The present document provides descriptions of principles for RAN intelligence enabled by AI, the functional framework (e.g., the AI functionality and the input/output of the component for AI enabled optimization) and use cases and solutions of AI enabled RAN.
The study is based on the current architecture and interfaces.
The following documents contain provisions which, through reference in this text, constitute provisions of the present document.
References are either specific (identified by date of publication, edition number, version number, etc.) or non specific.
For a specific reference, subsequent revisions do not apply.
For a non-specific reference, the latest version applies. In the case of a reference to a 3GPP document (including a GSM document), a non-specific reference implicitly refers to the latest version of that document in the same Release as the present document.
For the purposes of the present document, the terms given in TR 21.905
and the following apply. A term defined in the present document takes precedence over the definition of the same term, if any, in TR 21.905
Data collection: Data collected from the network nodes, management entity or UE, as a basis for AI/ML model training, data analytics and inference.
AI/ML Model: A data driven algorithm by applying machine learning techniques that generates a set of outputs consisting of predicted information and/or decision parameters, based on a set of inputs
AI/ML Training: An online or offline process to train an AI/ML model by learning features and patterns that best present data and get the trained AI/ML model for inference.
AI/ML Inference: A process of using a trained AI/ML model to make a prediction or guide the decision based on collected data and AI/ML model.
For the purposes of the present document, the following symbols apply:
For the purposes of the present document, the abbreviations given in TR 21.905
and the following apply. An abbreviation defined in the present document takes precedence over the definition of the same abbreviation, if any, in TR 21.905