Guest Editors
Dr. Qinqin Tang
Email: qqtang@bupt.edu.cn
Affiliation: Beijing University of Posts and Telecommunications, Beijing, China
Homepage:
Research Interests: internet of intelligence, edge/cloud computing, traffic offloading, resource management
Dr. Tianjiao Chen
Email: chentianjiao@chinamobile.com
Affiliation: China Mobile Research Institute, Beijing, China
Homepage:
Research Interests: internet of things, wireless communications, artificial intelligence
Dr. Weihong Wu
Email: wuwehong@uestc.edu.cn
Affiliation: University of Electronic Science and Technology of China, Chengdu, 611730, China
Homepage:
Research Interests: internet of things, artificial intelligence
Summary
With the rapid advancement of large AI models, various digital and physical AI agents, ranging from virtual digital assistants and digital humans to physical intelligent robots and unmanned aerial vehicles, are experiencing explosive growth. This surge has spurred urgent demands for 6G networks to provide high-performance connectivity, data collection, computation offloading, and AI-native services. Consequently, traditional communication networks must evolve into information service networks by integrating communication, computing, data and AI capabilities, ultimately realizing the collaborative evolution of networks and agents.
Despite promising prospects, the integration of networks and AI agents faces prominent challenges. First, 5G network is inadequate in capacity, connection density, and latency to meet the massive and diverse connectivity requirements of agents, necessitating AI agent-oriented connection enhancement technologies. Second, existing cloud computing and mobile edge computing architectures lack effective integrated control over communication and computing resources, resulting in low resource utilization and poor quality of AI service (QoAIS) guarantee. Third, agent traffic has evolved from traditional text, audio, and video modalities to new forms such as tokens, model parameters, and gradients, calling for innovative transmission methods like semantic communication and token communication. Fourth, agents are shifting from individual intelligence to swarm collaboration, posing new demands for network support in agent networking and cooperative operations.
Therefore, this special issue focuses on 6G network empowering AI agents, including its system architecture, key technologies, and testbed validation. The following subtopics are the particular interests of this special issue, including but not limited to:
· 6G network architecture for AI agents
· Integrating connection and computing empowering AI agents
· QoAIS guarantee for network-enabled AI agents
· Energy-efficient network empowering AI agents
· Multi-agent collaboration and network-enabled collective intelligence
· Network protocol design for AI agent cooperation
· Testbeds, Prototyping and Standardization for 6G empowering AI agents
Keywords
6G, network for AI agent, agent communication network, mobile edge intelligence, agent collaboration
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