How to Improve Immersive Experience?

With the explosive growth of online multi-modal applications that typically include audio, video, and haptic signals, immersive experience (IE) improvement has been broadly regarded as one of the most important tasks. Compared with traditional quality of experience (QoE) improvement for online audio/video applications, it highlights two sequential technical challenges to be resolved: i) much more stringent demand of real-time improvement due to the incorporation of delay-sensitive haptic signals, and ii) high-dimensional instead of existing one-dimensional (i.e., network-level) paradigm for better online improvement. To get over this dilemma, this work systematically addresses the following three fundamental problems: i) which factors influence IE, ii) how to online improve IE, and iii) to what extent of the corresponding IE improvement can be achieved. To this end, we first comprehensively explore and categorize the influence factors on IE from various dimensions. Then, by combing network resource scheduling with the multi-domain collaboration of user profile, device specification, and application type, an online IE improvement strategy is proposed based on the efficient linear contextual bandit with the $L_{1}$-norm estimation. Finally, we derive the theoretical bound of IE improvement, scaling at a poly-logarithmical function of data dimension. Numerical results on the practical system also demonstrate the remarkable improvement on IE.