Artificial Intelligence Augmentation for Channel State Information in 5G and 6G

In this article, we present an artificial intelligence (AI) augmentation framework for physical layer communication applicable to both 5G and future 6G networks. The framework classifies the channel state information (CSI), and uses the classified CSI knowledge to optimally adapt transmission configurations and/or improve conventional signal processing modules in estimation. We demonstrate system benefits of such AI-augmentation in different use cases in 5G NR context, such as beamforming mode adaptation, reference signal (RS) resource optimization, link adaptation as well as channel estimation. The framework also allows extension to resolve future 6G challenges.