  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.
