Quality-of-Experience Evaluation for Digital Twins in 6G Network Environments

As wireless technology continues its rapid evolution, the sixth-generation (6G) networks are capable of offering exceptionally high data transmission rates as well as low latency, which is promisingly able to meet the high-demand needs for digital twins (DTs). Quality-of-experience (QoE) in this situation, which refers to the users' overall satisfaction and perception of the provided DT service in 6G networks, is significant to optimize the service and help improve the users' experience. Despite progress in developing theories and systems for digital twin transmission under 6G networks, the assessment of QoE for users falls behind. To address this gap, our paper introduces the first QoE evaluation database for human digital twins (HDTs) in 6G network environments, aiming to systematically analyze and quantify the related quality factors. We utilize a mmWave network model for channel capacity simulation and employ high-quality digital humans as source models, which are further animated, encoded, and distorted for final QoE evaluation. Subjective quality ratings are collected from a well-controlled subjective experiment for the 400 generated HDT sequences. Additionally, we propose a novel QoE evaluation metric that considers both quality-of-service (QoS) and content-quality features. Experimental results indicate that our model outperforms existing state-of-the-art QoE evaluation models and other competitive quality assessment models, thus making significant contributions to the domain of 6G network applications for HDTs.