Quality-Aware Massive Content Delivery in Digital Twin-Enabled Edge Networks  

作　　者：Yun Gao Junqi Liao Xin Wei Liang Zhou 

机构地区：[1]School of Communications and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China [2]Key Laboratory of Broadband Wireless Communication and Sensor Network Technology,Ministry of Education,Nanjing University of Posts and Telecommunications,Nanjing 210003,China

出　　处：《China Communications》2023年第2期1-13,共13页中国通信（英文版）

基　　金：partly supported by the National Natural Science Foundation of China (Grants No.62231017 and No.62071254);the Priority Academic Program Development of Jiangsu Higher Education Institutions。

摘　　要：Massive content delivery will become one of the most prominent tasks of future B5G/6G communication.However,various multimedia applications possess huge differences in terms of object oriented(i.e.,machine or user)and corresponding quality evaluation metric,which will significantly impact the design of encoding or decoding within content delivery strategy.To get over this dilemma,we firstly integrate the digital twin into the edge networks to accurately and timely capture Quality-of-Decision(QoD)or Quality-of-Experience(QoE)for the guidance of content delivery.Then,in terms of machinecentric communication,a QoD-driven compression mechanism is designed for video analytics via temporally lightweight frame classification and spatially uneven quality assignment,which can achieve a balance among decision-making,delivered content,and encoding latency.Finally,in terms of user-centric communication,by fully leveraging haptic physical properties and semantic correlations of heterogeneous streams,we develop a QoE-driven video enhancement scheme to supply high data fidelity.Numerical results demonstrate the remarkable performance improvement of massive content delivery.

关 键 词：content delivery digital twin edge networks QoD QOE 

分 类 号：TN929.5[电子电信—通信与信息系统]