Bit Error Pattern Analysis for Digital System Fault Isolation
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Solution Overview
Problem
Conventional bit error rate testing in digital systems only provides error counts without identifying the root cause of errors, which hinders targeted remediation efforts.
Innovation Solution
A method and system that analyzes bit errors by correlating them with specific sub-patterns within a test sequence to distinguish between random and deterministic errors, enabling identification of specific faults in the digital system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional bit error rate testing is performed to count bit errors, then error detection capability is provided, but root cause identification capability is lost
Solution Approach 1:
The test bit sequence is divided into multiple sub-sequences, each designed to target specific deterministic error sources. By segmenting the error analysis according to sub-sequence type, the system can identify which sub-sequence produces errors, thereby revealing the root cause while maintaining overall error detection capability
Solution Approach 2:
The patent introduces an error analysis component that acts as an intermediary between the BER tester and the test sequences. This component correlates error patterns with specific sub-sequence types to identify deterministic error sources, preserving root cause information that would otherwise be lost in aggregate error counting
2Ease of operation
If aggregate bit error counting is used, then testing simplicity is maintained, but targeted remediation capability is reduced
Solution Approach 1:
The test sequence is segmented into different sub-sequences (e.g., NRZ, RZ, Manchester encoded) that target different deterministic error sources. This segmentation enables targeted remediation by identifying which encoding type or transmission condition causes errors, while the automated analysis maintains operational simplicity
Solution Approach 2:
The system changes test parameters by using different sub-sequences with varying characteristics (encoding types, bandwidth requirements). By observing which parameter variation produces errors, the system enables targeted remediation without significantly complicating the testing process
Data Source
AI summary
Systems and methods are provided for detecting bit errors and further processing bit error information. A method, according to one implementation, includes the step of receiving a binary test sequence pattern generated by a pattern generator at an input to a digital communications system under test, wherein the binary test sequence pattern includes a plurality of sub-patterns. The method also includes the step of receiving an output binary sequence from an output of the digital communications system. Also, the method includes comparing the binary test sequence pattern with the output binary sequence to detect bit errors. Based on correlation characteristics between the bit errors and each of the sub-patterns, the method also includes the step of determining whether the bit errors are caused by random factors or are caused by deterministic factors associated with the digital communications system.