Wireless Fingerprinting for WLAN Proximity Detection
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Solution Overview
Problem
Mobile devices face high power consumption when continuously searching for wireless local area networks (WLANs), leading to reduced battery life, as they need to remain awake for extended periods to detect beacon signals, especially in areas with multiple channels and frequency ranges.
Innovation Solution
A wireless communications device that uses a processor to create and modify fingerprints based on reference signals from cellular networks, allowing it to determine proximity to WLANs only when necessary, thereby reducing unnecessary searches and conserving power by limiting beacon signal searches to specific locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mobile devices continuously search for WLAN beacon signals to maintain network connectivity, then network handoff efficiency is improved, but power consumption increases and battery life decreases
Solution Approach 1:
The system performs preliminary actions by creating and storing WLAN fingerprints at specific cellular network locations in advance. These pre-stored fingerprints are then used for quick comparison during mobility events, eliminating the need for continuous beacon scanning and reducing power consumption while maintaining handoff efficiency.
Solution Approach 2:
Instead of continuous searching, the system implements periodic action by triggering WLAN fingerprint comparisons only at specific intervals or events, such as when the mobile device moves between cellular base stations. This event-driven approach maintains network handoff efficiency while significantly reducing overall power consumption.
2Measurement precision
If mobile devices remain awake for extended periods to detect beacon signals across multiple channels, then WLAN detection accuracy is improved, but battery life is reduced
Solution Approach 1:
WLAN fingerprints including beacon signal characteristics are captured and stored in advance at various cellular network locations. When the mobile device moves, these pre-stored fingerprints are quickly compared against current signals, maintaining detection accuracy without requiring extended awake periods for scanning.
Solution Approach 2:
The system creates copies of WLAN beacon signal characteristics in the form of fingerprints that are stored in the mobile device. These copied representations allow for rapid comparison and identification of WLANs without needing to perform full-scale continuous beacon detection, thereby preserving battery life while maintaining detection accuracy.
3Reliability
If mobile devices perform frequent WLAN searches to ensure seamless network coverage, then network connectivity reliability is improved, but unnecessary power consumption increases
Solution Approach 1:
The system performs preliminary actions by pre-capturing and storing WLAN fingerprints at specific cellular network locations before the mobile device arrives. This allows for reliable network connectivity through quick fingerprint comparisons during mobility events, eliminating unnecessary continuous searches and reducing power consumption.
Solution Approach 2:
The system implements feedback by using stored WLAN fingerprints to quickly determine when a mobile device enters or exits WLAN coverage areas. This feedback mechanism ensures reliable network connectivity by triggering searches only when necessary, based on the comparison results, rather than performing frequent unnecessary searches.
Data Source
Figure 1A
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Figure 2
AI summary
The disclosure is directed to a mobile communication device that measures characteristics or attributes of a first communications network that vary according to physical location within that first communications network to create a fingerprint, or signature, of a location within the first communications network. When the fingerprint of the current location of the mobile device is created it can be compared to a known fingerprint associated with a second communication network to determine the mobile device's proximity to the second communications network. Furthermore, the second and subsequent fingerprint that are generated for a particular communications network can be used to modify the stored fingerprint so as to refine it to improve detecting the proximity to the communications network.