Radio Network Node Alarm Detection in 5G Clusters
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Solution Overview
Problem
Current systems face challenges in detecting clustered alarm messages in 5G wireless networks, where multiple alarms can occur simultaneously, leading to potential missed messages and reduced system capacity due to high complexity detector algorithms or inefficient resource allocation.
Innovation Solution
A method in a radio network node that dynamically reconfigures radio settings to enhance detection capability for overlapping or interfered messages, including lowering detection thresholds and allocating additional hardware resources, thereby improving alert message detection performance while maintaining system capacity and reducing false alarm rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a high complexity detector algorithm is used to detect clustered alarm messages, then the detection reliability is improved, but the device complexity and hardware capacity requirements increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-configuring multiple detection algorithms with different complexity levels and pre-defining transition criteria between them. When an alarm message is detected, the system has already prepared alternative algorithms that can be activated without real-time computation overhead, thus improving reliability while controlling complexity.
Solution Approach 2:
The detection algorithm complexity is made dynamic rather than static. The system transitions between different algorithm complexity levels based on the detected alarm patterns and cluster characteristics. This allows the system to use simpler algorithms for isolated alarms and more complex algorithms for clustered alarms, optimizing the balance between reliability and device complexity.
2Reliability
If separate frequency/time resources are allocated for random access to all sensors to avoid collisions, then the detection reliability is improved, but the system capacity is reduced due to resource waste
Solution Approach 1:
The system changes detection parameters dynamically based on the alarm situation. Instead of allocating fixed resources for all sensors, the system adjusts detection thresholds, time windows, and algorithm complexity parameters in response to detected alarms. This allows efficient use of resources for actual alarm detection while maintaining system capacity for other communications.
Solution Approach 2:
The detection system serves itself by automatically adjusting its resource allocation and detection parameters based on the incoming alarm patterns. The system monitors the alarm traffic and self-adapts its detection capabilities without requiring pre-allocated dedicated resources for each sensor, thus maintaining both reliability and system capacity.
3Productivity
If resource allocation is optimized for ordinary cellular traffic, then the system capacity is improved, but the detection capability for rare alarm events is reduced
Solution Approach 1:
The system implements dynamic resource allocation that adapts between serving ordinary cellular traffic and detecting alarm events. During normal operation, resources are optimized for cellular traffic to maintain high system capacity. When alarm patterns are detected, the system dynamically reallocates resources to detection algorithms, ensuring reliable alarm detection without permanently sacrificing system capacity.
Solution Approach 2:
The system employs periodic monitoring and evaluation of alarm patterns to determine when to switch between traffic optimization mode and detection enhancement mode. This periodic assessment allows the system to maintain high system capacity during normal operation while periodically activating enhanced detection capabilities when alarm clusters are identified, balancing both objectives.
Data Source
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AI summary
The present disclosure relates to methods and devices in clustered alarm scenarios. More particularly the disclosure pertains to methods and arrangements for detecting several messages of a preconfigured message type, arriving sequentially in time. This disclosure proposes a method, performed in a radio network node, of detecting several messages of a preconfigured message type. The method comprises detecting SI a first message of the preconfigured message type, the first message being associated with an event. The method further comprises reconfiguring S3, in the radio network node, in response to the detection, at least one radio setting related to detecting further messages of the preconfigured message type and monitoring S4 a radio spectrum for further messages of the preconfigured message type using the reconfigured radio settings.