Robust Interference Detection Using Median-Scaled Spectral Density
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Solution Overview
Problem
Conventional narrowband interference excision techniques in DSSS receivers fail to reliably detect interference while maintaining low false-positive detection rates, often misidentifying high-powered desired signals as interference or failing to detect less-powerful interference due to high false-detection thresholds.
Innovation Solution
A communication device and method that perform transform operations on input signals to generate spectral periodograms, calculate spectral vector powers, determine ordered statistic spectral powers, and use statistically-scaled spectral density vectors to set detection thresholds, allowing for reliable identification and excision of interference-including bins while minimizing false detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional narrowband interference excision techniques are used, then interference detection is performed, but false-positive detection rate increases and reliability decreases
Solution Approach 1:
The patent implements dynamic threshold adjustment by calculating detection thresholds based on the statistical distribution of spectral power values. Instead of using fixed thresholds, the system adapts thresholds to the actual signal conditions by computing ordered statistics from the spectral data, allowing the detection criterion to dynamically respond to varying signal environments and reduce false positives
Solution Approach 2:
The patent transforms the detection approach by changing the parameter used for threshold determination from fixed values to statistically-derived values. By computing detection thresholds based on ordered statistics of spectral power values and comparing against a probability threshold, the system adjusts the detection parameters to achieve both high reliability and low false-positive rates
2Measurement precision
If high detection thresholds are used to reduce false positives, then false-detection rate decreases, but ability to detect less-powerful interference is reduced
Solution Approach 1:
The patent resolves this contradiction by changing the threshold parameter from a fixed high value to a dynamically calculated value based on ordered statistics. The detection threshold is computed as a function of the spectral power distribution, allowing it to adapt to the actual signal environment and maintain appropriate sensitivity without excessive false positives
Solution Approach 2:
The system uses feedback from the spectral power distribution itself to determine the detection threshold. By computing ordered statistics from the observed spectral data and using these to set the detection criterion, the system creates a feedback loop that automatically adjusts sensitivity based on the actual signal conditions, preventing both false positives and missed detections
Data Source
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AI summary
A communication device (102) may include a communication interface (106) configured to receive signals (101a,101b) and a controller (110) configured to: receive an input signal based on the received signals; perform transform operations on the input signal to generate a spectral periodogram of the input signal; calculate spectral vector powers for each bin of a plurality of bins of the spectral periodogram; determine a median spectral power for a selected range of bins of the plurality of bins; generate a median-scaled spectral density vector based on the median spectral power and a reference spectral density of an expected signal; calculate a detection threshold vector based at least in part on the median-scaled spectral density vector; and identify one or more interference-including bins of the plurality of bins of the spectral periodogram by comparing the spectral vector powers for each bin of the plurality of bins to the detection threshold vector.