从意图到基础设施：用于ISAC网络的基于大语言模型的智能体编译器

中文摘要 AI 辅助

集成感知与通信（ISAC）正从概念验证演示迈向第六代（6G）网络的系统级部署。由于感知与通信共享硬件、频谱和波形资源，ISAC设计涉及诸多紧密耦合的选择。本文介绍了智能体编译器，它是一个基于大语言模型的编译层，将高级工程意图转化为完整且可执行的ISAC系统配置。其工作分四个阶段，产生可验证的中间表示ISAC策略图。运行时引擎部署编译后的配置并支持三级闭环自适应。通过无人机辅助灾难救援示例展示了完整编译过程，还讨论了开放问题以指导未来研究。

英文摘要

Integrated sensing and communications (ISAC) is moving from proof-of-concept demonstrations to system-level deployment in sixth-generation (6G) networks. Because sensing and communication share hardware, spectrum, and waveform resources, ISAC design now involves many tightly coupled choices, including waveform selection, sensing algorithm setup, resource scheduling, and deployment planning. This design space is already too large to manage well through manual tuning or isolated optimizers. This article introduces the \textit{Agent Compiler}, a large language model (LLM)-enabled compilation layer that translates high-level engineering intent into complete and executable ISAC system configurations. The Agent Compiler works in four stages: intent parsing, task decomposition, policy graph synthesis, and infrastructure mapping. It produces a verifiable intermediate representation called the ISAC Policy Graph (IPG). A runtime engine then deploys the compiled configuration and supports closed-loop adaptation at three levels: fast parameter updates, partial recompilation of affected subgraphs, and full workflow recompilation. The core design principle is strict time-scale separation: the LLM handles slow-loop strategic decisions, while proven algorithms retain real-time control in the fast loop. A UAV-assisted disaster rescue example illustrates the full compilation process. We also discuss open issues, including compilation latency, output reliability, constraint verification, and pipeline security, to guide future research.

发表机构

• School of Computer Science and Technology, Xidian University（西安电子科技大学计算机科学与技术学院）
• Institute of Systems General, Academy of Systems Engineering, Academy of Military Sciences（系统工程院系统一般研究所）

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