首页> 外国专利> FUNCTIONAL ARCHITECTURE AND INTERFACE FOR NON-REAL-TIME RAN INTELLIGENT CONTROLLER

FUNCTIONAL ARCHITECTURE AND INTERFACE FOR NON-REAL-TIME RAN INTELLIGENT CONTROLLER

机译:非实时运行智能控制器的功能架构和接口

摘要

The present disclosure relates to a 5G communication system or a 6G communication system for supporting higher data rates beyond a 4G communication system such as long term evolution (LTE). A service management and orchestration (SMO) entity enabling a functional split between a non-real-time (RT) radio access network (RAN) intelligent controller (RIC) and an external artificial intelligence (AI)/machine learning (ML) server will, during a data collection phase, utilize the SMO entity and the non-RT RIC to collect and process RAN data and non-RAN data and, during a data transfer phase, transfer processed RAN and non-RAN data from the SMO entity to an external AI/ML server via an interface. During a training model input phase, the SMO entity receives a trained AI/ML model, metadata, and training results from the external AI/ML server via an interface and, during a configuration phase, the SMO entity uses the trained AI/ML model within the SMO entity and the non-RT RIC to transfer configuration parameters to a near-RT RIC.
机译:本公开涉及5G通信系统或6G通信系统,用于支持超出4G通信系统的更高数据速率,例如长期演进(LTE)。服务管理和编程(SMO)实体能够在非实时(RT)无线电接入网络(RAN)智能控制器(RIC)和外部人工智能(AI)/机器学习(ML)服务器之间的功能分开,在数据收集阶段期间,利用SMO实体和非RT RIC来收集和处理RAN数据和非RAN数据,并且在数据传输阶段期间,从SMO实体传输处理的RAN和非RAN数据通过接口外部AI / ML服务器。在训练模型输入阶段期间,SMO实体通过接口接收来自外部AI / ML服务器的训练的AI / ML模型,元数据和训练结果,并且在配置阶段期间,SMO实体使用训练的AI / ML模型在SMO实体和非RT RIC中将配置参数传输到近RT RIC。

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