AI-Driven Proactive Content Caching for 6G

Abstract

To address the limitations of the current proactive content caching technology for the 6th generation (6G) mobile network, this article comprehensively analyzes the complex application scenarios of proactive content caching technology for wireless edge networks. It constructs an accurate content popularity prediction model, develops a user-device-oriented proactive content caching mechanism, establishes an interpretable cached content replacement strategy, and designs a reliable interdevice content sharing service model to achieve accurate, effective, trustworthy, and practical results. In this article, we analyze the proactive content caching technology for wireless edge networks. Based on the analysis of the core theory and application scenarios of proactive content caching in wireless edge networks, this article focuses on improving the hit rate of content caching in edge devices, improving the quality-of-experience (QoE) of end-users accessing content, enhancing the robustness of proactive content caching schemes, and conducting in-depth research on the key technologies and methods involved. The proposed proactive content caching technology for wireless edge networks is validated and improved through experimental research.