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.
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