Research On Promoting Quality Of Experience In Mobile Network

With the popularization of3G in China, the bearer content of mobile network shall transfer gradually from traditional voice service to data service. Abundant operation experience accumulated in2G era of mobile network operators (MNOs) is unable to meet the need of new business. The MNOs pay attention to quality of experience (QoE) from end to end rather than network KPIs, such as switch rate, drop rate, speech quality and so on. Though the scholars and standardization organizations in this field have done massive exploration, but they still couldn’t put out an authoritative theory system in measure and evaluation of mobile users’ quality of experience. Related research is now under way.For the above reasons, this thesis focuses on quality of experience based on objective factors. For a start, we analyzed various influence factors of the user experience from tnree stages:purchase, use and feedback, including user categories, service classification. Second, we constructed QoE evaluation hiberarchy based on MNOs’network and business. Some standardization organizations published their achievements of research in tthis field. On the basis of the research of predecessors, we built a new evaluation hiberarchy according to double factor theory, dividing the influence factors into network layer indicators and application layer indicators, respectively corresponding to hygiene factors and motivator factors. Then we concluded that QoE would be ensured only when network layer indicators had exceeded a set threshold. Meanwhile, improvements of application layer indicators could make users feel better. Third, considering technical factors and non-technical factors, we constructed quantitative evaluation structure of QoE, and analyzed the collected data using wavelet neural network and fuzzy analytic hierarchy process (FAHP) respectively. The conclusion of these two methods was basically consistent, except moderately data. Fourth, In TD-SCDMA, for example, we introduced many kinds of optimal methods from aspect of technology, aspect of operation maintenance and aspect of management to improve the QoE of users. At last, we analyzed the impact of QoE in growth of the3G user number through open data and predicted the increasing rule using exponential model, the least square method and Logistic model separately. We concluded that short-term prediction of the least square method is remarkable accuracy in3G user forecasts of volume and2013-2014is the fastest-growing stage. By analyzing the data, we believed that QoE had some effects to increasing of user volume and considerable influence to ARPU.