QoE Aware Video Adaptation For Video Streaming in 5G Networks

The popularity of video streaming has skyrocketed as an outcome of the increased demand for use of wireless devices such as smartphones and tablets etc. As a result, perplexing video applications like remote surgery, mobile broadcasting, real-time demand, delivery of Ultra High Quality, and Augmented Reality are predicted to control the traffic of mobile networks in the future generation (5G). This is because video applications currently account for more than 70% of IP-based internet traffic, and by 2021, they are expected to account for more than 80%. In addition, mobile device traffic is expected to increase by 10%. As the demand for mobile video consumption grows, 5G networks will require larger bandwidths, improved dependability, and reduced end-to-end delay. Despite considerable improvements in QoS, network operators will continue to face significant issues as 5G video traffic grows in volume. As a result, the focus of network quality has shifted in recent days from network provider QoS to Quality of Experience (QoE), culminating in the QoE predictive model. The assumption for 5G networks is that they shall be capable of delivering Ultra Hd video streaming and the QoE-aware techniques shall be able to match the user’s anticipated quality standard. The purpose of this research is to study, give a broad overview of the many QoE aware adaptive video streaming systems available today, as well as their current trends, and implement an adaptive video streaming system that could enhance the QoE and user perception using a SDN platform.