A QoE-Driven Encoder Adaptation Scheme for Multi-User Video Streaming in Wireless Networks

Video streaming over networks has grown rapidly in recent years. Increasing focus has gradually turned from quality of service awareness to end viewer's quality of experience (QoE) awareness. For multi-user video streaming services, videos are encoded and transmitted through a bandwidth-limited wireless networks. Therefore, proper encoder settings for videos are required to satisfy the total channel rate constraint. In this paper, a QoE-driven High Efficiency Video Coding (HEVC) encoder adaptation scheme is proposed, aiming to maximize QoE of all the users for wireless networks. First, the influence of HEVC encoder on video streaming is investigated to generate an encoder parameter model. Then, the effect of network impairment together with HEVC encoder is taken into account to derive a subjective QoE prediction model. Afterward, we formulate a QoE-maximized encoder adaptation with total channel rate constraint into an optimization problem based on the obtained encoder parameter model and the subjective QoE model. The problem is solved and incorporated into an online encoder adaptation scheme. Compared with conventional rate allocation methods, the proposed QoE-driven encoder adaptation scheme achieves significant QoE gains independent of wireless network channel rate and video content. Simulation results demonstrate that the proposed encoder adaptation scheme can improve the QoE by 31.4% with fixed number of users or increase the number of satisfied users by 35.5% with variable number of users.