Abstract
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.
Published Version
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