Towards Dynamic Real-Time Latency Bounds in 5G Communication

Wireless systems require strict latency bounds for safety-critical applications, particularly in dynamic environments involving moving user equipment (UE) such as autonomous vehicles. Solutions in 5G mainly focus on static scheduling approaches in that regard, making them inapplicable for dynamic environments. However, latency in these dynamic settings is often unpredictable, creating a real challenge, as the need for safety is increased for moving systems, while at the same time, it is more challenging to ensure. Existing approaches typically detect latency violations after they occur, which is insufficient for real-time responsiveness, as it delays the reaction of UEs. This paper proposes a novel method to predict latency in 5G wireless communication before transmission, enabling proactive safety measures. Our approach proposes modeling of resource scheduling from a real-time perspective to apply analytical latency calculation. We introduce formulas for predicting latencies for future time intervals and discuss how to determine bandwidth relevant to latency in 5G communication. The accuracy of our latency predictions thus is dependent on forecasting the available bandwidth and traffic load. However, our studies using real-world data show that our approach results in high precision, as 95.93% of our predictions match the experienced delay, making our solution applicable for real-world deployment.