AI-Native for 6G Core Network Configuration

Abdullah Ridwan Hossain;Weiqi Liu;Nirwan Ansari;Abbas Kiani;Tony Saboorian
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Abstract

3GPP envisions exploiting AI-Native for the day-to-day operations of 6G core networks (CNs). As opposed to 5G CNs whose uses for artificial intelligence (AI) are limited and not yet standardized, 6G CNs seek a revolutionary redesign where AI will no longer simply be an overlaid service but rather the foundation upon which all network functions run, i.e., AI-Native. By leveraging knowledge of the CN control plane, we utilize an AI framework to optimize our three proposed CN configurations and minimize the CN execution time which is imperative for end-to-end routing in the user plane.
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面向 6G 核心网络配置的 AI 本机
3GPP 设想在 6G 核心网 (CN) 的日常运营中利用 AI-Native。与人工智能(AI)用途有限且尚未标准化的 5G 核心网相比,6G 核心网寻求的是革命性的重新设计,人工智能将不再是简单的叠加服务,而是所有网络功能运行的基础,即 AI-Native。通过利用 CN 控制平面的知识,我们利用人工智能框架来优化我们提出的三种 CN 配置,并最大限度地减少 CN 的执行时间,这对于用户平面的端到端路由至关重要。
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Table of Contents IEEE Networking Letters Author Guidelines IEEE COMMUNICATIONS SOCIETY IEEE Communications Society Optimal Classifier for an ML-Assisted Resource Allocation in Wireless Communications
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