The fifth-generation (5G) mobile network era has enabled the integration of artificial intelligence (AI), big data, Internet of Things (IoT), edge computing, etc. Wireless networks are becoming more complex. They have three main characteristics: network complexity, business diversification, and experience complexity. Faced with the increasingly difficult modelling of wireless networks, the complexity of solving problems is increasing exponentially. Moreover, the cost of network operation and maintenance is getting higher.

AI algorithms have been successfully supporting big data analytics, efficient parameter estimation, and interactive decision making and have shown compelling applications of wireless networks (e.g., heterogeneous networks (HetNets), cognitive radio (CR), Internet of Things (IoT), machine to machine (M2M) networks). Wireless networks are focused on a data-driven future. Therefore, AI has brought a paradigm shift to the design and optimization of networks. AI has become an important technological trend in the industry and is gradually being generalized. It faces the diversified, heterogeneous, high-precision, and high-reliability requirements of future wireless networks. Incorporating AI into the future wireless network architecture has become a technological trend for research and exploration. AI will make important contributions to the future wireless network transmission framework. Moreover, there is a need for further research discussing AI combined with communication network channel modelling, network operation and maintenance, network security audits, and other fields.

The aim of this Special Issue is to focus on the application of artificial intelligence in next-generation wireless networks. We welcome submissions particularly discussing AI algorithms. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• AI-enable architectures in next-generation wireless networks
• AI-based key performance management in next-generation wireless networks
• AI-powered energy-efficient network orchestration
• AI-based networks for channel modelling and estimation
• AI techniques for signal processing in wireless network systems
• AI-enabled techniques for ensuring security and privacy in next-generation wireless networks
• Deep learning for IoT services in next-generation wireless networks
• Energy-efficient AI for next-generation wireless networks