6G无线接口融合AI，以语义压缩与自适应为核心
Way to Build Native AI-driven 6G Air Interface: Principles, Roadmap, and Outlook
- 用语义压缩替代传统符号传输，聚焦任务相关性
- 支持多任务、多数据类型动态适配，提升鲁棒性
- 面向非地面网络场景，为6G AI原生架构提供蓝图
人工智能（AI）预计将成为6G网络全生命周期——从设计、部署到运营——的基础能力。本文提出一种基于压缩与自适应两大核心特性的原生AI驱动无线接口架构。一方面，压缩使系统能够理解并提取源数据中的关键语义信息，关注任务相关性而非符号级精度；另一方面，自适应使无线接口可在不同任务、数据类型和信道条件下动态传输语义信息，确保可扩展性与鲁棒性。文章首先介绍该原生AI驱动的无线接口架构，随后讨论代表性使能方法，并通过6G非地面网络中的语义通信案例研究进行验证。最后，展望原生AI在6G中的未来，指出关键技术挑战与研究机遇。
原文摘要 · Abstract (English)
Artificial intelligence (AI) is expected to serve as a foundational capability across the entire lifecycle of 6G networks, spanning design, deployment, and operation. This article proposes a native AI-driven air interface architecture built around two core characteristics: compression and adaptation. On one hand, compression enables the system to understand and extract essential semantic information from the source data, focusing on task relevance rather than symbol-level accuracy. On the other hand, adaptation allows the air interface to dynamically transmit semantic information across diverse tasks, data types, and channel conditions, ensuring scalability and robustness. This article first introduces the native AI-driven air interface architecture, then discusses representative enabling methodologies, followed by a case study on semantic communication in 6G non-terrestrial networks. Finally, it presents a forward-looking discussion on the future of native AI in 6G, outlining key challenges and research opportunities.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。