Analysis of Location based QoE for Mobile video streaming from YouTube in 4G Networks

Abstract: Mobile Video streaming has become popular with the arrival of high capability smart phones on Mobile Networks. Users are streaming high definition (HD) videos and have high expectations on Mobile Quality of Experience (QoE). Fourth Generation Mobile Networks are being deployed recently in many regions of the world and have capability to efficiently handle high definition video traffic. YouTube is one of the most extensively used Video on Demand Service on smart phones where wide range of people do video streaming. Most of the QoE experiments on 4g networks have been conducted in lab environment but they do not capture the daily routine of user experience on viewing videos. The user experiments in this thesis are conducted in natural life settings to capture Quality of Experience based on context of the user location. User experiments are designed and conducted for collecting Mean Opinion scores (MOS) in four different context based locations and have been collected using Experience Sampling Method (ESM). The Contribution of thesis is applying linear mixed effect Modeling on data collected to develop Quality of Experience (QoE) models of video streaming for Mobile YouTube on 4G Network. This thesis is one of the first works on modeling QoE experience at different context based physical locations in natural settings for mobile YouTube video streaming in 4G networks.