O-RAN nRT-RIC Interface for Near-Real-Time O-Cloud Control
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Solution Overview
Problem
The absence of a near real-time interface between the near-real-time RIC (nRT-RIC) and the O-Cloud in existing O-RAN architectures limits the ability of the nRT-RIC to control O-Cloud resources efficiently, leading to high latency responses and unbalanced utilization of computational and hardware resources.
Innovation Solution
Implementing an O-Cloud optimization policy via a direct interface between the nRT-RIC and the O-Cloud, allowing for a defined response time between 10 ms and 1 s, which enables the nRT-RIC to control O-Cloud resources in near real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a direct interface is implemented between nRT-RIC and O-Cloud, then resource control latency is reduced and response speed is improved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary communication interface that bridges the nRT-RIC and O-Cloud, enabling direct near-real-time control while managing system complexity through standardized protocols and abstraction layers. This intermediary structure allows fast resource control without directly coupling the complex components.
Solution Approach 2:
The system architecture is segmented into distinct functional modules (nRT-RIC, O-Cloud, management interfaces) with defined interaction protocols. This segmentation allows the direct interface to provide fast control where needed while isolating complexity into manageable segments that can be independently developed and maintained.
2Productivity
If near real-time control is implemented, then resource utilization balance is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic control cycles where the nRT-RIC monitors resource utilization metrics and activates near-real-time control operations only when imbalances are detected. This periodic approach maintains resource utilization balance while avoiding continuous energy-intensive control operations.
Solution Approach 2:
The system dynamically adjusts control parameters such as sampling intervals and threshold values based on current network conditions and resource states. When resource utilization is already balanced, control operations are reduced or suspended, lowering energy consumption while maintaining productivity when needed.
Data Source
AI summary
A system for implementing an open cloud (O-Cloud) optimization policy by an application hosted in a near real-time radio access network Intelligent Controller (nRT-RIC) of a telecommunications network. The system includes a memory storing instructions; and at least one processor configured to implement the nRT-RIC within an open radio access network (O-RAN) architecture, the at least one processor configured to execute the instructions to: receive the O-Cloud optimization policy from a non-real-time radio access network Intelligent Controller (NRT-RIC) within a Service Management and Orchestration (SMO) framework of the telecommunications network; control to implement the O-Cloud optimization policy in the O-Cloud computing environment within the O-RAN.