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Simulation and Modelling of various 5G-Mechanisms within the context of connected mobility

Project Description

The networking of vehicles with other road users or the infrastructure (Vehicle-to-Everything (V2X)) is one of the key technologies for autonomous driving and smart cities. The WLAN standard IEEE 802.11p developed for this purpose has already been the focus of research for a decade. So far, however, this communication technology has not been able to establish itself as a communication standard in the automotive industry. One possible reason for this is the non-existent stationary infrastructure (base stations at the roadside or at traffic lights), which would require high investments.

Many automobile manufacturers are therefore focusing their research on the latest generation of mobile radio technologies. The required infrastructure is available nationwide due to other mobile phone subscribers. LTE has already adopted specifications for direct communication between vehicles and communication via a base station. The latest mobile radio generation (5G), which is to be introduced from 2020, takes into account application cases and criteria for V2X communication right from the start. For 5G, the virtualization of mobile radio components via network slicing in conjunction with SDN and NFV will play a decisive role in maintaining quality of service parameters compared to LTE and WLAN.

For the simulation of V2X communication scenarios via WLAN IEEE 802.11p the Veins framework developed at the chair has been used in numerous studies. In order to evaluate comparisons between WLAN and mobile radio by simulation, a further development of Veins with the mobile radio technologies LTE/5G is of great interest. The focus here is in particular on questions of Quality of Service (QoS) and the planned V2X application cases. In the context of this doctoral thesis the Veins framework is extended to the 5G technology. The focus here is on mechanisms of the lower network layers and the planned network slicing and Quality of Service (QoS) approaches.

Project Period

    2017-10-01 – 2022-08-31

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