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

IEEE Wirel. Commun.(2023)

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摘要
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 adapt transmission configurations, perform resource optimization, and improve essential signal processing modules such as channel estimation. We demonstrate feasibility and benefits of the proposed AI augmentation in different use cases in the 5G NR context, such as beamforming mode adaptation, reference signal resource optimization, and link adaptation, as well as channel estimation. The framework also allows extension to resolve future 6G challenges.
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关键词
5G network,5G NR context,6G network,AI augmentation,artificial intelligence augmentation framework,channel estimation,channel state information,classified CSI knowledge,essential signal processing modules,link adaptation,mode adaptation,physical layer communication,reference signal resource optimization,transmission configurations
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