Next-generation multiple input multiple output (MIMO) is expected to be
intelligent and scalable. In this paper, we study generative artificial
intelligence (AI) agent-enabled next-generation MIMO design. Firstly, we
provide an overview of the development, fundamentals, and challenges of the
next-generation MIMO. Then, we propose the concept of the generative AI agent,
which is capable of generating tailored and specialized contents with the aid
of large language model (LLM) and retrieval augmented generation (RAG). Next,
we comprehensively discuss the features and advantages of the generative AI
agent framework. More importantly, to tackle existing challenges of
next-generation MIMO, we discuss generative AI agent-enabled next-generation
MIMO design, from the perspective of performance analysis, signal processing,
and resource allocation. Furthermore, we present two compelling case studies
that demonstrate the effectiveness of leveraging the generative AI agent for
performance analysis in complex configuration scenarios. These examples
highlight how the integration of generative AI agents can significantly enhance
the analysis and design of next-generation MIMO systems. Finally, we discuss
important potential research future directions.

本文研究了基于生成式人工智能代理的下一代 MIMO 设计，提出了生成式人工智能代理的概念，并探讨了其特点和优势，还从性能分析、信号处理和资源分配的角度讨论了生成式人工智能代理实现下一代 MIMO 设计的挑战和方法，并通过两个实例展示了生成式人工智能代理在复杂配置场景下性能分析方面的有效性，最后探讨了重要的未来研究方向。