative Game Theory
计算机科学, 2020, 47(1): 252-257. https://doi.org/10.11896/jsjkx.181202352
[9] 张绘娟, 张达敏, 闫威, 陈忠云, 辛梓芸.
异构网络中基于吞吐量优化的资源分配机制
Throughput Optimization Based Resource Allocation Mechanism in Heterogeneous Networks
计算机科学, 2019, 46(10): 109-115. https://doi.org/10.11896/jsjkx.180901787
[10] 王振朝,赵云,薛文玲.
下含D2D蜂窝网中基于公平性原理的功率控制
Power Control Based on Fairness in D2DUnderlaid Cellular Networks
计算机科学, 2018, 45(7): 104-109. https://doi.org/10.11896/j.issn.1002-137X.2018.07.017
[11] 徐涛,杜昱萱,吕宗磊.
基于线性规划的传感器节点布局模型
Sensor Node Deployment Model Based on Linear Programming
计算机科学, 2018, 45(7): 110-115. https://doi.org/10.11896/j.issn.1002-137X.2018.07.018
[12] 李方伟, 张琳琳, 朱江.
D2D通信网络中一种基于时间反演的无线资源优化机制
Radio Resource Optimization Mechanism Based on Time-reversal in Device-to-Device Communication Network
计算机科学, 2018, 45(10): 78-82. https://doi.org/10.11896/j.issn.1002-137X.2018.10.015
[13] 杨大禹,李敬兆,任萍.
基于噪声模型下D2D蜂窝系统的多用户合作功率控制分配方案
Multi-user Cooperative Power Control Allocation Scheme for D2D Cellular System Based on Noise Model
计算机科学, 2017, 44(7): 98-103. https://doi.org/10.11896/j.issn.1002-137X.2017.07.018
[14] 侯金奎,王磊.
基于体系结构的模型转换语义描述框架
Formal Framework of Architecture-based Model Transformation
计算机科学, 2017, 44(4): 148-152. https://doi.org/10.11896/j.issn.1002-137X.2017.04.032
[15] 冯谷,李尼格.
模型驱动的移动应用测试方法
Model-driven Testing for Mobile Applications
计算机科学, 2017, 44(11): 232-239. https://doi.org/10.11896/j.issn.1002-137X.2017.11.035
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!