Machine learning (ML) has been very successful in image and video recognition as well as natural language processing. For 6G, researchers are interested in applying machine learning to signal processing, so that a signal can be modified based on:
- Application
- Learned characteristics of the mobile radio channel
- Imperfections within the signal processing chain
- Analog and digital impairments induced by the transceiver architecture
The goal is to have networks that learn from traffic and density patterns, realizing the ultimate dream of self-organizing networks. Key industry players also emphasize the importance of data and combining these data elements into an air interface design. Another point of consideration is how AI/ML can work for battery-powered mobile devices.
