As an efficient graph analytical tool, graph neural networks (GNNs) have special properties that are particularly fit for the characteristics and requirements of wireless communications, exhibiting good potential for the advancement of next-generation wireless communications. This article aims to provide a comprehensive overview of the interplay between GNNs and wireless communications, including GNNs for wireless communications (GNN4Com) and wireless communications for GNNs (Com4GNN). In particular, we discuss GNN4Com based on how graphical models are constructed and introduce Com4GNN with corresponding incentives. We also highlight potential research directions to promote future research endeavors for GNNs in wireless communications.

中文翻译：

---

图神经网络满足无线通信：动机、应用和未来方向

作为一种高效的图分析工具，图神经网络（Graph Neural Networks，GNNs）具有特殊的性质，特别适合无线通信的特点和要求，在下一代无线通信的发展中展现出良好的潜力。本文旨在全面概述 GNN 与无线通信之间的相互作用，包括用于无线通信的 GNN (GNN4Com) 和用于 GNN 的无线通信 (Com4GNN)。特别是，我们基于图形模型的构建方式讨论了 GNN4Com，并介绍了具有相应激励的 Com4GNN。我们还强调了潜在的研究方向，以促进 GNN 在无线通信中的未来研究。