Proactive Application Rate Requirement Adaptation Mechanism for Sidelinks

Advanced wireless communication use cases relying on sidelinks require guaranteed network performance. However, fulfilling the desired Quality-of-Service (QoS) requirements can-not be always ensured due to factors such as varying interference and dynamicity in the network. To reduce the impact of varying network performance on sidelink applications, we address the problem of long-term proactive adaptation of sidelink applications based on network performance. Specifically, we propose a modular algorithmic framework comprising of data-driven prediction models and model-based optimization to predict the feasibility of given application data rate requirements. Further-more, the framework is capable of predicting the simultaneously achievable data rate demands (in the max-min sense). A vehicular communication scenario is considered as an example to show the applicability of the framework. Evaluations show that variations in feasibility and achievable data rate demands can be well captured to enable robust application layer adaptations.