This collection of Best Readings focuses on ML in the physical and medium access control (MAC) layer of communication networks. ML can be used to improve each individual (traditional) component of a communication system, or to jointly optimize the entire transmitter or receiver. Therefore, after introducing some popular textbooks, tutorials, and special issues in this collection, we divide the technical papers into the following six areas:
- Signal detection
- Channel encoding and decoding
- Channel estimation, prediction, and compression
- End-to-end communications
- Resource allocation
- Selected topics
Even if ML in communications is still in its infancy, we believe that a growing number of researchers will be dedicated to the related studies and ML will greatly change the way of communication system design in the near future.