External Intelligence Layer for Distributed Unit Outage Recovery
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Solution Overview
Problem
Cellular telecommunication networks, particularly 5G networks, experience outages that cause service interruptions, impacting user experiences and requiring effective management strategies to minimize such disruptions.
Innovation Solution
Implement systems and methods for managing user experiences during network outages by detecting communication failures, performing recovery actions, utilizing a radio resource manager (RRM) for redirection, employing an intelligence layer for predictive management, and leveraging backup data centers and containerized microservices to ensure seamless service continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network functions are virtualized and deployed in centralized data centers, then deployment flexibility and scalability are improved, but service interruption time during failures increases
Solution Approach 1:
The patent implements predictive analytics that monitor network conditions and predict failures before they occur. When a failure is predicted, the system proactively redirects traffic to backup data centers before the actual failure happens, eliminating service interruption time while maintaining deployment flexibility through virtualized network functions
2Reliability
If traffic is redirected to backup data centers during failures, then service continuity is improved, but network complexity increases
Solution Approach 1:
The patent introduces an intelligence layer as an intermediary between the radio access network and core network functions. This intelligence layer handles all failure detection, prediction, and traffic redirection logic, simplifying the overall network architecture by centralizing complexity in a dedicated management layer rather than distributing it across multiple network components
3Reliability
If predictive analytics are implemented to predict failures, then service interruption prevention is improved, but computational resources and system complexity increase
Solution Approach 1:
The patent implements predictive analytics selectively for critical network functions and failure modes rather than attempting to predict all possible failures. The system monitors key performance indicators and applies machine learning models only where they provide the most value, achieving effective failure prediction while limiting computational overhead and system complexity
Data Source
AI summary
Embodiments are directed towards systems and methods for managing user experiences during cellular telecommunication outages within a wireless telecommunication network, such as a wireless 5G network. Example embodiments include systems and methods for utilizing an intelligence layer module external to the DU and in communication with the DU, a primary physical data center and a backup physical data center for managing user experiences during a cellular telecommunication network outage. The intelligence layer module external to the distributed unit (DU) communicates with the DU to activate and manage the radio resource manager (RRM) in the DU to reduce interruptions in service during the cellular telecommunication network outages.