The Role of AI in 6G MAC

The potential of Artificial Intelligence (AI) techniques, such as autoencoders, for customizing the wireless physical layer has been demonstrated in previous works. In the current paper, we move up the protocol stack and explore the frontiers of Machine Learning (ML) on the wireless Medium Access Control (MAC) layer. Unlike the Physical Layer (PHY), the MAC aggregates multiple independent features, which require a separate ML treatment. Considering this, this survey paper navigates recent research on AI-driven MAC functions such as resource allocation, random access, Adaptive Modulation and Coding (AMC), power control, protocol learning, Channel State Information (CSI) reporting, Hybrid Automatic Repeat Request (HARQ), and Multi-RAT Spectrum Sharing (MRSS).