IEEE Organizations related to Vehicle-to-everything

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Most published Xplore authors for Vehicle-to-everything

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Xplore Articles related to Vehicle-to-everything

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Evolution of Vehicular Communications within the Context of 5G Systems

Enabling 5G Communication Systems to Support Vertical Industries, None

Vehicles and roads are starting to be connected and gradually moving towards fully autonomous vehicles and truly intelligent road infrastructure. This chapter investigates the evolution of vehicular communication systems towards fifth generation (5G) and how the applications and services follow that evolution. It also investigates the cellular‐based solution, and how it is evolving from LTE Release 14, the initial C‐V2X ...


State‐of‐the‐Art of Sparse Code Multiple Access for Connected Autonomous Vehicle Application

Enabling 5G Communication Systems to Support Vertical Industries, None

Considering the dramatic growth of traffic, 5G communication technology is proposed to support massive connectivity with a large number of devices. Connected autonomous vehicles (CAVs) network is one of the important future applications that can benefit from 5G. Sparse Code Multiple Access (SCMA), as a promising technique in 5G wireless communication networks, has recently received lots of attention. This chapter ...


Reinforcement Learning Based Vehicle-cell Association Algorithm for Highly Mobile Millimeter Wave Communication

IEEE Transactions on Cognitive Communications and Networking, None

Vehicle-to-everything (V2X) communication is a growing area of communication with a variety of use cases. This paper investigates the problem of vehicle- cell association in millimeter wave (mmWave) communication networks. The aim is to maximize the time average rate per vehicular user (VUE) while ensuring a target minimum rate for all VUEs with low signaling overhead. We first formulate the ...


Study on sharing and compatibility between ITS and Fixed Service

2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 2019

Intelligent transportation system (ITS) is one of the most important applications in Internet of Things (IoT). In several regions and countries, the government authority is planning to allocate 5850-5925MHz to ITS. In order to meet the requirements of ITS in this frequency band, no harmful interference could not be produced to the existing system. In this paper, the compatibility analysis ...


Design of a V2X Vehicle Antenna

2018 International Symposium on Antennas and Propagation (ISAP), 2018

In this paper, we propose V2X shark-fin antenna that operated on vehicle roof. Propose antenna is composed of AM/FM Radio broadcasting, Digital Media Broadcasting (DMB), Global Positioning System (GPS), and dual V2X (Vehicle-to- everything) antennas. Propose antenna has -1.2 dBi in AM/FM Radio band, 5.8 dBi in DMB band, and 28 dBic in GPS band (Including Low Noise Amplifier). Especially ...


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Educational Resources on Vehicle-to-everything

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IEEE-USA E-Books

  • Evolution of Vehicular Communications within the Context of 5G Systems

    Vehicles and roads are starting to be connected and gradually moving towards fully autonomous vehicles and truly intelligent road infrastructure. This chapter investigates the evolution of vehicular communication systems towards fifth generation (5G) and how the applications and services follow that evolution. It also investigates the cellular‐based solution, and how it is evolving from LTE Release 14, the initial C‐V2X system, towards Release 16, the fully‐fledged 5G system. The chapter focuses in the co‐existence issues with dedicated short range communication and what other technologies contribute to efficient V2X services. It also focuses on the data dissemination on top of a vehicular communication platform that could support efficient cloud‐based Intelligent Transportation Services. The chapter examines how the evolution of V2X communication technologies is mirrored on the evolution of services it supports, from awareness to autonomous driving.

  • State‐of‐the‐Art of Sparse Code Multiple Access for Connected Autonomous Vehicle Application

    Considering the dramatic growth of traffic, 5G communication technology is proposed to support massive connectivity with a large number of devices. Connected autonomous vehicles (CAVs) network is one of the important future applications that can benefit from 5G. Sparse Code Multiple Access (SCMA), as a promising technique in 5G wireless communication networks, has recently received lots of attention. This chapter aims to investigate the fundamental principles of SCMA technique, summarize the state‐of‐the‐art of SCMA technology and its application, and point out how the current research work can contribute to the quality of experience for drivers and passengers. It identifies the gaps in the adoption of SCMA in vehicular communication systems. The chapter also identifies the challenges and research gaps for the provision of massive connections with low latency and high reliability in the 5G communication system for CAVs.

  • Reinforcement Learning Based Vehicle-cell Association Algorithm for Highly Mobile Millimeter Wave Communication

    Vehicle-to-everything (V2X) communication is a growing area of communication with a variety of use cases. This paper investigates the problem of vehicle- cell association in millimeter wave (mmWave) communication networks. The aim is to maximize the time average rate per vehicular user (VUE) while ensuring a target minimum rate for all VUEs with low signaling overhead. We first formulate the user (vehicle) association problem as a discrete non-convex optimization problem. Then, by leveraging tools from machine learning, specifically distributed deep reinforcement learning (DDRL) and the asynchronous actor critic algorithm (A3C), we propose a low complexity algorithm that approximates the solution of the proposed optimization problem. The proposed DDRL-based algorithm endows every road side unit (RSU) with a local RL agent that selects a local action based on the observed input state. Actions of different RSUs are forwarded to a central entity, that computes a global reward which is then fed back to RSUs. It is shown that each independently trained RL performs the vehicle-RSU association action with low control overhead and less computational complexity compared to running an online complex algorithm to solve the non-convex optimization problem. Finally, simulation results show that the proposed solution achieves up to 15% gains in terms of sum rate and 20% reduction in VUE outages compared to several baseline designs.

  • Study on sharing and compatibility between ITS and Fixed Service

    Intelligent transportation system (ITS) is one of the most important applications in Internet of Things (IoT). In several regions and countries, the government authority is planning to allocate 5850-5925MHz to ITS. In order to meet the requirements of ITS in this frequency band, no harmful interference could not be produced to the existing system. In this paper, the compatibility analysis between ITS and fixed service systems is studied in 5850-5925 MHz band. The research results show that the ITS and FS system can coexist at a certain isolation distance.

  • Design of a V2X Vehicle Antenna

    In this paper, we propose V2X shark-fin antenna that operated on vehicle roof. Propose antenna is composed of AM/FM Radio broadcasting, Digital Media Broadcasting (DMB), Global Positioning System (GPS), and dual V2X (Vehicle-to- everything) antennas. Propose antenna has -1.2 dBi in AM/FM Radio band, 5.8 dBi in DMB band, and 28 dBic in GPS band (Including Low Noise Amplifier). Especially designed antenna has -2.3 dBi average gain in V2X 1, -2.9 dBi average gain in V2X 2. V2X antenna's communication distance is 995~1329 m in Line-Of-Sight [LOS].

  • Can Beacons be Compressed to Reduce the Channel Load in Vehicular Networks?

    Significant efforts have been devoted to date to the congestion control problem in vehicular networks. The solutions proposed so far have been designed to adapt the communication parameters to reduce and control the channel load. A totally different approach would be the compression of the data generated by each vehicle. This paper proposes and explores for the first time the use of data compression to reduce the channel load in vehicular networks. By compressing and decompressing V2X messages, the channel load generated could be reduced, thereby decreasing the interference and packet loses due to collisions. We apply this idea in this study to CAMs using existing data compression tools to have a first estimate of the compression gain that could be achieved, and the time needed to compress and decompress. The results obtained show that the CAM length could be reduced by up to around 14%, which is a non-negligible percentage given the relevance of the congestion control problem. The data compression and decompression times obtained demonstrate its potential for its integration in V2X devices. The results obtained motivate to more deeply investigate the compression of V2X messages in vehicular networks.

  • Standardization Evolution and Typical Solutions of IoV

    The Internet of Vehicles (IoV) is changing the smart life on the wheels through multiple interactions among vehicle, road, people and network, providing a safer, more efficient and more energy-efficient driving experience. This paper introduces the standardization process of V2X and summarizes the key technologies of LTE-V2X. Additionally, two typical use case solutions of IoV are proposed, including remote driving and platooning.

  • Interference Aware Optimal Resource Allocation on V2X Networks

    In this work, optimum transmit power allocation in V2X networks to maximize the aggregate data rate in the V2I network without violating individual peak transmit power constraints on the V2I users and the interference power constraints on the V2V users is considered. In the proposed model, V2I users form a multiple-access channel to the roadside unit and cause interference in the V2V network. Under this setup, it is first shown that the data rate maximizing optimum power allocation vector lies at one of the vertices of the feasible set of all transmit power vectors. The structure derived for the optimum power allocation vectors simplifies the solution of the power optimization problem significantly. That is, calculating and comparing the data rates at the vertices of the feasible power set, the optimum power allocation vector can be derived for each channel state. Furthermore, with the entry of each new V2V user to the system, the number of vertices increases at most by 3. Time division multiple access solution as a special case appears by a subset of our solution. In the final part of the paper, the theoretical results obtained are utilized to give numerical performance figures for V2X networks.

  • On Latency and Reliability of Road Hazard Warnings over the Cellular V2X Sidelink Interface

    Decentralized Environmental Notification Messages (DENMs) are generated by a vehicle upon detection of an accident or other hazards on the road, and need to be promptly and reliably transmitted. Delayed or lost messages may have fatal consequences, especially in critical driving situations, such as automated overtake and emergency braking, when vehicles can be very close to each other. In this letter, the DENM latency and reliability performances are characterized over the Cellular Vehicle-to-everything (C-V2X) sidelink (PC5 interface). The conducted study uses analytical tools, among which stochastic geometry, to derive performance results, then validated by simulations. Results are applied to the case of DENMs for emergency electronic brake lights, and helpful insights are provided for this crucial case and for other more general DENM-assisted V2X use cases.

  • An Efficient GPS-Free Vehicle Localization Algorithm Using Single Roadside Unit and Receiver

    Accurate vehicle localization is critical for connected and autonomous vehicles of the future. But it is challenging, especially in global positioning system (GPS) denied or urban environments. In this paper, we propose an efficient GPS-free vehicle localization algorithm by exploiting vehicle-to-infrastructure communications. It is an on-board odometer and inertial measurement unit (IMU) assisted and single roadside unit (RSU) based approach. The available RSU position, speed vector and distance information between the RSU and vehicle are formulated as an over-determined system of linear equations. The linear least squares method is then utilized to estimate the vehicle position in a computationally efficient manner.



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