Improving QoS of 5G Video Streaming Through Network Exposure Function.

Ultra-low latency video delivery in such places as stadiums is catching much attention because of 5G's ability for isolating network resources per usage scenario via network slicing to satisfy required QoS. However, network slicing in wireless environment poses significant challenges as the radio characteristics dynamically changes. In particular, video transmission is highly susceptible to the impact of wireless environment changes such as packet loss caused by e.g., camera movement. While 5G specifies a static 5G QoS Identifier (5QI) for each network slice, static QoS settings are insufficient for ensuring stable video delivery. To address this issue, we propose a strategic and dynamic selection of 5QI through the Network Exposure Function (NEF) according to the wireless environment to improve video streaming quality. By collecting network data from User Equipment (UE) and sink devices, our proposed method adjusts 5QI and improves transmitted video quality. Our approach utilizes Private 5G where we can customize UE and utilize NEF to achieve stable video delivery. Our proposed method reduces packet loss under low radio-quality conditions, improving the ITU-T G.1072 Predicted Gaming Mean Objective Score (MOS), which considers both delay and image quality, from 1.12 to 2.14, even in degraded radio conditions. It indicates the usefulness of our proposed method in improving video transmission stability. We plan to identify the requirements for dynamic 5QI control via NEF so that we can propose the same scheme for public 5G environment.