Qualcomm Incorporated

David Loweth Winslow

Diego Calzolari

John Boro

Guilherme Hoefel

Liang Zhao

Daniel Fred Filipovic

Jie Wu

Jordan C Cookman

Kevin Robert Boyle

Adrianus Van Bezooijen

Erwin Spits

Maurice Adrianus De Jongh

Peyman Hesami

Robbin Damen

Certain aspects of the present disclosure provide techniques for adaptively tuning a wireless data transmission system in an electronic device, including receiving one or more operating characteristics of a wireless data transmission system of a device; determining, using a wireless data transmission system configuration model, a target wireless data transmission system configuration based on the one or more operating characteristics; and implementing the target wireless data transmission system configuration in the wireless data transmission system.

Machine learning-assisted adaptive antenna tuning

Techniques and apparatus for tuning a wireless data transmission system in an electronic device. One example method includes receiving a measured impedance value corresponding to a current user interaction state with respect to one or more antennas of a mobile device; determining a user interaction stability state of the mobile device based on the measured impedance value and a set of historical impedance values; classifying the current user interaction state based at least on the measured impedance value and a plurality of impedance values from the set of historical impedance values; and tuning the one or more antennas based on the classified current user interaction state and the determined user interaction stability state of the mobile device.

Avoiding ping-pong between different antenna tuning configurations

A wireless communication system includes: a first sub-system including a first radio and a second radio, each including a transceiver or a receiver; and a second sub-system coupled to the first sub-system and including: a first antenna configured to convey signals; a first tuner coupled to the first antenna; and a controller coupled to the first tuner, the controller being configured to cause the first tuner to adjust a characteristic of the first tuner; where the controller and/or the first tuner is configured to provide, to the first sub-system, an indication of an effect on operational performance of a portion of the second sub-system coupled to the second radio based on operation of the first tuner or the first antenna, or a combination thereof; where the first sub-system is configured to modify operation of the second radio based on the indication of the effect on operational performance.

Radio control based on operational performance feedback

Certain aspects of the present disclosure provide techniques for adaptively tuning a wireless data transmission system in an electronic device, including: generating a plurality of measurements of an element of the wireless data transmission system in the electronic device; generating a determined use case for the electronic device based on a use case determination model and the plurality of measurements; determining one or more antenna settings associated with the determined use case; tuning the wireless data transmission system based on the one or more antenna settings; and transmitting data via the wireless data transmission system using the one or more antenna settings.

Machine learning-assisted use case classification and adaptive antenna tuning

An apparatus includes a radio-frequency (RF) path that includes an antenna tuner. The apparatus also includes calibration circuitry coupled to the antenna tuner. The calibration circuitry is configured to selectively isolate an antenna from a component of the RF path.

Calibration and adaptive control of antenna tuners

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San Diego, CA, United States of America

David Loweth Winslow