Machine learning-based positioning with multiple positioning frequency layers
AssigneeQUALCOMM Incorporated
InventorsMohammed Ali Mohammed HIRZALLAH, Srinivas YERRAMALLI, Marwen ZORGUI
Life of this patent
Estimating the term…
Abstract
Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) receives, from a location server, a configuration of a plurality of positioning frequency layers (PFLs) and one or more positioning reference signal (PRS) resources in each of the plurality of PFLs, obtains a first set of measurements of the one or more PRS resources in each of the plurality of PFLs, and applies a machine learning model to the first set of measurements to obtain positioning information associated with the first set of measurements.
Claims30
A method of wireless communication performed by a user equipment (UE), comprising:
- receiving, from a location server, a configuration of a plurality of positioning frequency layers (PFLs) and one or more positioning reference signal (PRS) resources in each of the plurality of PFLs;
- obtaining a first set of measurements of the one or more PRS resources in each of the plurality of PFLs;
- and
- applying a machine learning model to the first set of measurements to obtain positioning information associated with the first set of measurements.
A method of communication performed by a network entity, comprising:
- transmitting, to a user equipment (UE), a configuration of a plurality of positioning frequency layers (PFLs) and one or more positioning reference signal (PRS) resources in each of the plurality of PFLs;
- and
- receiving, from the UE, positioning information associated with a first set of measurements of the one or more PRS resources in each of the plurality of PFLs, the positioning information obtained by the UE by applying a machine learning model to the first set of measurements.
A user equipment (UE), comprising:
- one or more memories;
- one or more transceivers;
- and
- one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to:
- receive, via the one or more transceivers, from a location server, a configuration of a plurality of positioning frequency layers (PFLs) and one or more positioning reference signal (PRS) resources in each of the plurality of PFLs;
- obtain a first set of measurements of the one or more PRS resources in each of the plurality of PFLs;
- and
- apply a machine learning model to the first set of measurements to obtain positioning information associated with the first set of measurements.
A network entity, comprising:
- one or more memories;
- one or more transceivers;
- and
- one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to:
- transmit, via the one or more transceivers, to a user equipment (UE), a configuration of a plurality of positioning frequency layers (PFLs) and one or more positioning reference signal (PRS) resources in each of the plurality of PFLs;
- and
- receive, via the one or more transceivers, from the UE, positioning information associated with a first set of measurements of the one or more PRS resources in each of the plurality of PFLs, the positioning information obtained by the UE by applying a machine learning model to the first set of measurements.
Dependencies are inferred from the claim text.