Modified O-RAN 5G Edge Reference Architecture using RNN

Murali Narasimham, Y.V.S Sai Pragathi
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Abstract

This paper explores the implementation of 6G/5G standards by network providers using cloud-native technologies such as Kubernetes. The primary focus is on proposing algorithms to improve the quality of user parameters for advanced networks like car as cloud and automated guided vehicle. The study involves a survey of AI algorithm modifications suggested by researchers to enhance the 5G and 6G core. Additionally, the paper introduces a modified edge architecture that seamlessly integrates the RNN technologies into O-RAN, aiming to provide end users with optimal performance experiences. The authors propose a selection of cutting-edge technologies to facilitate easy implementation of these modifications by developers.
使用 RNN 的改进型 O-RAN 5G 边缘参考架构
本文探讨了网络提供商利用 Kubernetes 等云原生技术实施 6G/5G 标准的问题。主要重点是提出算法,以提高汽车作为云和自动导引车等先进网络的用户参数质量。这项研究包括对研究人员提出的人工智能算法修改建议进行调查,以增强 5G 和 6G 核心。此外,论文还介绍了一种改进的边缘架构,该架构将 RNN 技术无缝集成到 O-RAN 中,旨在为终端用户提供最佳性能体验。作者提出了一些前沿技术,以方便开发人员轻松实施这些修改。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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