Edge Intelligence for IoT Services in 6G Integrated Terrestrial and Non-Terrestrial Networks
Qian Liu, Sihong Wang, Zhi Qi, Kaisa Zhang, Qilie Liu
Abstract
Integrating terrestrial and non-terrestrial networks can provide a wide area of Internet of Things (IoT) services with global connections and ubiquitous communications. However, integrated terrestrial and non-terrestrial networks (ITNTNs) also face huge challenges caused by complex environments, diverse services, and heterogeneous nodes. By leveraging the powerful driving force of edge intelligence (EI) technology for network development, a framework named “ITNTNs with EI” is proposed in this paper as the solution to the challenges above. We design system architecture, dynamic edge resource deployment, and intelligent edge model training for the proposed framework and discuss its application scenarios, challenges, and some open research issues. Then, simulation experiments about a joint computation offloading and resource allocation optimization algorithm based on the DRL-based model are conducted for a specific framework instance. The results demonstrate that optimization management solutions driven by EI can provide faster response and greater quality of service for IoT applications in ITNTNs.