Narrow Band Interference Detection in Wireless Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless local area networks (WLANs) face interference from non-WLAN devices like microwave ovens, which cannot be coordinated, leading to performance degradation, and existing methods require continuous scanning, disrupting normal user communications.
Innovation Solution
A method that infrequently scans wireless channels using commercially available WiFi/WLAN devices to detect microwave oven interference by processing FFT magnitude data, estimating duty cycles, and classifying signals based on narrow band periodicity, minimizing memory usage and impacting normal operations minimally.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous scanning is performed to detect interference, then detection reliability is improved, but normal user communications are disrupted
Solution Approach 1:
The system performs periodic scanning at specific intervals rather than continuous scanning. The WLAN device scans for interference at predetermined times when user data transmission is less critical, allowing interference detection while minimizing disruption to normal communications.
Solution Approach 2:
The system performs preliminary interference detection scans before initiating or during periods of low user data activity. By scanning in advance or during idle periods, the system identifies interference without significantly impacting ongoing user communications.
2Productivity
If coarse spectrum measurements are taken infrequently, then impact on normal operations is minimized, but measurement precision deteriorates
Solution Approach 1:
The system uses FFT magnitude data as an intermediary representation of the spectrum rather than performing full spectrum analysis. This intermediary data structure provides sufficient information for interference detection while requiring minimal processing and memory resources, enabling infrequent scanning without impacting normal operations.
Solution Approach 2:
The system extracts only the essential interference detection information from the spectrum data using FFT magnitude values, rather than analyzing the complete spectrum. This extraction approach provides adequate precision for detecting narrowband interference while minimizing processing overhead and memory usage.
Data Source
AI summary
A method detects narrow band interference in wireless networks by first thresholding each block of samples to produce thresholded samples. The samples are normalized frequency magnitudes obtained from a spectrum of a wireless signal in a channel. Each block of the thresholded samples is summed to produce a thresholded value for each block. Then, thresholded values are autocorrelated to determine whether a bandwidth of the wireless signal is consistent with narrow band interference.