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With the maturity of 5G technology and global commercialization, scholars in institutions and industrial circles began to research 6G technology. An important innovation of 6G technology is to integrate artificial intelligence (AI) technology and communication technology to build a highly endogenous intelligent communication network. This paper investigates the process of AI technology introduced into the field of communication and reviews the use cases of the simulation and application of AI algorithms being discussed in 3GPP meetings in industry circles. In this research report, we first investigate the progress of AI technology in 5G network architecture and then discuss the requirements of endogenous intelligent 6G networks, which leads to the possible network architecture. This work aims to provide enlightening guidance for subsequent research of intelligence-endogenous 6G network.

The 6G technology is expected to revolutionize wireless networks by enabling intelligent connectivity of all devices. The concept of a 6G green network aims for ubiquity, intelligence, simplicity, environmental friendliness, and carbon reduction. This paper delves into the essential energy-saving technologies for 6G radio access networks within an energy-efficient framework and proposes a multi-tiered cloud-enabled endogenous intelligent architecture for 6G wireless networks. It provides a design case for an intelligent endogenous wireless network architecture in the context of 6G. Building upon this intelligent network architecture, the paper introduces novel ideas for protocol stack design and multi-rate signaling transmission semantic transmission model. Furthermore, it analyzes the relationship between AI model deployment and energy efficiency while presenting an example of hierarchical deployment of federated learning models. The paper suggests deploying a hierarchical federated learning model within the network architecture to enhance energy efficiency.