Cellular networks are undergoing a revolutionary transform with the advent of O-RAN architectures and AI/ML solutions. O-RAN's Non-Real-Time and Near-Real Time RAN Intelligent Controllers open the door to the implementation of automated control-loops that can provide RAN optimisations in numerous scenarios and use cases, and which can be further empowered by AI-driven approaches. Energetic sustainability has raised as one of the main optimisations targets due to the impact of mobile networks on global energy consumption. To this end, the BeGREEN project aims at enhancing the energy efficiency of beyond 5G networks by defining novel AI/ML-based methods at RAN and edge infrastructure. This paper presents BeGREEN Intelligent Plane, a novel framework which implements and exposes AI/ML workflows to O-RAN-based optimisations targeting energy efficiency. We also describe an exemplary application of the Intelligent Plane and its AI Engine, which aims at providing AI-driven cell on/off control.

翻译：蜂窝网络正随着O-RAN架构与AI/ML解决方案的兴起经历革命性变革。O-RAN的非实时与近实时RAN智能控制器为自动化控制环的实现打开了大门，这些控制环能够在众多场景与用例中提供无线接入网优化，并可通过AI驱动方法进一步增强。由于移动网络对全球能源消耗的影响，能源可持续性已成为主要优化目标之一。为此，BeGREEN项目旨在通过在RAN与边缘基础设施定义基于AI/ML的新型方法，提升超5G网络的能效。本文提出BeGREEN智能平面这一新型框架，该框架实现并向O-RAN底层优化暴露AI/ML工作流，以提升能效。我们还描述了智能平面及其AI引擎的示范性应用，该应用旨在提供基于AI的基站开关控制。