Cell-free massive multiple-input multiple-output (mMIMO) and extremely large-scale MIMO (XL-MIMO) are regarded as promising innovations for the forthcoming generation of wireless communication systems. Their significant advantages in augmenting the number of degrees of freedom have garnered considerable interest. In this article, we first review the essential opportunities and challenges induced by XL-MIMO systems. We then propose the enhanced paradigm of cell-free XL-MIMO, which incorporates multi-agent reinforcement learning (MARL) to provide a distributed strategy for tackling the problem of high-dimension signal processing and costly energy consumption. Based on the unique near-field characteristics, we propose two categories of the low-complexity design, i.e., antenna selection and power control, to adapt to different cell-free XL-MIMO scenarios and achieve the maximum data rate. For inspiration, several critical future research directions pertaining to green cell-free XL-MIMO systems are presented.

翻译：无蜂窝大规模多输入多输出（mMIMO）与超大规模MIMO（XL-MIMO）被视为下一代无线通信系统的创新性技术。它们通过增加自由度数量所展现的显著优势已引起广泛关注。本文首先回顾了XL-MIMO系统带来的关键机遇与挑战，进而提出了一种增强型无蜂窝XL-MIMO架构，该架构融合多智能体强化学习（MARL）以提供分布式策略，用于解决高维信号处理与高能耗问题。基于独特的近场特性，我们提出了两类低复杂度设计方案——天线选择与功率控制——以适应不同无蜂窝XL-MIMO场景并实现最大数据传输速率。为启发后续研究，本文还探讨了绿色无蜂窝XL-MIMO系统的若干关键未来研究方向。