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Feasibility study of V2X communications in initial 5G NR deployments
Date
2023
Abstract
Advancements in intelligent vehicles and Intelligent Transport Systems (ITS) have shown that they are now feasible in both technology and commerce. However, there are still significant challenges to overcome, particularly regarding the perception and coordination of intelligent vehicles in unfavourable conditions. Vehicle-to-Everything (V2X) communications is a technology that aims to enable intelligent vehicles to communicate with other road users and infrastructure to increase their range of perception and coordination capabilities. While the 4th generation of cellular technology (4G LTE) is capable of supporting V2X communications to some extent, its multimedia and telephony-centric design does not translate well to safety-critical applications. As a result, the 5th generation of cellular technology (5G NR) is being developed to improve V2X communications. To investigate the effectiveness of 5G NR in V2X communications, a driving-based measurement campaign of a commercial cellular network with early 5G NR deployments was conducted. Results showed that the existing 4G LTE network is limited in its capability, and early 5G NR deployments can in fact outperform it. However, neither 4G LTE nor 5G NR can reliably support advanced V2X applications. Early 5G NR deployments suffer from significant reliability issues compared to existing 4G LTE deployments. These reliability issues are of particular concern, as they impact the vehicle’s ability to trust the information it receives. These findings highlight the need for further design and implementation of intelligent vehicles and future 5G NR networks to address these reliability concerns and ensure the safe and efficient operation of intelligent vehicles in all conditions.
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Publisher
IEEE Computer Society
Citation
IEEE Access, 2023, 11, pp. 75269 - 75284
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Funding Information
This work was supported by the Connaught Automotive Research (CAR) Group, University of Galway; in part by the Science Foundation Ireland under Grant 13/RC/2094_P2; and in part by the European Regional Development Fund through the Southern and Eastern Regional Operational Programme to Lero, the Science Foundation Ireland Research Centre for Software (www.lero.ie).
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Type
Article
Rights
https://creativecommons.org/licenses/by-nc-sa/4.0/
