Space communications, particularly mega satellite networks, re-emerged as an appealing candidate for next generation networks due to major advances in space launching, electronics, processing power, and miniaturization. However, mega satellite networks rely on numerous underlying and intertwined processes that cannot be truly captured using conventionally used models, due to their dynamic and unique features such as orbital speed, inter-satellite links, short time pass, and satellite footprint, among others. Hence, new approaches are needed to enable the network to proactively adjust to the rapidly varying conditions associated within the link. Artificial intelligence (AI) provides a pathway to capture these processes, analyze their behavior, and model their effect on the network. This article introduces the application of AI techniques for integrated terrestrial satellite networks, particularly mega satellite network communications. It details the unique features of mega satellite networks, and the overarching challenges concomitant with their integration into the current communication infrastructure. Moreover, the article provides insights into state-of-the-art AI techniques across various layers of the communication link. This entails applying AI for forecasting the highly dynamic radio channel, spectrum sensing and classification, signal detection and demodulation, inter-satellite link and satellite access network optimization, and network security. Moreover, future paradigms and the mapping of these mechanisms onto practical networks are outlined.

翻译：空间通信，特别是巨型卫星网络，因空间发射、电子技术、处理能力及微型化方面的重大进展，重新成为下一代网络的有力候选方案。然而，由于其轨道速度、星间链路、短时过顶及卫星覆盖范围等动态独特特征，巨型卫星网络依赖大量且相互交织的底层过程，传统模型难以真实捕捉。因此，需要新型方法使网络能够主动适应链路中快速变化的条件。人工智能提供了一条途径来捕捉这些过程、分析其行为并建模其对网络的影响。本文介绍了人工智能技术在天地一体化卫星网络，特别是巨型卫星网络通信中的应用。详细阐述了巨型卫星网络的独特特征，以及它们与现有通信基础设施集成所伴随的总体挑战。此外，文章深入探讨了通信链路各层的前沿人工智能技术，包括应用人工智能预测高动态无线电信道、频谱感知与分类、信号检测与解调、星间链路与卫星接入网络优化，以及网络安全。最后，概述了未来范式以及这些机制在实际网络中的映射。