Artificial Intelligence in Wireless Communications: An Overview of Present-day Paradigms

The integration of artificial intelligence (AI) into wireless communications is growing rapidly. This growth is primarily driven by machine learning (ML) techniques, which can be broadly categorized into supervised learning, unsupervised learning, and reinforcement learning. Today, AI-based paradigms are transforming the field of wireless communications by enhancing various aspects, from the rapid design and optimization of components and devices to the robust analysis and characterization of entire systems and networks. This includes advanced systems such as present-day fifth-generation mobile (5G) and the upcoming sixth-generation mobile (6G) systems and networks. AI techniques also offer promising solutions to numerous design and development challenges in modern wireless communications. These challenges encompass enhancing power and energy effi-ciency, meeting stringent performance criteria, and improving the overall reliability of wireless communication devices, systems, and networks. This paper provides an overview of current paradigms demonstrating the application of AI, particularly ML techniques, in wireless communications.