Research

Fifth Generation New Radio (5G NR) presents a new framework for Quality-of-Service (QoS) management that especially fits cases for eXtended Reality (XR) traffic applications thanks to the new presented concept of QoS flows that can handle various service data flows. In that respect, in this paper we exploit the QoS flow model and we present a QoS MAC scheduler that can classify XR and mixed traffic based on the assigned QoS indicators to each traffic. We perform an end-to-end system level evaluation under two scenarios using the ns-3 5G-LENA simulator. First, we validate the correct operation of the QoS MAC scheduler in a single-cell scenario under non-saturation and saturation conditions. Then, we consider a realistic multi-cell scenario defined by the ITU-R and used for calibration of the 5G-LENA simulator, in order to evaluate the proposed solution and study its performance under realistic network conditions. Results demonstrate the correct functionality of the proposed QoS MAC scheduler and prove its ability to classify XR and other types of traffic based on the desired QoS indicators.