Pioneering Air-Ground Integrated Mobility: A Knowledge-Driven Space-Air-Ground Integrated Network for 6G On-Demand Service

Zifan Sha, Changle Li, Wenwei Yue, Nan Cheng, Yilong Hui, Aoyu Pang, Man-On Pun, Zhili Sun, Yang Yang

Abstract: In order to improve the bearing capacity of current transportation system and the efficiency of production and living, it is imperative to construct a new type of transportation system combined with the near-ground space (NGS), among which the air-ground integrated mobility (AIM) is a typical representative in 6G era. However, in catering to the extensive AIM services with customized requirements, there is an urgent need for the support of novel network architectures endowed with the capabilities of network collaboration and endogenous intelligence. In light of this, we propose a knowledge-driven space-air-ground integrated network architecture for AIM (AIM-SAGIN), which divides into six network layers and integrates multi-tier AI controllers for achieving efficient collaboration. Moreover, this article presents the knowledge-driven logical network structure for AIM-SAGIN. Specifically, we add the knowledge plane to conventional planes, aiming at enhancing the awareness and optimization of integrated sensing, communication, computing, and control (ISCCC) strategies for AIM control. Besides, a digital management and control platform for AIM services is constructed, which can realize the real-time mapping of digital domain and on-demand strategies for AIM-SAGIN. In addition, simulations are conducted to verify system end to end delay and service satisfaction rate of AIM-SAGIN, which demonstrates the performance gains brought by network collaboration with knowledge and AI controllers, as well as reveals the balance between transmission efficiency and computational complexity. Finally, we discuss some useful enabling technologies and open challenges for AIM-SAGIN.

External IDs:dblp:journals/network/ShaLYCHPPSY25