Cell-free massive MIMO is emerging as a promising technology for future wireless communication systems, which is expected to offer uniform coverage and high spectral efficiency compared to classical cellular systems. We study in this paper how cell-free massive MIMO can support federated edge learning. Taking advantage of the additive nature of the wireless multiple access channel, over-the-air computation is exploited, where the clients send their local updates simultaneously over the same communication resource. This approach, known as over-the-air federated learning (OTA-FL), is proven to alleviate the communication overhead of federated learning over wireless networks. Considering channel correlation and only imperfect channel state information available at the central server, we propose a practical implementation of OTA-FL over cell-free massive MIMO. The convergence of the proposed implementation is studied analytically and experimentally, confirming the benefits of cell-free massive MIMO for OTA-FL.

翻译：无蜂窝大规模MIMO正成为未来无线通信系统的一项有前景技术，与经典蜂窝系统相比，有望提供均匀覆盖和高频谱效率。本文研究无蜂窝大规模MIMO如何支持联邦边缘学习。利用无线多址信道的加性特性，采用基于空中计算的方法，即客户端在同一通信资源上同时发送本地更新。这种被称为空中联邦学习（OTA-FL）的方法已被证明能减轻无线网络联邦学习的通信开销。考虑信道相关性以及中央服务器仅能获取不完美信道状态信息，我们提出一种在无蜂窝大规模MIMO上实现OTA-FL的实用方案。通过分析和实验研究该实现方案的收敛性，证实了无蜂窝大规模MIMO对OTA-FL的益处。