Predictive Network Testing Using Symbol Displacement Metrics
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Solution Overview
Problem
Current network testing methods are inadequate for predicting network performance under different modulation formats and do not provide sufficient margin analysis to prevent impairments in hybrid fiber-coaxial cable networks, leading to potential service degradation.
Innovation Solution
A method and apparatus that utilize symbol-level performance metrics by demodulating communication signals, computing displacements of received symbol samples, and comparing them to decision thresholds for different modulation formats to evaluate network performance and estimate error margins, enabling predictive testing and proactive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current test equipment requires users to enter parameters to define signals for measurement, then the equipment can perform basic signal measurement, but it cannot predict network performance under different modulation formats or provide sufficient margin analysis
Solution Approach 1:
The system performs preliminary demodulation of the communication signal to obtain received symbol samples and modulation symbol decisions before actual performance evaluation. By computing displacements of received symbol samples with respect to modulation symbol decisions in advance, the system prepares predictive metrics that can be used to evaluate network performance for different modulation formats without requiring separate measurements for each format.
Solution Approach 2:
The system compares computed displacements to decision thresholds associated with different modulation formats (e.g., switching from 64-QAM to 256-QAM thresholds) to evaluate network performance for the second modulation format. This parameter change approach allows the same received signal to be evaluated under multiple modulation format assumptions, providing predictive capability without retransmission.
2Reliability
If the system uses symbol-level performance metrics to compute displacements and compare to decision thresholds, then predictive network performance evaluation is achieved, but the device complexity increases
Solution Approach 1:
The system introduces an intermediary processing stage that demodulates the communication signal to obtain received symbol samples and modulation symbol decisions. This intermediary step converts the raw modulated signal into a form that can be easily compared against decision thresholds for different modulation formats, simplifying the overall evaluation process while maintaining high predictive accuracy.
Solution Approach 2:
The system computes displacements of received symbol samples with respect to modulation symbol decisions and uses this feedback information to evaluate network performance. By continuously monitoring these displacements and comparing them to decision thresholds, the system provides real-time predictive metrics that enable proactive network maintenance and format optimization.
3Adaptability or versatility
If the system evaluates network performance for a second modulation format using displacements from the first modulation format, then adaptability to different modulation formats is improved, but measurement precision may be compromised
Solution Approach 1:
The system performs preliminary demodulation to obtain received symbol samples and modulation symbol decisions that are format-agnostic. By computing displacements before committing to a specific modulation format evaluation, the system preserves the integrity of the raw signal information and can accurately evaluate performance for any modulation format by simply changing the decision thresholds.
Data Source
AI summary
The invention relates to a method and apparatus for evaluating a network and for predicting network performance for a higher order modulation by analyzing network signals modulated using a lower order modulation format. A margin index may be generated for the current or projected modulation formats based on displacement vectors for received symbols to indicate a margin remaining before a codeword error occurs to alert the network operator of potential performance issues before actual codeword errors occur.