Conversational RAN Constraint Definition for Deployment Planning
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Solution Overview
Problem
The high infrastructure costs and power consumption of radio access networks (RANs) in the telecommunications industry, particularly in the transition to 5G technology, are exacerbated by challenges in defining constraints for RAN design and deployment, leading to increased development and maintenance costs and reduced upgrade flexibility.
Innovation Solution
An analytics system utilizing a large language model (LLM) to assist users in identifying and defining constraints through a conversational user interface, generating precise machine-readable language descriptions for RAN deployments, and integrating with an automation platform to build, test, and deploy solutions that meet user requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional RAN development methods are used, then infrastructure costs and power consumption are high, but adopting innovative software solutions and disaggregated architectures introduces technical challenges in constraint definition and deployment complexity
Solution Approach 1:
The patent introduces an analytics system as an intermediary between user requirements and RAN deployment configurations. This system automatically defines constraints, generates deployment plans, and manages the complexity of disaggregated architectures, allowing users to benefit from energy-efficient software solutions without directly dealing with the technical challenges of constraint definition and deployment complexity
Solution Approach 2:
The analytics system enables self-service deployment by automatically generating constraint definitions and deployment configurations based on user-provided requirements. The system self-manages the complex processes of translating high-level requirements into specific technical constraints and deployment plans, reducing the need for manual intervention and expert knowledge
2Adaptability or versatility
If innovative software solutions and disaggregated architectures are adopted to reduce costs, then upgrade flexibility improves, but development and maintenance costs increase due to technical challenges in constraint definition
Solution Approach 1:
The analytics system serves as an intermediary that handles the complex task of constraint definition and translation. It converts high-level user requirements into precise technical constraints needed for disaggregated architectures, thereby maintaining upgrade flexibility while reducing the development burden on users who lack specialized knowledge
Solution Approach 2:
The system performs preliminary actions by automatically generating constraint definitions and deployment configurations before actual implementation. This advance preparation of technical specifications simplifies subsequent development and maintenance activities, allowing users to adopt flexible architectures without bearing the full burden of complex constraint management
3Reliability
If manual constraint definition and deployment planning are performed, then control over RAN configuration is high, but time-to-market and development efficiency are reduced
Solution Approach 1:
The analytics system enables self-service constraint definition and deployment planning by automatically generating configurations based on user requirements. This maintains configuration control through user-provided high-level specifications while dramatically improving development efficiency by eliminating manual constraint translation and deployment planning tasks
Solution Approach 2:
The system transforms the parameter representation from detailed technical constraints to high-level user requirements. By changing the parameter space from specific technical specifications to abstract functional requirements, the system maintains configuration control at the requirement level while automating the generation of detailed deployment parameters, thereby improving productivity
Data Source
AI summary
Various aspects of the subject technology relate to systems, methods, and machine-readable media for cross-platform programmable network communication. The method includes receiving, via a conversational user interface (UI), a request from a user for a radio access network (RAN), the request including a description of a set of requirements for the RAN made in a conversation format. The method also includes generating a set of constraints for network hardware of the RAN based on the request. The method also includes providing, via the conversational UI, a description of the set of constraints to the user. The method also includes generating, based on an approval of the set of constraints from the user, a solution to a deployment for the network hardware of the RAN according to the set of constraints. The method also includes outputting a description of the solution including attributes of the solution.