Abstract
The support for reliable communication in the increasingly large fleets of autonomous vehicles is one of the important challenges for emerging 5G systems. The presence of heterogeneous data streams of different priority between the connected vehicles (coordinated autonomous driving, platooning, passenger entertainment services, etc.) calls for new methods to estimate the performance characteristics of these systems. In this article, a novel mathematical framework is proposed to model the process of dynamic radio resource (re-)allocation across multiple competing data streams in autonomous vehicular fleets equipped with 5G cellular capabilities. The developed framework is subsequently applied to: (i) study the coexistence of multiple traffic types having different service requirements and (ii) quantify the impact of session prioritization schemes. Our study reveals that the prioritization scheme initially offloading high-rate entertainment sessions, named ESpreempt, in most of the setups achieves a 5-30% performance gain in comparison with the scheme initially offloading low-rate platooning sessions, named PSpreempt. It is also shown that higher variations in the traffic load of autonomous driving sessions have a distinctly negative impact on system-level performance. The outlined framework can be applied in a wide range of 5G vehicular scenarios, as well as extended to capture other categories of data streams in future wireless networks.
Highlights
The envisioned emergence of connected autonomous vehicles is one of the major disruptions introduced on the way from 4G and 4G+ to the 5G-grade communication systems [1]–[3]
Our study considers three heterogeneous data streams coming from connected vehicles: (i) mission-critical traffic related to collective autonomous driving; (ii) platooning traffic between the vehicles and the road-side infrastructure; and (iii) multimedia data streams for in-vehicle entertainment systems
MAIN NUMERICAL RESULTS we report on the illustrative numerical results that characterize the main metrics of interest in the considered system, where multi-service data streams associated with the fleet of intelligent autonomous vehicles are handled simultaneously by the 5G mmWave cellular network
Summary
The envisioned emergence of connected autonomous vehicles is one of the major disruptions introduced on the way from 4G and 4G+ to the 5G-grade communication systems [1]–[3]. One of the key challenges in achieving sustainable network performance is to effectively share the resources among multi-service data streams with intelligent admission control and session management procedures [21] Such sharing needs to provide guaranteed reliability levels for mission-critical vehicular communication, while at the same time not hindering the operation of other network services [22]. We analyze intelligent admission control and session management procedures that aim to accept the new session for service only when there are sufficient radio resources available to serve this session For this purpose, we develop a mathematical framework that is capable of evaluating a wide range of performance characteristics, with a particular emphasis on serving multi-service data streams in large fleets of connected autonomous vehicles.
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