RSSI Statistical Analysis for Jamming Detection in Home Alarms
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Solution Overview
Problem
Current jamming detection systems in wireless communication systems struggle to differentiate between interference from malicious jamming devices and benign nearby wireless systems, leading to high false alarm rates.
Innovation Solution
The method involves continuously measuring the Received Signal Strength Indicator (RSSI) and calculating its average and variance over time to differentiate between jamming signals and signals from nearby wireless systems, using predetermined thresholds to classify the signal origin as 'Jammer', 'Carrier', or 'Noise', thereby reducing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If jamming detection is performed using traditional methods, then jamming signals can be detected, but false alarms increase due to inability to differentiate from benign wireless systems
Solution Approach 1:
The patent changes the parameters used for jamming detection from simple signal presence detection to analyzing multiple statistical parameters (mean, variance, skewness, kurtosis) of the received signal. By examining these parameter combinations, the system can differentiate between jamming signals and benign wireless transmissions, thereby improving detection accuracy while reducing false alarms
Solution Approach 2:
The system implements feedback by continuously monitoring signal parameters and comparing them against established thresholds and patterns. The detection algorithm uses feedback from statistical analysis to dynamically adjust classification decisions, improving the reliability of jamming detection while maintaining precision in signal origin classification
2Measurement precision
If statistical parameters like mean and variance are calculated for jamming detection, then detection capability improves, but computational complexity increases
Solution Approach 1:
The patent applies partial action by selectively calculating only the necessary statistical parameters (mean, variance, skewness, kurtosis) required for effective jamming detection rather than performing complete signal analysis. This approach provides sufficient detection accuracy while keeping computational requirements manageable for embedded alarm system processors
Data Source
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AI summary
A method and a system for detecting an interference signal and classifying the interference signal into two or more classes by - repeatedly measuring (201) a received signal strength indicator (RSSI) of a received signal; - repeatedly calculating an average value (205) of the received signal strength indicator over a first time-period; - repeatedly calculating a variance value (210) of the received signal strength indicator over a second time-period, said second time period at least partly overlapping said first time period; - comparing the calculated average value (215) to a predetermined threshold average value; - comparing the calculated variance value (220) to a predetermined threshold variance value; and - classifying the signal into one of two or more classes (235) based on the comparisons (215, 220), one class being indicative of a jamming condition. The system comprises an antenna, a transceiver and a processor.