Performance Modeling and Dimensioning of Latency-Critical Traffic in 5G Networks

We propose a new performance model for transport of time-critical Ultra Reliable Low Latency Communications (URLLC) traffic in 5G networks and Beyond and apply it to dimensioning of such systems. The Quality of Service (QoS) requirement is formulated in terms of an outage probability which is defined as the probability that the latency exceeds a maximal allowed budget, and which should be kept very low. We develop a generic queuing model to compute this outage probability and adapt it to integrate the specificity of the 5G radio interface, taking into account the heterogeneity of users radio conditions and thus their Modulation and Coding Schemes (MCS) as well as retransmissions due to errors on the radio link. We also propose a low complexity method to calculate it using a geometric tail approach to approximate the tail distribution of the queue, for relevant arrival distributions: Poisson and Binomial. We show numerically the performance of our exact model and approximation and that they yield very accurate performance against simulations, and in comparison with other models from the state of the art. We also show the system dimensioning in terms of required resources to satisfy the outage constraint.