Generative AI Control for Disaggregated O-RAN Network Data
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Solution Overview
Problem
Network operators face challenges in utilizing disaggregated data from different solution providers in O-RAN environments, as existing systems lack the capability to make sense of this data and facilitate dynamic network decisions.
Innovation Solution
Implementing data-driven artificial intelligence (AI) mechanisms that enable network operators to obtain, format, and apply data from disaggregated wireless communication networks using generative AI processes to generate commands for network components, facilitating dynamic decision-making and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data collection capabilities are placed external to the RAN and core networks, then network operators can purchase AI systems, but data collection from multiple sources becomes difficult and AI systems reside outside the carrier network
Solution Approach 1:
The patent implements a multi-vendor data collection interface that can collect data from multiple sources including RAN, core network, and external systems through a single unified interface. This universal interface enables the AI system to adapt to different data sources and vendors while remaining integrated within the carrier network, resolving the contradiction between deployment ease and data collection versatility.
2Adaptability or versatility
If conventional SMO functions and RICs are used to facilitate data extraction, then components from different vendors can be managed, but the ability to make sense of disaggregated data and enable dynamic network decisions is lacking
Solution Approach 1:
The patent introduces an AI system as an intermediary layer between the multi-vendor data collection interface and the network control functions. This AI intermediary processes disaggregated data from multiple vendors, extracts meaningful insights, and generates dynamic network decisions, thereby enhancing productivity while maintaining the ability to manage multi-vendor components.
3Quantity of substance
If disaggregated data from different solution providers is collected, then more network data is available, but network operators lack the capability to utilize this data for monetization and dynamic decisions
Solution Approach 1:
The patent replaces manual data analysis and processing mechanisms with an automated AI system that collects, processes, and analyzes disaggregated network data. This substitution transforms the mechanical process of data utilization into an intelligent automated system, enabling network operators to easily operate with large volumes of data and derive monetization opportunities and dynamic decisions without manual intervention.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, obtaining first data from a first component of a disaggregated wireless communication network; obtaining second data from a second component of the disaggregated wireless communication network; formatting the first data and the second data for use in a generative artificial intelligence (AI) process, wherein the formatting results in formatted data; applying the formatted data to the generative AI process, wherein the generative AI process results in one or more first commands for the first component of the disaggregated wireless communication network; and transmitting the one or more first commands to the first component of the disaggregated wireless communication network. Other embodiments are disclosed.