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  4. QoS Evaluation and Prediction for C-V2X Communication in Commercially-Deployed LTE and Mobile Edge Networks
 
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2020
Conference Paper
Title

QoS Evaluation and Prediction for C-V2X Communication in Commercially-Deployed LTE and Mobile Edge Networks

Abstract
Cellular vehicle-to-everything (C-V2X) communication is a key enabler for future cooperative automated driving and safety-related applications. The requirements they demand in terms of Quality of Service (QoS) performance vary according to the use case. For instance, Day-1 applications such as Emergency Brake Light warning have less strict requirements than remote driving. In this paper, we seek to answer two questions: Are current LTE networks ready to support Day-1 applications at all times? And, can underperforming situations be reliably predicted based on GPS and network-related information? To address these questions, we first implement a system that collects positioning data and LTE key performance indicators (KPIs) with a higher time resolution than commercial off-the-shelf LTE modems, while simultaneously measuring the end-to-end (E2E) delay of an LTE network. We then use this system to assess the readiness of multiple mobile network operators (MNOs) and a live Mobile Edge Computing (MEC) deployment in an urban scenario. For evaluating whether an adaptable operation is possible in adverse circumstances, e.g., by performing hybrid networking or graceful degradation, we finally use Machine Learning to generate a client-based QoS predictor and forecast the achievable QoS levels.
Author(s)
Torres-Figueroa, Luis
Fraunhofer-Institut für Kognitive Systeme IKS  
Schepker, Henning F.
Fraunhofer-Institut für Kognitive Systeme IKS  
Jiru, Josef  
Fraunhofer-Institut für Kognitive Systeme IKS  
Mainwork
IEEE 91st Vehicular Technology Conference, VTC2020-Spring. Proceedings  
Funder
Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie StMWi  
Conference
Vehicular Technology Conference (VTC Spring) 2020  
Open Access
DOI
10.24406/publica-r-408347
10.1109/VTC2020-Spring48590.2020.9129382
File(s)
N-593528.pdf (3.47 MB)
Rights
Under Copyright
Language
English
Fraunhofer-Institut für Kognitive Systeme IKS  
Keyword(s)
  • cellular vehicle-to-everything

  • C-V2X communication

  • OpenAirInterface

  • Long Term Evolution

  • LTE

  • mobile edge computing

  • MEC

  • quality of service

  • QoS

  • QoS prediction

  • machine learning

  • Software Defined Radio

  • SDR

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