> **来源：[研报客](https://pc.yanbaoke.cn)** # 6G Networks Integrated with AI: Summary and Key Insights ## Core Content This White Paper explores the transformative trends and technological pathways of integrating artificial intelligence (AI) with 6G networks, emphasizing the shift from traditional communication systems to intelligent service platforms. It outlines the evolution of 6G networks toward becoming an "intelligent service engine" that supports new services and applications through endogenous intelligence, capability exposure, and digital twin technologies. ## Main Viewpoints ### 1. **Core Transformations in AI-6G Integration** - **Revolutionary Evolution of Terminal Forms**: Terminals evolve into intelligent agent terminals, capable of environmental perception and collaboration. - **Intelligent Upgrading of Application Scenarios**: Transition from "Interconnection of Everything (IoE)" to "Intelligent Interconnection of Everything (IIoE)". - **Intelligent Reconstruction of Network Architecture**: AI is embedded as a core component, enabling predictive, cognitive, and self-evolving capabilities. - **Integrated Development of Service Systems**: Shift from a communication-centric model to a tightly integrated system of communication, sensing, computing, and intelligence. ### 2. **Trends in AI-6G Integration** - AI is a central driver in shaping the 6G network architecture. - The 6G network must be designed around a systematic framework of endogenous intelligence, capability exposure, and digital twin. - The integration of AI technologies will drive the evolution of the network toward a more flexible, scalable, and autonomous system. ### 3. **Key Technological Characteristics** - **Endogenous Intelligence**: AI becomes an intrinsic part of network architecture, enabling self-perception, self-decision-making, self-optimization, self-execution, and self-evolution. - **Capability Exposure**: AI capabilities such as data, computing resources, and models are exposed through open architecture, lowering integration barriers and enhancing service efficiency. - **Digital Twin**: A dual-loop mechanism of internal closed-loop validation and external closed-loop feedback enables real-time simulation and optimization of network operations. ## Key Technologies - **Small AI Models**: Efficient, low-complexity models used for specific tasks like network optimization and resource scheduling. - **Large AI Models**: Support complex tasks such as knowledge extraction and cross-domain generalization. - **Intelligent Agents**: Enable multi-agent collaboration and real-time decision-making. - **Digital Twins**: Facilitate simulation and virtual-physical integration, supporting AI model iteration and network verification. ## Hierarchical Development Pathway - **Network Element Level**: Focus on high-performance and efficient deployment. - **Upper Layer**: Emphasize multi-task and multi-network-element collaboration. - **Top Layer**: Target advanced intelligence powered by large AI models. - The integration of small and large models, along with intelligent agents, will create a "collaboration between small and large models, with intelligence empowering all domains". ## 6G Intelligent Network Architecture - **Design Principles**: - **AI-as-a-Service (AIaaS)**: Modular, elastic, and scalable AI services. - **Multi-dimensional Heterogeneous AI Resource Coordination**: Dynamic allocation of spectrum, computing, and data resources. - **Cross-layer/End-to-End Joint Intelligent Coordination**: Elimination of information silos, global optimization, and improved service quality. - **Layered Distributed Intelligent Coordination**: "Cloud-network-edge-end" architecture with AI capabilities at each level. - **Efficient Data Flow and AI Life Cycle Management (LCM)**: Robust data handling and closed-loop AI management. - **Virtual-Physical Integrated Intelligent Decision-Making**: Digital twin and AI engines enable predictive operations and autonomous functions. - **Architecture Layers**: - Terminal Device - Radio Access Network (RAN) - Edge Intelligence Brain - Core Network - Central Intelligent Brain - **Functionality**: - The RAN introduces AI-based channel estimation and low-pilot transmission. - Higher-layer protocols implement intelligent decision-making mechanisms. - The core network supports large-scale AI model deployment and end-to-end optimization. - Intelligent agents and digital twins facilitate AI strategy simulation and predictive assurance. ## Development Trends - The 6G network will evolve from a communication pipeline to an intelligent service hub. - It will support the development of new applications like XR/holographic communication and distributed swarm intelligence. - The integration of AI technologies will redefine the communications industry and drive digital transformation across various sectors. ## Conclusion The integration of AI with 6G networks represents a fundamental paradigm shift, moving from a data pipeline to an intelligent service engine. By leveraging endogenous intelligence, capability exposure, and digital twin technologies, the 6G network will become a robust platform for the digital economy and intelligent society. This transformation will enable a new stage of network autonomy and industry empowerment, ultimately materializing the vision of "Networks as a Platform, Capabilities as a Service".