Artificial intelligence (AI) is defined as any process or device that perceives its environment and takes actions that maximize the chances of success for some predefined goal, which can provide feasible solutions for emerging complex communication systems. The recent advances in machine learning, such as deep learning, convolutional neural networks, recurrent neural networks, and reinforcement learning, hold significant promise for solving complex and intractable problems. The fifth generation (5G) wireless communications are expected to satisfy the diverse service requirements in various aspects of our daily life, from residence, work, leisure, to transportation.

Due to the extreme range of 5G requirements for user experience, efficiency, performance, and complex network environments, the design and optimization of 5G networks becomes very challenging. The future 5G network will require robust and intelligent algorithms to adapt network protocols and resource management for different services in different scenarios. It is now appropriate to apply AI technology to wireless communications to tackle optimized physical layer design, complicated decision making, network management, and resource optimization tasks in such networks. Moreover, emerging big data technology has brought us an excellent opportunity to study the essential characteristics of wireless networks and to help us to obtain a more clear and in-depth knowledge of the behaviour of wireless networks. In the study of wireless technologies and communication systems, AI will be a powerful tool and a hot research topic with many potential applications, e.g., wireless signal processing, channel modelling, and resource management.

This Special Issue aims to collate original research and review articles in the field of artificial intelligence applied to wireless networks.

Potential topics include but are not limited to the following:

• Novel design of deep-learning approaches for wireless system applications and services
• Novel design of machine-learning and pattern recognition algorithms for wireless communication technologies
• Systems and applications of AI for optimizing wireless communication systems, including channel models, channel state estimation, code book design, and signal processing, etc.
• Systems and applications of AI for wireless transmission technologies, including coordinated multiple points of transmission/reception, large scale antenna array, and multi-hop relay, etc.
• Systems and applications of AI for mobile management, including user association, handoff strategy, and backhaul technology, etc.
• Systems and applications of AI for resource management, including spectrum resources, energy sources, cloud resources, computing resources, and communication infrastructure, etc.
• AI-enabled security methods in wireless networks
• AI-enabled network pricing models
• The analysis and prediction of network behaviour via AI technologies, including multi-media traffic load, network overhead, and network collision, etc.
• Evaluating the scope and potential limitations of AI solutions in wireless communications