But before we get there AI must prove its metal and 3GPP is already hard at work investigating possible applications of AI in each release. In this month?s article the author provides an overall review of what was done in R18 as it relates to a general framework and discusses several key use cases that were part of the release work.
The present document may refer to technical specifications or reports using their 3GPP identities. These shall be interpreted as being references to the corresponding ETSI deliverables. The cross reference between 3GPP and ETSI identities can be found at 3GPP to ETSI numbering cross-referencing.
In terms of 3GPP specification the integration artificial intelligence (AI) has been introduced for many years and have been evolved to enhance cellular network functionality even though the real implementation and deployment is there yet.
At this stage 3GPP?s AI/ML efforts were modest but foundational ? the focus was on creating functions that could analyze network data and set the stage for automation.
The main take-aways of this presentation were that AI/ML is pervasive and that its reach into 3GPP?s work is increasing ? expected to touch virtually every aspect of the system.
The 3rd generation partnership project better known as 3GPP is one of such SDOs that?s looking to add AI/ML technology into the development of the global standards for mobile telecommunications systems it oversees.
The present document specifies the Artificial Intelligence / Machine Learning (AI/ML) management capabilities and services for 5GS where AI/ML is used including management and orchestration (e.g. MDA see 3GPP TS 28.104 [2]) and 5G networks (e.g. NWDAF see 3GPP TS 23.288 [3]).
To support and facilitate the efficient deployment and operation of AI/ML capabilities/features with the suitable AI/ML techniques in 5GS the ML model and AI/ML inference function need to be managed throughout its entire lifecycle.