During the process of building smart cities, mobile networks have attracted much attention from global researchers, communities, and operators. Although new emerging applications have promoted the development of mobile networks, the requirements of high-quality content delivery cause that mobile networks cannot handle real-time traffic and cannot satisfy more users. For example, the instable traffic delivery brings about the problem of stuttering; the belated traffic scheduling results in the long response time; the unscientific traffic classification leads to the unbalanced satisfaction. Artificial Intelligence (AI) has been accepted as a brain power to optimize traffic delivery for mobile networks. For example, AI conducts to accelerate the transmission of content streaming. AI has the self-adaptive training ability to perform traffic classification. (iii) AI analyzes and builds the model of traffic to satisfy the requirements of users with the distributed learning ability.

This Special Issue focuses on AI-based traffic delivery for mobile networks in terms of theoretical and practical issues. The purpose of this special issue is to bring together researchers, industry personnel, academicians, and individuals working in these areas and to exchange novel ideas and latest findings.

Potential topics include but are not limited to the following:

• AI-driven mobile network architecture/framework
• AI-based traffic awareness
• AI-based traffic filtering algorithm
• AI-based traffic scheduling
• AI-based traffic modelling
• AI-based traffic resource allocation
• AI-based energy-efficient traffic delivery
• AI-based security and privacy for traffic delivery
• AI-based QoE assessment
• New AI-based traffic dataset