A Comparison of the V2X Communication Systems: ITS-G5 and C-V2X

Mannoni, Valérian; Berg, Vincent; Sesia, Stefania; Perraud, Eric

doi:10.1109/vtcspring.2019.8746562

Cited by 120 publications

(76 citation statements)

References 5 publications

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“…Another CAM message size distribution obtained through a field test can be found in [19]. This case is not as extensive as the previous one but shows a histogram where about 70% of CAMs have sizes around 190 bytes, about 20% with sizes close to 320 bytes, and the remaining 10% have sizes between 350 bytes and 660 bytes.…”

Section: Analysis Of Etsi Its Protocol Stack Traffic Characteristicsmentioning

confidence: 77%

Understanding the Impact of the PC5 Resource Grid Design on the Capacity and Efficiency of LTE-V2X in Vehicular Networks

Lopez

Mendoza

Casademont

et al. 2020

Wireless Communications and Mobile Computing

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Vehicular communications will foster mobility services and enable mass adoption of future autonomous vehicles, interchanging huge amount of data acquired from vehicles’ sensors. 3GPP Release 14 presents the first standard for supporting V2X in LTE. Several enhancements are introduced, including a new arrangement of the physical resource grid, where subchannels are the minimum resource unit instead of Resource Blocks. The resource grid is defined by several design parameters, some of them with constraints imposed by 3GPP specifications, that affect the maximum message transmission rate and efficiency of the system. Moreover, the optimum choice of these parameters is closely linked to message length, which is another variable parameter. This paper provides an analysis of the relationship between these design parameters (Resource Block per Subchannel, Transport Block Size Index, and coding rate), message size, and the system’s maximum capacity and efficiency. In doing so, we do not consider channel reuse or radio transmission characteristics because the focus of this paper is trying to find the resource grid design parameters that optimize system capacity, which is a very important aspect to consider by V2X operators.

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Section: Analysis Of Etsi Its Protocol Stack Traffic Characteristicsmentioning

confidence: 77%

Understanding the Impact of the PC5 Resource Grid Design on the Capacity and Efficiency of LTE-V2X in Vehicular Networks

Lopez

Mendoza

Casademont

et al. 2020

Wireless Communications and Mobile Computing

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“…It should also be noted that the C-V2X uses a Turbo-code which has per definition better performance than the convolutional code used by ITS-G5. A performance synthesis using more physical layer configurations in particular for C-V2X is given in [3].…”

Section: B Physical Layer Resultsmentioning

confidence: 99%

“…In the following, Section II briefly introduces the physical layer parameters and the simulation comparison. Extended analysis can be found in [3]. Section III introduces system level simulation set up based on urban topology, and Cooperative Awareness Applications (based on CAM messages); it describes the system level simulation principles with a specific focus for each technology in Section III-D for LTE-V2X and Section III-E for 802.11p and it provides the system level performance evaluation.…”

Section: Introductionmentioning

confidence: 99%

System Level Analysis for ITS-G5 and LTE-V2X Performance Comparison

Roux

Sesia

Mannoni

et al. 2019

2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)

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Vehicular communications, known under the name of V2X (Vehicle to Everything) are expected to grow fast in the next years, bringing for example safer driving conditions, optimized traffic management, energy reduction, etc.. Currently two short range-based technologies (ITS-G5, standardized in Europe by ETSI and derived from WiFi communications IEEE standards and LTE based Vehicle to Everything or LTE-V2X developed by 3GPP and derived from LTE) consider the use of 5.9 GHz ITS band for their deployment. While different countries are more or less advanced in terms of regulation definition for Intelligent Transport System (ITS), it seems clear that the same solution will not be necessarily worldwide deployed. This study compares performances of both technologies by means of system level simulation, in particular considering the European ITS-G5 protocol stack specification. In order to analyze system level performance, physical layer simulation is used to provide Packet Delivery Rate (PDR) versus Signal to Noise plus Interference Ratio (SINR). Then PDR curves are exploited to feed system level simulation aimed at providing statistics about Cooperative Awareness Message (CAM) transmission reliability, in typical urban scenario. The paper provides a brief description of the systems together with the definition of the assumptions and the key results related to the physical layer analysis; it follows with the description of the NS-3 simulator models used for system level simulation (with particular emphasis on PC5 Mode 4) and the discussion about the results which provide insight about the expected and the simulated behavior of both technologies, in particular comparative statistics with regards to CAM success ratio versus maximum communication distance are provided in order to compare the performance.

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“…In this context, Vehicle-to-everything (V2X) communication [89] is defined as information transmission from a vehicle to any entity that may affect the vehicle, and vice versa (Figure 7). It is a vehicular communication system that incorporates other more specific types of communication as V2I (vehicle-to-infrastructure), V2N (vehicle-to-network), V2V (vehicle-to-vehicle), V2P (vehicle-to-pedestrian), V2D (vehicle-to-device), and V2G (vehicle-to-grid).…”

Section: Integration Of Autonomous Vehiclesmentioning

confidence: 99%

A Comprehensive Study on Simulation Techniques for 5G Networks: State of the Art Results, Analysis, and Future Challenges

2020

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Ιn this review article, a comprehensive study is provided regarding the latest achievements in simulation techniques and platforms for fifth generation (5G) wireless cellular networks. In this context, the calculation of a set of diverse performance metrics, such as achievable throughput in uplink and downlink, the mean Bit Error Rate, the number of active users, outage probability, the handover rate, delay, latency, etc., can be a computationally demanding task due to the various parameters that should be incorporated in system and link level simulations. For example, potential solutions for 5G interfaces include, among others, millimeter Wave (mmWave) transmission, massive multiple input multiple output (MIMO) architectures and non-orthogonal multiple access (NOMA). Therefore, a more accurate and realistic representation of channel coefficients and overall interference is required compared to other cellular interfaces. In addition, the increased number of highly directional beams will unavoidably lead to increased signaling burden and handovers. Moreover, until a full transition to 5G networks takes place, coexistence with currently deployed fourth generation (4G) networks will be a challenging issue for radio network planning. Finally, the potential exploitation of 5G infrastructures in future electrical smart grids in order to support high bandwidth and zero latency applications (e.g., semi or full autonomous driving) dictates the need for the development of simulation environments able to incorporate the various and diverse aspects of 5G wireless cellular networks.

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A Comparison of the V2X Communication Systems: ITS-G5 and C-V2X

Cited by 120 publications

References 5 publications

Understanding the Impact of the PC5 Resource Grid Design on the Capacity and Efficiency of LTE-V2X in Vehicular Networks

Understanding the Impact of the PC5 Resource Grid Design on the Capacity and Efficiency of LTE-V2X in Vehicular Networks

System Level Analysis for ITS-G5 and LTE-V2X Performance Comparison

A Comprehensive Study on Simulation Techniques for 5G Networks: State of the Art Results, Analysis, and Future Challenges

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