A Content-Aware Bitrate Selection Method Using Multi-Step Prediction for 360-Degree Video Streaming  

作　　者：GAO Nianzhen YU Yifang HUA Xinhai FENG Fangzheng JIANG Tao 

机构地区：[1]Huazhong University of Science and Technology,Wuhan 430074,China [2]ZTE Corporation,Shenzhen 518057,China

出　　处：《ZTE Communications》2022年第4期96-109,共14页中兴通讯技术（英文版）

基　　金：supported in part by ZTE Corporation under Grant No.2021420118000065.

摘　　要：A content-aware multi-step prediction control(CAMPC)algorithm is proposed to determine the bitrate of 360-degree videos,aim⁃ing to enhance the quality of experience(QoE)of users and reduce the cost of video content providers(VCP).The CAMPC algorithm first em⁃ploys a neural network to generate the content richness and combines it with the current field of view(FOV)to accurately predict the probability distribution of tiles being viewed.Then,for the tiles in the predicted viewport which directly affect QoE,the CAMPC algorithm utilizes a multi-step prediction for future system states,and accordingly selects the bitrates of multiple subsequent steps,instead of an instantaneous state.Meanwhile,it controls the buffer occupancy to eliminate the impact of prediction errors.We implement CAMPC on players by building a 360-degree video streaming platform and evaluating other advanced adaptive bitrate(ABR)rules through the real network.Experimental results show that CAMPC can save 83.5%of bandwidth resources compared with the scheme that completely transmits the tiles outside the viewport with the Dynamic Adaptive Streaming over HTTP(DASH)protocol.Besides,the proposed method can improve the system utility by 62.7%and 27.6%compared with the DASH official and viewport-based rules,respectively.

关 键 词：DASH content-aware FOV prediction bitrate adaptation multi-step prediction generalized predictive control 

分 类 号：TN919.8[电子电信—通信与信息系统] TP393.09[电子电信—信息与通信工程]