When Machine Learning Meets Wireless Cellular Networks: Deployment, Challenges, and Applications
This is an incremental survey paper for researchers and practitioners in wireless networking, summarizing existing challenges and applications without presenting new results.
This paper provides an overview of integrating AI functionalities into 5G and beyond wireless networks to shift from reactive to proactive operations, highlighting key factors like data, security, and explainable AI, and summarizing applications across physical layer, mobility management, security, and localization.
Artificial intelligence (AI) powered wireless networks promise to revolutionize the conventional operation and structure of current networks from network design to infrastructure management, cost reduction, and user performance improvement. Empowering future networks with AI functionalities will enable a shift from reactive/incident driven operations to proactive/data-driven operations. This paper provides an overview on the integration of AI functionalities in 5G and beyond networks. Key factors for successful AI integration such as data, security, and explainable AI are highlighted. We also summarize the various types of network intelligence as well as machine learning based air interface in future networks. Use case examples for the application of AI to the wireless domain are then summarized. We highlight on applications to the physical layer, mobility management, wireless security, and localization.