FWA CPE Coverage Detection During Network Outages
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Solution Overview
Problem
In 5G NSA networks, there is no reliable mechanism to predict which FWA CPEs will be impacted by a planned outage of 4G and 5G base stations, leading to disruptions in network connectivity and poor user experience due to resource consumption and failure to identify disconnected FWA CPEs during outages.
Innovation Solution
A coverage detection system that filters FWA CPEs based on age out time periods and determines the impact of planned outages by analyzing 4G and 5G base station outages, predicting service impacts such as failover possibilities and complete loss of service, thereby conserving resources and improving user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current techniques are used to predict 4G and 5G base stations connected to FWA CPE, then network connectivity can be maintained, but computing resources and networking resources are consumed causing poor user experience during planned outages
Solution Approach 1:
The system performs preliminary actions by receiving outage information before the planned network outage occurs, identifying affected FWA CPEs in advance, and notifying them of the upcoming disruption. This allows the system to predict which CPEs will be impacted without consuming excessive computing resources during the actual outage event, thereby maintaining reliability while reducing resource consumption.
2Stability of the object's composition
If current techniques are used to predict base station connections, then service continuity can be maintained, but the system fails to identify disconnected FWA CPEs during outages
Solution Approach 1:
The system establishes a feedback mechanism by comparing the planned outage information with the actual network status, identifying FWA CPEs that were predicted to be affected but actually remained connected (or vice versa). This feedback loop allows the system to learn from discrepancies and improve its prediction accuracy for future outages, ensuring both service continuity and accurate identification of disconnected CPEs.
3Ease of operation
If comprehensive prediction of FWA CPE impact is performed, then user experience can be improved, but device complexity increases
Solution Approach 1:
The system segments the prediction process into distinct modular components: receiving outage information, identifying affected FWA CPEs, determining service impact levels, and notifying users. Each module performs a specific function independently, making the overall complex prediction system easier to manage, maintain, and scale while improving user experience through comprehensive impact assessment.
Data Source
AI summary
A device may receive a list of 4G base stations and 5G base stations associated with outages and identifiers of FWA CPEs associated with the 4G base stations and the 5G base stations, and may filter identifiers of the FWA CPEs from the list, that fail to satisfy an age out time period, to generate a filtered list. The device may determine whether all 4G base stations are out of service for a particular identifier of remaining identifiers included in the filtered list, and may identify a particular FWA CPE associated with the particular identifier as out of service. The device may determine whether all 5G base stations, associated with operational 4G base stations, are out of service for the particular identifier, and may identify the particular FWA CPE associated with the particular identifier as having only 4G service.