Dynamic Resource Allocation of eMBB-uRLLC Traffic in 5G New Radio

Abstract

5G technology is intended to support three promising services with heterogeneous requirements: Ultra-Reliable and Low Latency Communication (uRLLC), enhanced Mobile Broadband (eMBB) and massive Machine Type Communication (mMTC). The presence of these services on the same network creates a challenging task of resource allocation to meet their requirements. Given the critical nature of uRLLC applications, uRLLC traffic will always have the highest priority which causes a negative impact on the performance of other types of applications. In this paper, the problem of uRLLC/eMBB resource allocation is formulated as an optimization problem aiming to maximize the average throughput of eMBB User Equipment (UE) while satisfying the latency demands of uRLLC applications. A dynamic programming approach is used to achieve an optimal resource allocation for uRLLC traffic on a TTI level that minimizes its impact on eMBB average throughput in addition to preserving an acceptable level of fairness among eMBB UE. This approach is applied on top of heuristic scheduling algorithms where uRLLC traffic punctures pre-allocated resources of eMBB UE upon arrival. The effectiveness of the approach is evaluated using numerical simulations and the results show how it minimizes the impact of uRLLC traffic on the performance of these algorithms in terms of data rate, spectral efficiency, and fairness.