Machine learning-assisted adaptive antenna tuning
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.
1. A method, comprising:
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;
determining, using a first estimator model, one or more estimated operating characteristics of the wireless data transmission system using one or more virtual wireless data transmission system configurations different from the target wireless data transmission system configuration;
determining, using a second estimator model, one or more estimated performance metrics of the wireless data transmission system based on the one or more estimated operating characteristics;
determining an actual performance metric based on the target wireless data transmission system configuration;
determining a best wireless data transmission system configuration of the target wireless data transmission system configuration and the one or more virtual wireless data transmission system configurations based on the actual performance metric and the one or more estimated performance metrics;
generating feedback data based on the determined best wireless data transmission system configuration; and
implementing the target wireless data transmission system configuration in the wireless data transmission system.
2. The method of claim 1 , further comprising updating the wireless data transmission system configuration model based on the feedback data.
3. The method of claim 2 , wherein the wireless data transmission system configuration model is a reinforcement learning model.
4. The method of claim 3 , wherein the feedback data comprises one of:
a reward signal for the reinforcement learning model if the target wireless data transmission system configuration matches the best wireless data transmission system configuration; or
a penalty signal if the target wireless data transmission system configuration does not match the best wireless data transmission system configuration.
5. The method of claim 3 , wherein the feedback data comprises the best wireless data transmission system configuration.
6. The method of claim 1 , wherein the actual performance metric comprises an indicator provided by a network in wireless data communication with the device.
7. The method of claim 6 , wherein the indicator comprises at least one of:
a received signal received power (RSRP) metric;
a received signal received quality (RSRQ) metric;
a signal to noise metric (SNR/SINR); or
a received signal strength indicator (RSSI).
8. The method of claim 1 , wherein the first estimator model comprises a neural network model.
9. The method of claim 1 , wherein the second estimator model comprises a neural network model.
10. The method of claim 1 , further comprising determining an optimal tunecode for an impedance tuner based on the target wireless data transmission system configuration.
11. The method of claim 1 , wherein the one or more operating characteristics comprise:
a real impedance of an element of the wireless data transmission system;
an imaginary impedance of the element of the wireless data transmission system;
a frequency of the wireless data transmission system; and
an antenna tuner state.
12. The method of claim 11 , wherein:
the element is an antenna of the wireless data transmission system, and
the target wireless data transmission system configuration comprises an antenna tuner setting.
13. The method of claim 12 , wherein the antenna tuner setting comprises at least one of an aperture tuner setting or an impedance tuner setting.
14. An apparatus, comprising:
a wireless data transmission system;
memory comprising computer-executable instructions; and
one or more processors configured to execute the computer-executable instructions and cause the apparatus to:
receive one or more operating characteristics of the wireless data transmission system of a device;
determine, using a wireless data transmission system configuration model, a target wireless data transmission system configuration based on the one or more operating characteristics;
determine, using a first estimator model, one or more estimated operating characteristics of the wireless data transmission system using one or more virtual wireless data transmission system configurations different from the target wireless data transmission system configuration;
determine, using a second estimator model, one or more estimated performance metrics of the wireless data transmission system based on the one or more estimated operating characteristics;
determine an actual performance metric based on the target wireless data transmission system configuration;
determine a best wireless data transmission system configuration of the target wireless data transmission system configuration and the one or more virtual wireless data transmission system configurations based on the actual performance metric and the one or more estimated performance metrics;
generate feedback data based on the determined best wireless data transmission system configuration; and
implement the target wireless data transmission system configuration in the wireless data transmission system.
15. The apparatus of claim 14 , wherein the one or more processors are further configured to cause the apparatus to update the wireless data transmission system configuration model based on the feedback data.
16. The apparatus of claim 15 , wherein the wireless data transmission system configuration model is a reinforcement learning model.
17. The apparatus of claim 16 , wherein the feedback data comprises one of:
a reward signal for the reinforcement learning model if the target wireless data transmission system configuration matches the best wireless data transmission system configuration; or
a penalty signal if the target wireless data transmission system configuration does not match the best wireless data transmission system configuration.
18. The apparatus of claim 16 , wherein the feedback data comprises the best wireless data transmission system configuration.
19. The apparatus of claim 14 , wherein the actual performance metric comprises an indicator provided by a network in wireless data communication with the device.
20. The apparatus of claim 19 , wherein the indicator comprises at least one of:
a received signal received power (RSRP) metric;
a received signal received quality (RSRQ) metric;
a signal to noise metric (SNR/SINR); or
a received signal strength indicator (RSSI).
21. The apparatus of claim 14 , wherein the first estimator model comprises a neural network model.
22. The apparatus of claim 14 , wherein the second estimator model comprises a neural network model.
23. The apparatus of claim 14 , wherein the one or more processors are further configured to cause the apparatus to determine an optimal tunecode for an impedance tuner based on the target wireless data transmission system configuration.
24. The apparatus of claim 14 , wherein the one or more operating characteristics comprise:
a real impedance of an element of the wireless data transmission system;
an imaginary impedance of the element of the wireless data transmission system;
a frequency of the wireless data transmission system; and
an antenna tuner state.
25. The apparatus of claim 24 , wherein:
the element is an antenna of the wireless data transmission system, and
the target wireless data transmission system configuration comprises an antenna tuner setting.
26. The apparatus of claim 25 , wherein the antenna tuner setting comprises at least one of an aperture tuner setting or an impedance tuner setting.
27. A non-transitory computer-readable medium comprising computer-executable instructions that, when executed by one or more processors of a processing system, cause the processing system to perform a method, the method comprising:
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;
determining, using a first estimator model, one or more estimated operating characteristics of the wireless data transmission system using one or more virtual wireless data transmission system configurations different from the target wireless data transmission system configuration;
determining, using a second estimator model, one or more estimated performance metrics of the wireless data transmission system based on the one or more estimated operating characteristics;
determining an actual performance metric based on the target wireless data transmission system configuration;
determining a best wireless data transmission system configuration of the target wireless data transmission system configuration and the one or more virtual wireless data transmission system configurations based on the actual performance metric and the one or more estimated performance metrics;
generating feedback data based on the determined best wireless data transmission system configuration; and
implementing the target wireless data transmission system configuration in the wireless data transmission system.
28. An apparatus, comprising:
means for receiving one or more operating characteristics of a wireless data transmission system of a device;
means for determining, using a wireless data transmission system configuration model, a target wireless data transmission system configuration based on the one or more operating characteristics;
means for determining, using a first estimator model, one or more estimated operating characteristics of the wireless data transmission system using one or more virtual wireless data transmission system configurations different from the target wireless data transmission system configuration;
means for determining, using a second estimator model, one or more estimated performance metrics of the wireless data transmission system based on the one or more estimated operating characteristics;
means for determining an actual performance metric based on the target wireless data transmission system configuration;
means for determining a best wireless data transmission system configuration of the target wireless data transmission system configuration and the one or more virtual wireless data transmission system configurations based on the actual performance metric and the one or more estimated performance metrics;
means for generating feedback data based on the determined best wireless data transmission system configuration; and
means for implementing the target wireless data transmission system configuration in the wireless data transmission system.