Classifying access point beacon communications using machine learning
AssigneeSilicon Laboratories Inc.
InventorKrishna Chaitanya Suryavenkata Emani
Life of this patent
Estimating the term…
Abstract
In one aspect, a method comprises: receiving, in a machine learning (ML) classifier, power plot information associated with communication between a wireless device and an access point; analyzing, in the ML classifier, the power plot information comprising determining whether an anomalous condition exists with respect to beacon communication between the wireless device and the access point; and in response to determining the anomalous condition, classifying a type of an anomalous beacon communication.
Claims17
A computer readable medium comprising instructions that, when executed, cause a system to perform a method comprising:
- receiving, in a machine learning (ML) classifier, power plot information associated with communication between a wireless device and an access point;
- analyzing, in the ML classifier, the power plot information comprising determining whether an anomalous condition exists with respect to beacon communication between the wireless device and the access point;
- and
- in response to determining the anomalous condition, classifying a type of the anomalous beacon communication comprising identifying the type of the anomalous beacon communication as one or more of a fat beacon or a drifted beacon and determining a configuration for the wireless device based at least in part on the type of the anomalous beacon communication.
A method comprising:
- configuring a wireless device to operate in a standby mode;
- in the standby mode, receiving a plurality of beacons from an access point in a wireless network with the wireless device;
- while the wireless device is in the standby mode, measuring a power consumption of the wireless device during a first duration;
- providing the measured power consumption of the wireless device to a power analyzer, comprising sending the measured power consumption to a controller of the wireless device to cause generation of power plot information of the power consumption and communication of the power plot information to a machine learning (ML) classifier, the controller to generate the power plot information;
- and
- classifying a type of beacon communication in the ML classifier, the wireless device to execute the ML classifier.
A method comprising:
- receiving, in a machine learning (ML) classifier, power plot information associated with a power consumption level of a wireless device during beacon communication between the wireless device and an access point, the power plot information comprising power consumption information of the wireless device for a plurality of components of a standby mode in which the beacon communication comprises a plurality of beacons sent by the access point;
- analyzing, in the ML classifier, the power plot information comprising determining whether an anomalous condition exists with respect to the beacon communication;
- and
- in response to determining the anomalous condition, classifying a type of the anomalous condition.
Dependencies are inferred from the claim text.