计算机工程与应用 ›› 2025, Vol. 61 ›› Issue (13): 46-61.DOI: 10.3778/j.issn.1002-8331.2411-0460

• 热点与综述 • 上一篇    下一篇

空天地网络智能流量卸载技术研究综述

贾哲源,金凤林,何源   

  1. 中国人民解放军陆军工程大学 指挥控制工程学院,南京 210007
  • 出版日期:2025-07-01 发布日期:2025-06-30

Survey of Intelligent Traffic Offloading Technology in Space-Air-Ground Networks

JIA Zheyuan, JIN Fenglin, HE Yuan   

  1. College of Command & Control Engineering, Army Engineering University of PLA, Nanjing 210007, China
  • Online:2025-07-01 Published:2025-06-30

摘要: 随着地面网络流量需求的日益增长,传统地面网络服务难以满足用户需求。为了提供高质量的网络覆盖,空天地网络迅速发展,其中,利用流量卸载技术缓解地面网络通信压力成为当前的研究热点。此外,人工智能技术的引入为解决流量卸载中的复杂问题提供了解决方案。对空天地网络中智能流量卸载技术的研究进展进行全面综述,梳理了流量卸载技术的应用场景和智能方法应用,对不同场景中流量卸载技术的特点进行了全面梳理和分析,从智能化方法应用的角度分析了现有的流量卸载技术,并归纳了不同方法的特点和适用场景。基于上述研究,提出了未来空天地网络中智能流量卸载技术所面临的挑战,同时对未来的研究方向进行了展望。

关键词: 空天地网络, 流量卸载, 人工智能, 强化学习

Abstract: Due to the growing demand for terrestrial network traffic, traditional ground network services struggle to satisfy user requirements. Space-air-ground integrated network (SAGIN) are evolving quickly to offer high-quality, extensive coverage. Traffic offloading technologies are now a focal point in research to ease the burden on terrestrial networks. The fast development of artificial intelligence (AI) provides effective approaches to the intricate issues in traffic offloading. This article reviews the advancements in intelligent traffic offloading technologies within SAGINs. It outlines the application scenarios for traffic offloading and the use of intelligent methods, analyzing the characteristics of these technologies across different settings. Based on the application of intelligent methods, it examines current traffic offloading technologies, summarizing their features and suitable scenarios. Lastly, it identifies the challenges for intelligent traffic offloading in future SAGINs and suggests potential research directions.

Key words: space-air-ground integrated network(SAGIN), traffic offloading, artificial intelligence, reinforcement learning