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  • AI-Driven Seamless and Massive Access in Space-Air-Ground Integrated . . .
    In particular, we explore a practical AI case for joint optimization of multidimensional resources in SAGIN and further analyze why the deep reinforcement learning (DRL) method can achieve efficient resource management and performance enhancement compared to traditional optimization methods based on their principles and simulation results
  • Generative AI for Space-Air-Ground Integrated Networks - arXiv. org
    Integrating generative AI with SAGIN is expected to sig-nificantly transform wireless communication networks and digital content creation By leveraging the comprehensive connectivity provided by SAGIN, generative AI facilitates the seamless generation and dissemination of high-quality informationacross disparate networks, such as real-time
  • AI-Enabled Space-Air-Ground Integrated Networks: Management and . . .
    AI-enabled Beyond 5G (B5G) and 6G technolo-gies are promising candidates to support the future generation Space-Air-Ground Integrated Networks (SAGINs) The highly dynamic heterogeneity and time variability, however, complicate management and optimization eforts
  • Space-Air-Ground Integrated Network with Native Intelligence . . .
    In this paper, we propose a novel AI-enabled space-air-ground integrated networks (SAGIN) This new integrated networks architecture consists of LEO satellites and civil aircrafts carrying aerial base stations, called "civil aircraft assisted SAGIN (CAA-SAGIN)''
  • Secure, Intelligent, Programmable Space-Air-Ground Integrated Networks . . .
    ML and AI solutions are being explored to advance cooperative and autonomous behaviour, self-organisation, and optimization within the SAGIN Specifically, there are questions around the impact of interactive systems in space e g , satellite UAV cooperation (AI-driven) and security considerations of the dynamic environment
  • Utilizing Large Language Models for Advanced Optimization and . . .
    We thoroughly analyze the application of LLMs in optimizing channel models, improving communication algorithms, and enhancing network management and security performance to address the unique characteristics and requirements of SAGIN
  • Interplay Between AI and Space-Air-Ground Integrated Network: The Road . . .
    Through advanced AI technologies such as DRL, federated learning, and edge intelligence, SAGIN can achieve dynamic optimization, real-time response, and adaptive adjustment in complex and multi-layered networks In new scenarios such as intelligent disaster response, smart city management, and low-altitude economy, AI technologies provide SAGIN
  • CCAI 2025 | Haikou, China
    AI-driven ISAC frameworks synergize cognitive network optimization, federated learning-enhanced environmental perception, and adaptive edge computing to overcome spectrum scarcity, mobility constraints, and heterogeneous service requirements
  • Application of Artificial Intelligence in Mobile Communication Networks . . .
    This study comprehensively explores the application of artificial intelligence (AI) in mobile communication networks and its revolutionary impact on network optimization With the evolution of mobile communication technology from 2 to 5G and future 6G, the complexity of networks and user demands continue to increase, making traditional network
  • Generative AI for Intelligent Networks | Computer Networks and . . .
    Welcome to our research on applying generative artificial intelligence (GAI) in intelligent networks Two core goals of these efforts are to explore how intelligent networks can support various artificial intelligence-generated content (AIGC) services, and how generative AI can enhance network performance In response to the above goals, our





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