LTE/5G RF Device Detection for Geofenced Perimeter Security
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Solution Overview
Problem
Current methods for detecting unauthorized mobile devices in geo-fenced areas, such as livestock and poultry farms, are inadequate, as they either fail to guarantee perimeter security or are prohibitively expensive, and existing systems like video surveillance and biometric scanning are not effective.
Innovation Solution
A system and method utilizing LTE/5G RF monitoring, machine learning, and proprietary RF techniques to passively track and classify mobile devices within a geofenced area, using SDR, mmWave sensors, and FPGAs to monitor and whitelist authorized devices while blacklisting unauthorized ones, leveraging 3GPP protocols without compromising encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video surveillance and movement detectors are used for perimeter security, then detection capability is improved, but cost and effectiveness deteriorate
Solution Approach 1:
The patent replaces mechanical surveillance systems (video cameras, movement detectors) with a wireless communication-based detection system that monitors mobile device signals. The system uses network infrastructure (MME, eNB) and software processing to detect unauthorized devices, eliminating the need for expensive physical surveillance hardware while maintaining perimeter security effectiveness.
Solution Approach 2:
The patent introduces an intermediary detection layer that monitors mobile device communications between the device and the network. By intercepting and analyzing signaling messages (paging messages, tracking area codes) without requiring direct physical observation, the system achieves security monitoring with lower cost and complexity than traditional surveillance systems.
2Reliability
If biometric scanning/screening is implemented, then security detection capability is improved, but cost becomes prohibitively expensive
Solution Approach 1:
The patent uses inexpensive, readily available mobile devices as the detection target. Instead of requiring expensive biometric scanners, the system leverages the existing mobile network infrastructure and standard cellular protocols to identify unauthorized devices. The detection mechanism relies on analyzing standard signaling messages rather than expensive biometric verification hardware.
Solution Approach 2:
The patent makes the mobile network infrastructure serve multiple functions: it not only provides communication services but also simultaneously performs security monitoring and intruder detection. By utilizing the existing network's paging and tracking mechanisms for dual purposes, the system avoids the need for separate expensive biometric scanning systems.
3Reliability
If mobile device detection systems are deployed, then perimeter security is improved, but disruption to authorized users may occur
Solution Approach 1:
The patent applies local quality by creating a geo-fenced detection area with specific perimeter boundaries. The system monitors for unauthorized devices entering this defined geographic zone rather than monitoring all mobile devices globally. By localizing the detection scope to the property boundary area, the system minimizes disruption to authorized users while maintaining effective intruder detection.
Solution Approach 2:
The patent uses partial action by monitoring only specific signaling parameters (paging messages, tracking area codes, TMSI) rather than intercepting all mobile device communications. This selective monitoring approach enables security detection while minimizing interference with normal authorized device operations and communications.
Data Source
AI summary
A system and method of detecting mobile devices is provided. The method comprises a processor sending a soft page message via MSISDN to an MME, tracking at least one of a TMSI, S-TMSI, GUTI, or c-RNTI, and receiving a P-RNTI filtering message from an eNB. A system and method of classifying detected mobile devices is also provided. The method comprises listening on an uplink channel for a detected mobile device, receiving from the detected mobile device capabilities information regarding the detected mobile device, and obtaining a UE model of the detected mobile device where the UE model is determined based on the capabilities information.