Channel Models for the Simulation of Different RATs Applied to Platoon Emergency Braking

We analyze the performance of different channel models and Radio Access Technologies (RATs) for platoon emergency braking in a highway scenario. We present a ray tracing channel model and analyze its differences with the WINNER+ stochastic channel model in terms of the pathloss calculation. Thanks to the consideration of obstacles and their reflections, the ray tracing channel model has been shown to be more realistic in near Tx-Rx distance. This corroborates the results of our performance comparison which highlights larger differences in close Tx-Rx pairs. Considering the simulation time consumption and the more realistic ray tracing predictions, we propose a new models usage for our simulations: a combination of WINNER+ and ray tracing channel models. Moreover, we implement one new 5G numerology on the basis of Long Term Evolution-Vehicles (LTE-V) for Vehicle-to-everything (V2X) communications. We include this new feature in our benchmarking setup and provide performance analysis results. It provides a basis for our future research of further 5G components

Packet Inter-Reception Time Modeling for High-Density Platooning in Varying Surrounding Traffic Density

A recent feature of communications systems is the agile quality of service adaptation, in which the application and the communications system exchange requirements and prediction of quality of service. The application first provides its quality of service requirement. The communications system tries to enforce it, and makes a prediction of the available quality of service. Finally, the application adapts its settings to the future quality of service and provides updated requirements. Though this concept is originally designed for cellular-based technologies, it is also applicable to ad-hoc communication systems. In this paper, we focus on the prediction of quality of service for ad-hoc communications in a high-density platooning system. The quality of service of interest is the packet inter-reception time in an IEEE 802.11p network. Our platooning system drives through different vehicular traffic conditions, in which we gather transmission and position data. We then analyze the distribution of the packet inter-reception time to select the model features and then fit multiple distribution models. This empirical prediction modeling will then be the baseline for future modeling

Sidelink Technologies Comparison for Highway High-Density Platoon Emergency Braking

We present a benchmarking framework for different radio access technologies (RATs) in a high density platooning (HDPL) emergency braking use case. We assess the performance of IEEE 802.11p as well as LTE-V managed mode (mode 3) and unmanaged mode (mode 4) for sidelink communications. The performances are studied in terms of delays, packet error rates (PERs) and unctional safety indicators.We first vary the number of vehicles, the surrounding traffic and the inter-vehicle distance. Multiple traffic scenarios are then investigated for the most challenging conditions. We find that for reasonable surrounding traffic, the platoon is generally safe in this emergency scenario, although packet error rates are growing for IEEE 802.11p and LTE-V mode 4 as the traffic intensifies, along with delays for the former technology. Thanks to scheduling, LTE-V mode 3 is not affected by this increasing PER and shows a large constant delay: the scheduling delay. With this study, we pave the way for a further study of these radio technologies with more accurate channel models as well as including new 5G components in our benchmarking