View source for 17821626. USER EQUIPMENT-BASED (UE-BASED) POSITIONING BASED ON SELF-RADIO FREQUENCY FINGERPRINT (SELF-RFFP) simplified abstract (QUALCOMM Incorporated)

=USER EQUIPMENT-BASED (UE-BASED) POSITIONING BASED ON SELF-RADIO FREQUENCY FINGERPRINT (SELF-RFFP)=


==Organization Name==

[[:Category:QUALCOMM Incorporated|QUALCOMM Incorporated]]


[[Category:QUALCOMM Incorporated]]

==Inventor(s)==

[[:Category:Mohammed Ali Mohammed Hirzallah of San Diego CA (US)|Mohammed Ali Mohammed Hirzallah of San Diego CA (US)]][[Category:Mohammed Ali Mohammed Hirzallah of San Diego CA (US)]]

[[:Category:Marwen Zorgui of San Diego CA (US)|Marwen Zorgui of San Diego CA (US)]][[Category:Marwen Zorgui of San Diego CA (US)]]

[[:Category:Srinivas Yerramalli of San Diego CA (US)|Srinivas Yerramalli of San Diego CA (US)]][[Category:Srinivas Yerramalli of San Diego CA (US)]]

==USER EQUIPMENT-BASED (UE-BASED) POSITIONING BASED ON SELF-RADIO FREQUENCY FINGERPRINT (SELF-RFFP) - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17821626 titled 'USER EQUIPMENT-BASED (UE-BASED) POSITIONING BASED ON SELF-RADIO FREQUENCY FINGERPRINT (SELF-RFFP)

==Simplified Explanation==

In an aspect, a UE may transmit one or more reference signals. The UE may obtain one or more self-radio frequency fingerprint (self-RFFP) measurements based on reflections of the one or more reference signals transmitted by the UE. The UE may determine a location of the UE based on applying a machine learning model to the one or more self-RFFP measurements.

* The patent application involves a method for determining the location of a User Equipment (UE) by analyzing self-radio frequency fingerprint measurements.
* The UE transmits reference signals and collects self-RFFP measurements based on reflections of these signals.
* A machine learning model is applied to the self-RFFP measurements to determine the location of the UE accurately.

== Potential Applications ==
* Location-based services for mobile devices
* Indoor navigation systems
* Asset tracking in industrial environments

== Problems Solved ==
* Improving location accuracy in indoor environments
* Enhancing user experience with location-based services
* Optimizing asset management and tracking processes

== Benefits ==
* Increased precision in determining UE location
* Enhanced performance of location-based applications
* Improved efficiency in asset tracking and management


==Original Abstract Submitted==

In an aspect, a UE may transmit one or more reference signals. The UE may obtain one or more self-radio frequency fingerprint (self-RFFP) measurements based on reflections of the one or more reference signals transmitted by the UE. The UE may determine a location of the UE based on applying a machine learning model to the one or more self-RFFP measurements.



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