Performance analysis of Non-Standalone 5G network under different traffic models

Ongoing worldwide adoption of mobile devices has created an increased demand for access to e-commerce, social media, and entertainment applications anywhere, at any time. Mobile traffic that was traditionally voice-only is now dominated by video and data owing to applications like live video streaming, Netflix, Facebook, Twitter, and mobile browsing. As the number of subscribers grows, so too does the demand for an enhanced user experience with differentiated service levels. To achieve this, the mobile network elements must incorporate techniques to manage the diverse traffic characteristics of the growing range of multimedia applications and services. Analyzing the performance of the mobile network can enable efficient deployment and optimization. The aim of this paper is to analyze the performance of the 5G nonstandalone (NSA) network, in terms of average throughput and delay, under different traffic models, including real-time and non-real-time traffic, as the number of users increases. These analyses we make help us understand how the requirements of the network vary as the traffic generated by different users’ changes, to have a proper deployment, optimization, and the techniques used to guarantee the best user experience. Further in the paper, we analyze different scheduling schemes and the effect that each algorithm has on the network under different traffic models. The estimation is done in terms of the average user and cell throughput, delay, and fairness.