O-RAN Cell Site Validation Engine for Zero-Touch Provisioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing zero-touch provisioning (ZTP) methods for Open RAN (O-RAN) lack accurate and efficient data validation processes, leading to potential errors and inconsistencies in configuring and deploying network devices, especially in large-scale environments.
Innovation Solution
Implementing a validation engine for O-RAN that performs data validation in multiple phases, including design, build, integration, and operational phases, using inventory management and triggers to ensure successful progression through each phase, with automated orchestration and management tools like CI/CD, AI, and ML to facilitate seamless integration of diverse hardware vendors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration methods are used for O-RAN devices, then flexibility and ease of operation are improved, but productivity and time consumption are worsened
Solution Approach 1:
The patent segments the configuration process into distinct phases (design, build, integration, operational) with specific validation rules for each phase. This segmentation enables automated validation while maintaining structured control, resolving the contradiction by allowing fast automated processing without sacrificing configuration precision.
Solution Approach 2:
The patent implements preliminary validation of configuration data before deployment across different phases. By validating data in advance during design and build phases, the system prevents errors before they affect deployment, enabling faster automated provisioning while maintaining configuration accuracy.
2Productivity
If automated zero-touch provisioning is implemented, then productivity and deployment speed are improved, but reliability and measurement precision are worsened due to lack of validation
Solution Approach 1:
The patent implements feedback mechanisms through validation engines that check configuration data against predefined rules at each phase. The validation results feed back into the provisioning process, allowing automated deployment while maintaining reliability through continuous verification and error correction.
Solution Approach 2:
The system performs preliminary validation of all configuration parameters before automated deployment. By validating data in advance during design and build phases, the system ensures configuration accuracy is maintained while enabling fast automated provisioning in the operational phase.
3Reliability
If multi-phase validation is implemented, then reliability and configuration accuracy are improved, but device complexity and process complexity are worsened
Solution Approach 1:
The patent divides the validation process into four distinct phases (design, build, integration, operational), each with specific validation rules and objectives. This segmentation reduces perceived complexity by organizing validation into manageable stages while maintaining comprehensive coverage for high reliability.
Solution Approach 2:
The validation engine serves multiple functions across different phases - validating configuration data, checking parameter consistency, verifying device compatibility, and ensuring compliance with operational requirements. This multi-functionality reduces overall system complexity by using a single unified validation framework rather than separate validation systems for each function.
Data Source
AI summary
Various embodiments provide data validation for a cell site. In some embodiments, the data validation for the cell site is performed in different phases of the O-RAN by a validation engine. Inventory management is employed in those embodiments to capture statuses of the validation. Triggers are created to cause the validation of the cell site to move onto the next phase when one or more previous phases are completed with success statuses.