Fine-Grained Reliability for V2V Communications around Suburban and Urban Intersections

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ITS, V2X, V2V, C-V2X, DSRC, VANET, 802.11p, 5G, LOS, WLOS, NLOS, CAV, URLLC, H2020, intelligent transportation system, connected vehicles, vehicle-to-everything, vehicle-to-vehicle, dedicated short-range communication, vehicular ad hoc network, path loss, propagation model, channel model, connected vehicle, autonomous vehicle, connected and autonomous vehicle, outage probability, reliability, ultra-reliable low-latency communication, stochastic geometry, meta distribution, road safety, traffic efficiency, urban intersection, suburban intersection, smart intersection, intelligent intersection, smart city, research funding, grant proposals, government funding, European Commission, EU, MSCA, Marie-Curie, Marie Skłodowska Curie Action


Safe transportation is a key use-case of the 5G/LTE Rel.15+ communications, where an end-to-end reliability of 0.99999 is expected for a vehicle-to-vehicle (V2V) transmission distance of 100-200 m. Since communications reliability is related to road-safety, it is crucial to verify the fulfillment of the performance, especially for accident-prone areas such as intersections. We derive closed-form expressions for the V2V transmission reliability near suburban corners and urban intersections over finite interference regions. The analysis is based on plausible street configurations, traffic scenarios, and empirically-supported channel propagation. We show the means by which the performance metric can serve as a preliminary design tool to meet a target reliability. We then apply meta distribution concepts to provide a careful dissection of V2V communications reliability. Contrary to existing work on infinite roads, when we consider finite road segments for practical deployment, fine-grained reliability per realization exhibits bimodal behavior. Either performance for a certain vehicular traffic scenario is very reliable or extremely unreliable, but nowhere in relatively proximity to the average performance. In other words, standard SINR-based average performance metrics are analytically accurate but can be insufficient from a practical viewpoint. Investigating other safety-critical point process networks at the meta distribution-level may reveal similar discrepancies.


Faculty of Applied Science and Technology (FAST)

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Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
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