Research On Cross-Layer Optimazation Of Adaptive Streaming Service Based On QoE In LTE Network

With the rapid development of wireless network technology as well as the upgrade of multimedia user terminal video streaming service has become the mainstream of LTE business. The number of end users is growing and the user's demand for video quality of the business is also gradually increased. The contradiction between the shortage of wireless resources and the demands of users' quality of service becomes more and more serious, which brings great challenges to the development of wireless video services. Therefore, how to use limited wireless resources to meet the growing user experience quality requirements becomes the focus of current research. Aiming at the above problems, this paper proposes an adaptive cross-layer optimization scheme for streaming media services based on QoE. The cross-layer optimization scheme is studied in four aspects: business model, cross-layer algorithm, performance comparison and user experience.The main work of this paper consists of two parts: In the first part, we propose a cross-layer wireless resource allocation scheme with QoE as the objective of adaptive streaming media service. It includes: based on the work of literature, the mapping model is established between the PSNR and the parameters which are extracted from the application layer and the physical layer,and another mapping is established between the PSNR and the MOS value reflecting the user's subjective experience. Based on the MOS value of each user,a multiuser QoE utility function is established. Based on the QoE utility function,the greedy algorithm is successfully applied to the radio resource allocation. In the second part, this paper realizes the cross-layer wireless resource allocation scheme on the OAI platform and analyzes its performance. This part includes:Realizing the cross-layer optimization model and scheduling program of the first part. Building the adaptive streaming media business platform on the client side.On the server side to achieve the video coding, slicing and packaging work. The comparison of simulation result between the cross-layer resource allocation based on QoE and traditional scheduling can show that cross-layer optimization can get a better user experience and better fairness among multiple users.