Rogue ONU Detection in PON Using Infected Zone Segmentation
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Solution Overview
Problem
In Passive Optical Networks (PON), identifying rogue ONUs that disrupt upstream services by transmitting signals in incorrect time slots is challenging, as existing methods are time-consuming, cause service interruptions, and lack reliability, especially since affected ONUs are not always the ones causing the disturbance.
Innovation Solution
A method and apparatus that determine a rogue ONU by identifying infected zones based on error rates and optical power differences, using two time slot allocations to isolate the rogue ONU candidate, and verifying through error rate checks without interrupting normal communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If powering off/on each ONU one by one to determine rogue ONU, then rogue ONU can be identified, but service interruption occurs and time consumption increases
Solution Approach 1:
The system performs preliminary monitoring of upstream signals to detect error patterns and identify infected zones before attempting rogue ONU isolation. By pre-categorizing ONUs into infected and non-infected zones based on error rates, the system avoids time-consuming trial-and-error power cycling of all ONUs, thus reducing determination time while maintaining identification accuracy.
Solution Approach 2:
The system segments the PON network into infected zones and non-infected zones based on upstream signal error rates. This segmentation allows the system to focus detection efforts only on specific infected zones rather than checking all ONUs uniformly, thereby reducing the time required to identify rogue ONUs while maintaining reliable detection.
2Reliability
If powering off/on each ONU one by one to determine rogue ONU, then rogue ONU can be identified, but normal communication is interrupted
Solution Approach 1:
The system performs preliminary monitoring and identifies infected zones before taking isolation actions. By pre-detecting error patterns and categorizing affected ONUs, the system can implement targeted rogue ONU isolation without interrupting normal communication for non-infected ONUs, thus maintaining service continuity while ensuring accurate identification.
Solution Approach 2:
The system applies different quality control measures to different zones: infected zones undergo monitoring and potential isolation, while non-infected zones continue normal operation without interruption. This localized approach ensures rogue ONU identification accuracy while maintaining service continuity for the majority of normal ONUs.
3Reliability
If using error rate and DBA history to locate rogue ONU, then rogue ONU can be identified, but implementation complexity increases due to lack of recorded data
Solution Approach 1:
The system uses self-service by leveraging existing upstream signal monitoring capabilities already present in the OLT. Instead of requiring external DBA history recording infrastructure, the system generates its own detection data by monitoring upstream signals in real-time, thus achieving reliable rogue ONU identification without increasing device complexity or requiring additional recording systems.
Solution Approach 2:
The system achieves multi-functionality by using the existing upstream signal monitoring function for dual purposes: normal communication management and rogue ONU detection. This universal approach eliminates the need for separate DBA history recording systems, reducing implementation complexity while maintaining identification accuracy.
4Measurement precision
If monitoring upstream signals to detect infected zones, then detection accuracy improves, but processing complexity increases
Solution Approach 1:
The system uses parameter changes by monitoring variations in upstream signal characteristics (error rates, optical power levels) to detect infected zones. By focusing on specific measurable parameters rather than analyzing entire signal waveforms, the system achieves high detection accuracy while keeping processing complexity manageable through targeted parameter monitoring.
Data Source
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AI summary
The present invention provides a method and apparatus for determining a rogue ONU in an OLT of a PON. The method comprises determining an original infected zone based on a first time slot allocation in which each time slot corresponds to one uplink signal of an ONU; determining a new infected zone based on a second time slot allocation in which each time slot corresponds to an uplink signal of an ONU; determining if there is a same ONU in the original infected zone and in the new infected zone to determine rogue ONU candidate; and determining a rogue ONU based on the rogue ONU candidate. The solution disclosed in the present application has the advantages of quick determination of the rogue ONU, no interruption of the normal service and system compatibility etc.