Interplay Between AI and Space-Air-Ground Integrated Network: The Road Ahead

TL;DR

This paper explores the integration of artificial intelligence with space-air-ground networks, proposing a generalized AI model and a management framework using SDN to enhance SAGIN's automation and resource management.

Contribution

It introduces a multi-task AI model for SAGIN and a SDN-based framework for resource management, addressing the interaction gap between AI and SAGIN.

Findings

Proposed a generalized AI model for SAGIN tasks

Developed a SDN-based resource management framework

Validated the framework through a real-world case study

Abstract

Space-air-ground integrated network (SAGIN) is envisioned as a key network architecture for achieving ubiquitous coverage in the next-generation communication system. Concurrently, artificial intelligence (AI) plays a pivotal role in managing the complex control of SAGIN, thereby enhancing its automation and flexibility. Despite this, there remains a significant research gap concerning the interaction between AI and SAGIN. In this context, we first present a promising approach for developing a generalized AI model capable of executing multiple tasks simultaneously in SAGIN. Subsequently, we propose a framework that leverages software-defined networking (SDN) and AI technologies to manage the resources and services across the entire SAGIN. Particularly, we demonstrate the real-world applicability of our proposed framework through a comprehensive case study. These works pave the way for the deep integration of SAGIN and AI in future wireless networks.