面向6G的智能调制和波形技术研究OA

Recently,the technical discussions and standardization of the 6th Generation Mobile Network(6G)have been at a pivotal stage.In the pursuit of higher spectral efficiency,lower power consumption,and broader coverage,traditional modulation technologies and waveform designs are encountering performance bottlenecks at the physical layer.Meanwhile,the explosive development of Artificial Intelligence and Machine Learning(AI/ML)has laid a solid foundation for breaking through these physical layer limitations.This paper aims to explore the deep integration of AI with 6G physical layer technologies,particularly modulation and waveforms,alongside its standardization progress.This paper begins with a systematic overview of the current standardization progress related to modulation and waveform technologies in 3GPP Release 20(R20).Specifically,the paper introduces the optimization of irregular geometric AI constellation designs via AI/ML,the AI-based generation of low Peak-to-Average Power Ratio(PAPR)waveforms,and endogenous AI receiver architectures designed to replace traditional receiving modules,providing a technical reference for the design of future 6G air interfaces.