Agentic AI for Integrated Sensing and Communication: Analysis, Framework, and Case Study

TL;DR

This paper explores how agentic AI can enhance integrated sensing and communication (ISAC) systems in 6G networks by proposing a new framework and demonstrating its advantages through a case study.

Contribution

It introduces a novel agentic ISAC framework, reviews key characteristics of agentic AI and ISAC, and highlights the benefits of GenAI-based approaches for autonomous network operation.

Findings

Proposed a new agentic ISAC framework.

Demonstrated the framework's effectiveness in a case study.

Highlighted advantages of GenAI in ISAC optimization.

Abstract

Integrated sensing and communication (ISAC) has emerged as a key development direction in the sixth-generation (6G) era, which provides essential support for the collaborative sensing and communication of future intelligent networks. However, as wireless environments become increasingly dynamic and complex, ISAC systems require more intelligent processing and more autonomous operation to maintain efficiency and adaptability. Meanwhile, agentic artificial intelligence (AI) offers a feasible solution to address these challenges by enabling continuous perception-reasoning-action loops in dynamic environments to support intelligent, autonomous, and efficient operation for ISAC systems. As such, we delve into the application value and prospects of agentic AI in ISAC systems in this work. Firstly, we provide a comprehensive review of agentic AI and ISAC systems to demonstrate their key characteristics. Secondly, we show several common optimization approaches for ISAC systems and highlight the significant advantages of generative artificial intelligence (GenAI)-based agentic AI. Thirdly, we propose a novel agentic ISAC framework and prensent a case study to verify its superiority in optimizing ISAC performance. Finally, we clarify future research directions for agentic AI-based ISAC systems.