IEEE Open Journal of the Communications Society (Jan 2021)

An Overview on the Application of Graph Neural Networks in Wireless Networks

  • Shiwen He,
  • Shaowen Xiong,
  • Yeyu Ou,
  • Jian Zhang,
  • Jiaheng Wang,
  • Yongming Huang,
  • Yaoxue Zhang

DOI
https://doi.org/10.1109/OJCOMS.2021.3128637
Journal volume & issue
Vol. 2
pp. 2547 – 2565

Abstract

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In recent years, with the rapid enhancement of computing power, deep learning methods have been widely applied in wireless networks and achieved impressive performance. To effectively exploit the information of graph-structured data as well as contextual information, graph neural networks (GNNs) have been introduced to address a series of optimization problems of wireless networks. In this overview, we first illustrate the construction method of wireless communication graph for various wireless networks and simply introduce the progress of several classical paradigms of GNNs. Then, several applications of GNNs in wireless networks such as resource allocation and several emerging fields, are discussed in detail. Finally, some research trends about the applications of GNNs in wireless communication systems are discussed.

Keywords