System and method for optimized thermal management of a WWAN modem
A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to execute intelligent thermal management of a WWAN modem. In at least one embodiment, the temperature conditions associated with the operation of the WWAN modem and the current communication conditions of the WWAN modem are detected. The detected temperature conditions and current communication conditions are provided to an input of a trained thermal AI/ML model, which generates a set of new communication parameters. In at least one embodiment, the WWAN modem is set to operate using one or more of the new communication parameters.
1. A computer-implemented method comprising:
detecting temperature conditions associated with operation of a Wireless Wide Area Network (WWAN) modem in an information handling system;
detecting current communication conditions of the WWAN modem;
providing the detected temperature conditions and current communication conditions to an input of a trained thermal artificial intelligence/machine learning (AI/ML) model;
generating new communication parameters using the trained thermal AI/ML model at an output of the trained thermal AI/ML model, wherein the new communication parameters are generated by the trained thermal AI/ML model using the detected temperature conditions and current communication conditions provided to the input of the trained thermal AI/ML model; and
setting the WWAN modem to operate using one or more of the new communication parameters.
2. The computer-implemented method of claim 1 , wherein the detected temperature conditions associated with operation of the WWAN modem include one or more of:
an ambient temperature of an operating environment proximate the WWAN modem;
a change in the ambient temperature of the operating environment proximate the WWAN modem over time;
device temperatures of hardware components of the WWAN modem; and
a change in device temperatures of the hardware components of the WWAN modem over time.
3. The computer-implemented method of claim 1 , wherein the detected current communication conditions of the WWAN modem include one or more of:
a communication mode of the WWAN modem;
a modulation coding scheme used by the WWAN modem;
a duty cycle in use for communications transmitted by the WWAN modem;
a channel in use by the WWAN modem;
a transmit power level in use for communications transmitted by the WWAN modem;
a data throughput of current communications transmitted by the WWAN modem;
a signal quality of a serving cell currently used by the WWAN modem;
a distance between the WWAN modem and the serving cell currently used by the WWAN modem;
a signal quality of a neighboring cell that may be used by the WWAN modem;
a mobility mode of the WWAN modem;
a status of the WWAN modem; and
a name of a network to which the WWAN modem is connected.
4. The computer-implemented method of claim 3 , wherein the new communication parameters provided at the output of the trained thermal AI/ML model include one or more of:
a recommended communication mode for use by the WWAN modem;
a recommended duty cycle for use in communications by the WWAN modem;
a recommended modulation coding scheme for use in communications by the WWAN modem;
a recommended transmit power level for use in communications by the WWAN modem;
a recommended shutdown of the radio functions of the WWAN modem; and
a carrier aggregation technique for use in communications by the WWAN modem.
5. The computer-implemented method of claim 1 , further comprising:
detecting conditions associated with an operating scenario of the information handling system; and
providing the detected conditions associated with the operating scenario to the input of the trained thermal AI/ML model; and
using, by the trained thermal AI/ML model, the detected conditions associated with the operating scenario to obtain the new communication parameters from an output of the trained thermal AI/ML model.
6. The computer-implemented method of claim 5 , wherein the detected conditions associated with the operating scenario of the information handling system include one or more of:
applications currently running on the information handling system;
software drivers used by the information handling system;
operating system used by the information handling system;
speed of a cooling fan of the information handling system;
speed of one or more central processing units used by the information handling system;
speed of one or more graphics processing units used by the information handling system;
an ambient temperature of the information handling system; and
a change in the ambient temperature of the information handling system over time.
7. The computer-implemented method of claim 5 , further comprising:
obtaining new operating scenario conditions for use by the information handling system from the output of the trained thermal AI/ML model, wherein the new operating scenario conditions include one or more of:
a recommended speed for a cooling fan of the information handling system;
a recommended speed for operation of one or more central processing units of the information handling system; and
a recommended speed for operation of one or more graphics processing units of the information handling system.
8. The computer-implemented method of claim 1 , further comprising:
providing fixed parameters associated with the WWAN modem and information handling system to the input of the trained thermal AI/ML model, wherein the fixed parameters include one or more of
an identification of a model of the WWAN modem,
identification of hardware components of the WWAN modem,
identification of a model of the information handling system; and
generating the new communication parameters using the trained thermal AI/ML model at an output of the trained thermal AI/ML model using one or more of the fixed parameters.
9. A wireless wide area network (WWAN) modem comprising:
a processor; and
a non-transitory, computer-readable storage medium embodying computer program code including instructions that are executable by the processor and configured for:
detecting temperature conditions associated with operation of the WWAN modem in an information handling system;
detecting current communication conditions of the WWAN modem;
providing the detecting temperature conditions and current communication conditions to an input of a trained thermal artificial intelligence/machine learning (AI/ML) model;
generating new communication parameters using the trained thermal AI/ML model at an output of the trained thermal AI/ML model, wherein the new communication parameters are generated by the trained thermal AI/ML model using the detected temperature conditions provided to the input of the trained thermal AI/ML model; and
setting the WWAN modem to operate using one or more of the new communication parameters.
10. The WWAN modem of claim 9 , wherein the detected temperature conditions associated with operation of the WWAN modem include one or more of:
an ambient temperature of an operating environment proximate the WWAN modem;
a change in the ambient temperature of the operating environment proximate the WWAN modem over time;
device temperatures of hardware components of the WWAN modem; and
a change in device temperatures of the hardware components of the WWAN modem over time.
11. The WWAN modem of claim 9 , wherein the detected current communication conditions of the WWAN modem include one or more of:
a communication mode of the WWAN modem;
a modulation coding scheme used by the WWAN modem;
a duty cycle in use for communications transmitted by the WWAN modem;
a channel in use by the WWAN modem;
a transmit power level in use for communications transmitted by the WWAN modem;
a data throughput of current communications transmitted by the WWAN modem;
a signal quality of a serving cell currently used by the WWAN modem;
a distance between the WWAN modem and the serving cell currently used by the WWAN modem;
a signal quality of a neighboring cell that may be used by the WWAN modem;
a mobility mode of the WWAN modem;
a status of the WWAN modem;
radio shutdown of the WWAN modem; and
a name of a network to which the WWAN modem is connected.
12. The WWAN modem of claim 11 , wherein the new communication parameters provided at the output of the trained thermal AI/ML model include one or more of:
a recommended communication mode for use by the WWAN modem;
a recommended duty cycle for use in communications by the WWAN modem;
a recommended modulation coding scheme for use in communications by the WWAN modem;
a recommended transmit power level for use in communications by the WWAN modem;
a recommended shutdown of the radio of the WWAN modem;
a recommended radio shutdown of the WWAN modem; and
a carrier aggregation technique for use in communications by the WWAN modem.
13. The WWAN modem of claim 9 , wherein the instructions are further configured for:
detecting conditions associated with an operating scenario of the information handling system; and
providing the detected conditions associated with the operating scenario to the input of the trained thermal AI/ML model; and
using, by the trained thermal AI/ML model, the detected conditions associated with the operating scenario to obtain the new communication parameters from an output of the trained thermal AI/ML model.
14. The WWAN modem of claim 13 , wherein the detected conditions associated with the operating scenario of the information handling system include one or more of:
applications currently running on the information handling system;
software drivers used by the information handling system;
operating system used by the information handling system;
speed of a cooling fan of the information handling system;
speed of one or more central processing units used by the information handling system;
speed of one or more graphics processing units used by the information handling system;
an ambient temperature of the information handling system; and
a change in the ambient temperature of the information handling system over time.
15. The WWAN modem of claim 13 , wherein the instructions are further configured for:
obtaining new operating scenario conditions for use by the information handling system from the output of the trained thermal AI/ML model, wherein the new operating scenario conditions include one or more of:
a recommended speed for a cooling fan of the information handling system;
a recommended speed for operation of one or more central processing units of the information handling system; and
a recommended speed for operation of one or more graphics processing units of the information handling system.
16. The WWAN modem of claim 9 , wherein the instructions are further configured for:
providing fixed parameters associated with the WWAN modem and information handling system to the input of the trained thermal AI/ML model, wherein the fixed parameters include one or more of
an identification of a model of the WWAN modem,
identification of hardware components of the WWAN modem,
identification of a model of the information handling system; and
generating the new communication parameters using the trained thermal AI/ML model at an output of the trained thermal AI/ML model using one or more of the fixed parameters.
17. A non-transitory, computer-readable medium embodying computer program code, the computer program code comprising computer-executable instructions configured for:
detecting temperature conditions associated with operation of a Wireless Wide Area Network (WWAN) modem in an information handling system;
detecting current communication conditions of the WWAN modem;
providing the detected temperature conditions and current communication conditions to an input of a trained thermal artificial intelligence/machine learning (AI/ML) model;
generating new communication parameters using the trained thermal AI/ML model at an output of the trained thermal AI/ML model, wherein the new communication parameters are generated by the trained thermal AI/ML model using the detected temperature conditions and current communication conditions provided to the input of the trained thermal AI/ML model; and
setting the WWAN modem to operate using one or more of the new communication parameters.
18. The non-transitory, computer-readable storage medium of claim 17 , wherein the detected temperature conditions associated with operation of the WWAN modem include one or more of:
an ambient temperature of an operating environment proximate the WWAN modem;
a change in the ambient temperature of the operating environment proximate the WWAN modem over time;
device temperatures of hardware components of the WWAN modem; and
a change in device temperatures of the hardware components of the WWAN modem over time.
19. The non-transitory, computer-readable storage medium of claim 17 , wherein the detected current communication conditions of the WWAN modem include one or more of:
a communication mode of the WWAN modem;
a modulation coding scheme used by the WWAN modem;
a duty cycle in use for communications transmitted by the WWAN modem;
a channel in use by the WWAN modem;
a transmit power level in use for communications transmitted by the WWAN modem;
a data throughput of current communications transmitted by the WWAN modem;
a signal quality of a serving cell currently used by the WWAN modem;
a distance between the WWAN modem and the serving cell currently used by the WWAN modem; and
a signal quality of a neighboring cell that may be used by the WWAN modem;
a mobility mode of the WWAN modem;
a status of the WWAN modem;
a radio shutdown of the WWAN modem; and
a name of a network to which the WWAN modem is connected.
20. The non-transitory, computer-readable storage medium of claim 19 , wherein the new communication parameters provided at the output of the trained thermal AI/ML model include one or more of:
a recommended communication mode for use by the WWAN modem;
a recommended duty cycle for use in communications by the WWAN modem;
a recommended modulation coding scheme for use in communications by the WWAN modem;
a recommended transmit power level for use in communications by the WWAN modem;
a recommended shutdown of the radio of the WWAN modem; and
a carrier aggregation technique for use in communications by the WWAN modem.