  Due to the proliferation of smart devices and emerging applications, many
next-generation technologies have been paid for the development of wireless
networks. Even though commercial 5G has just been widely deployed in some
countries, there have been initial efforts from academia and industrial
communities for 6G systems. In such a network, a very large number of devices
and applications are emerged, along with heterogeneity of technologies,
architectures, mobile data, etc., and optimizing such a network is of utmost
importance. Besides convex optimization and game theory, swarm intelligence
(SI) has recently appeared as a promising optimization tool for wireless
networks. As a new subdivision of artificial intelligence, SI is inspired by
the collective behaviors of societies of biological species. In SI, simple
agents with limited capabilities would achieve intelligent strategies for
high-dimensional and challenging problems, so it has recently found many
applications in next-generation wireless networks (NGN). However, researchers
may not be completely aware of the full potential of SI techniques. In this
work, our primary focus will be the integration of these two domains: NGN and
SI. Firstly, we provide an overview of SI techniques from fundamental concepts
to well-known optimizers. Secondly, we review the applications of SI to settle
emerging issues in NGN, including spectrum management and resource allocation,
wireless caching and edge computing, network security, and several other
miscellaneous issues. Finally, we highlight open challenges and issues in the
literature, and introduce some interesting directions for future research.
