5G and beyond mobile networks will support heterogeneous use cases at an unprecedented scale, thus demanding automated control and optimization of network functionalities customized to the needs of individual users. Such fine-grained control of the Radio Access Network (RAN) is not possible with the current cellular architecture. To fill this gap, the Open RAN paradigm and its specification introduce an open architecture with abstractions that enable closed-loop control and provide data-driven, and intelligent optimization of the RAN at the user level. This is obtained through custom RAN control applications (i.e., xApps) deployed on near-real-time RAN Intelligent Controller (near-RT RIC) at the edge of the network. Despite these premises, as of today the research community lacks a sandbox to build data-driven xApps, and create large-scale datasets for effective AI training. In this paper, we address this by introducing ns-O-RAN, a software framework that integrates a real-world, production-grade near-RT RIC with a 3GPP-based simulated environment on ns-3, enabling the development of xApps and automated large-scale data collection and testing of Deep Reinforcement Learning-driven control policies for the optimization at the user-level. In addition, we propose the first user-specific O-RAN Traffic Steering (TS) intelligent handover framework. It uses Random Ensemble Mixture, combined with a state-of-the-art Convolutional Neural Network architecture, to optimally assign a serving base station to each user in the network. Our TS xApp, trained with more than 40 million data points collected by ns-O-RAN, runs on the near-RT RIC and controls its base stations. We evaluate the performance on a large-scale deployment, showing that the xApp-based handover improves throughput and spectral efficiency by an average of 50% over traditional handover heuristics, with less mobility overhead.
翻译:5G 移动网络外的5G网络将支持以前所未有的规模使用各种情况,从而要求自动控制和优化适合个人用户需要的网络功能。 在当前细胞结构中,无法对无线电接入网络(RAN)进行这种精细控制。 为了填补这一空白, Open RAN 范式及其规格将引入一个开放的架构,该架构将允许闭路控制并提供数据驱动和智能优化在用户一级使用RAN。 这是通过在网络边缘的近实时 RAN 智能主计长(即,XApp) 上安装的定制 RAN 控制应用程序(即,XApps) 进行自动化控制和优化控制。 在网络内部网络上安装了一个基于近实时 RAN 的智能控制程序(近实时RAN ), 在网络上安装了近实时RAN-RIC(近实时RA ), 在网络上安装了一个基于3GP的模拟环境, 在深度的NS-3级的服务器上, 驱动服务器数据库上安装了一个升级的自动升级的系统, 进行升级的系统测试和升级的系统控制。