Qualcomm Incorporated

Apple Inc.

Intel Corporation

Aditya Narain Srivastava

Guttorm Ringstad Opshaug

Suhas H Sheshadri

Harsha Shirahatti

Sai Pradeep Venkatraman

Gengsheng Zhang

William J Bencze

Glenn D Macgougan

Rajesh Bezawada

Lei Wang

Weihua Gao

Madhusudan Chaudhary

Dominic Gerard Farmer

Ju-Yong Do

Glenn Donald MacGougan

Ashwin Deepak Swaminathan

Benjamin A Werner

Michael P Dal Santo

Sachin J Sane

Isaac Thomas Miller

Richard B Warren

Shankar Sadasivam

Stephen P Jackson

Pejman Lotfali Kazemi

Kumar Gaurav Chhokra

Ron Rotstein

Abhijeet Bisain

Christina Selle

Ozgur Ekici

Balaji Subramanyam Natakala

Piero Zappi

Muralidhar Reddy Akula

Milind Patil

Santiago Mazuelas

Abhishek Adappa

Sachin Kumar Prabodhkumar Vyas

Fatemeh Ghafoori

Mohamed Youssef

Cheng Jia

Yi-Wen Liao

Alexandru Popovici

Helena D O'shea

Sachin Vyas

Mojtaba Bahrami

Helena D O Shea

Balaji Natakala

Suhas Hariharapura Sheshadri

User equipment (UE) may determine a probability that a cellular network may allocate a resource block to the UE having a frequency that, when a cellular transmitter of the UE transmits a radio frequency (RF) signal using the resource block, a harmonic signal may be generated that interferes with a global navigation satellite systems (GNSS) signal received by a GNSS receiver of the UE. The probability may be determined based on a number of factors that may impact resource block allocation, including a location of the UE, a current date and/or time, a historical allocation of resource blocks (which may be crowdsourced), a client type associated with a signal to be transmitted, a signal environment at the UE, real world conditions, and so on. Based on the probability, the UE may selectively perform a mitigation procedure or transmit an RF signal without performing the mitigation procedure.

Selective cellular interference mitigation for GNSS

This disclosure is directed to shared antenna tuning. An electronic device may receive a global navigation satellite system (GNSS) tune request to tune a shared antenna to a GNSS signal frequency. The electronic device may then tune the antenna to the GNSS signal frequency and enable a GNSS receiver. The electronic device may also receive a cellular tune request to tune the antenna to a cellular frequency. The electronic device may tune the antenna to a cellular frequency and may deactivate the GNSS receiver or blank the GNSS receiver. In some embodiments, the electronic device may also communicate with a Low Earth Orbit (LEO) satellite. During LEO satellite communication, the electronic device may transmit a signal to blank a GNSS L1 receiver to avoid signal interference with the LEO satellite communication, and activate a GNSS L5 receiver to receive GNSS signals.

Systems and methods for shared antenna tuning

Described herein are techniques to enable a mobile device to perform multi-source estimation of an altitude for a location. A baseline altitude may be determined at ground level for a location and used to calibrate a barometric pressure sensor on the mobile device. The calibrated barometric pressure sensor can then estimate changes in altitude relative to ground level based on detected pressure differentials, allowing a relative altitude to ground to be determined. Baseline calibration for the barometric sensor calibration can be performed to determine an ambient ground-level barometric pressure.

Location of interest altitude and determining calibration points

In some implementations, a processor may retrieve predicted positioning data and predicted orbital data from global navigation satellite service (GNSS) positioning circuitry of a wireless device in response to a request for device time. The processor may retrieve long-term learning (LTL) data for a temperature sensing crystal (TSX) of the wireless device, the LTL data including S-curve characteristics of the TSX, and the time tracking uncertainty of the TSX. The processor may generate a GNSS-based device time estimate using the predicted positioning data and the predicted orbital data. The processor may perform TSX-based device time processing by updating the GNSS-based device time estimate using a clock signal of the TSX to generate a final device time estimate, the updating based on the retrieved LTL data for the TSX.

Global navigation satellite system (GNSS) and temperature sensing crystal (TSX) based device time service

Systems and methods for multi-carrier frequency grip detection are described. For example, a method may include determining a first signal strength of a first signal received using a first antenna from a source device; determining a second signal strength of a second signal received using a second antenna from the source device; comparing the first signal strength with the second signal strength; and detecting a detuned condition for a device including the first antenna and the second antenna based on the comparison of the first signal strength with the second signal strength.

Systems and methods for handgrip and case detection for multi-carrier wireless systems

A mobile wireless transmitter is detected from location data received for a plurality of wireless transmitters obtained through crowdsourcing or wardriving. Location data is held until sufficient time or enough location data is collected from which movement of a wireless transmitter can be detected. Sets of measurement data for each wireless transmitter are determined from the collected location data. The sets of measurement data may include, e.g., Service Set Identifier (SSID), a round trip time (RTT) variance, and/or a neighbor relationship graph for each wireless transmitter. The mobile wireless transmitter is identified from the sets of measurement data. An almanac database may then be published in which any mobile wireless transmitters are identified or excluded.

Detection of mobile wireless terminals in crowdsourced data

Method, mobile device, computer program product, and apparatus for performing Fine Grain Position Data Collection is described. In one aspect a mobile device performs measurement batching of data, for example positioning and AP measurement data. In some aspects, the mobile device processes positioning and AP measurement data in response to a batch trigger. The mobile device may send the processed measurement batch to a server for analysis or processing. A batch trigger may include receiving a positioning fix with high confidence such that the mobile device may backfilter or otherwise correct mobile sensor based positioning data associated with AP measurements. The server may interpret the data from the measurement batches identified from a number of different mobile devices to calculate position of APs within an environment.

Measurement batching

Methods, systems, computer-readable media, and apparatuses for determining a flight route for a flight of an unmanned aerial vehicle (UAV) are presented. The flight-specific route for the UAV is determined dynamically during the flight or in advance before the flight, using navigation assistance data that includes flight-specific navigation assistance data for a plurality of geographic zones determined based on flight-specific information. The flight-specific navigation assistance data includes flight-specific ranking data for the plurality of geographic zones that can be used by the UAV or a server to determine the flight route.

Navigation assistance data and route planning for drones

A method of auto-calibrating light sensor data of a mobile device includes, obtaining, by the mobile device, one or more reference parameters representative of light sensor data collected by a reference device. The method also includes collecting, by the mobile device, light sensor data from a light sensor included in the mobile device, itself. One or more sample parameters of the light sensor data obtained from the light sensor included in the mobile device are then calculated. A calibration model is then determined for auto-calibrating the light sensor data of the light sensor included in the mobile device based on the one or more reference parameters and the one or more sample parameters.

Auto-calibrating light sensor data of a mobile device

According to various embodiments, there is provided a method for controlling a vehicle, the method including detecting a triggering event. The method further includes, in response to detecting the triggering event, determining updated dimensions of the vehicle. The method further includes adjusting operation of the vehicle based on the updated dimensions.

Shape detecting autonomous vehicle

Methods and systems for utilizing priority based geofences are disclosed. A mobile device receives, from another device over a wireless network, at least one geofence, each of the at least one geofence having an assigned priority level indicating an importance of the at least one geofence, wherein the assigned priority level is one of a plurality of priority levels and is received from the other device over the wireless network, determines, based on the priority level of the at least one geofence, a geofence breach detection method and an evaluation rate, and monitors a position of the mobile device relative to the at least one geofence at the evaluation rate using the geofence breach detection method.

Methods and systems for priority based geofences

A system and method for a mobile device to efficiently use a geofence capability without draining its battery, and to allow flexibility in specifying various parameters related to geofencing, such as the latency and confidence in determining when or where a geofence breach occurs, and reducing the probability of not detecting a geofence breach.

Geofence breach confidence

Examples disclosed herein relate to a method performed at a first mobile station that includes receiving a request for positioning assistance data from a second mobile station over a communication link; and transmitting one or more messages to the second mobile station in response to the request, wherein the one or more messages include the requested positioning assistance data, wherein the first mobile station is on a synchronous network.

Synchronous network device time transfer for location determination

Mechanism to reduce missing breach detection in geofencing solution

Growing community of inventors

Fremont, CA, United States of America

Aditya Narain Srivastava