Abstract:
Determining a location of a user device comprises a wireless system supported by wireless access points receiving signals from a user device. The wireless system estimates a location of the user device based on a coarse calculation based on an angle of arrival of the received signal and determines if the user device is in an area under an access point. The wireless system identifies received signal strength indicator values for the user device and uses the values and the calculated location of the user device to improve calibration of a received signal strength location model. If the system determines that the user is not in the area under the access point, the wireless system combines the coarse calculation location, a received signal strength determined location, and a previous received signal strength determined location, and estimates a location based on the combined calculations.
Abstract:
Determining a location of a user device comprises a wireless computing system supported by an access point. The wireless computing system receives a signal from the user device. The system estimates a location of the user device based on RSSI and calculates a boundary around the estimated location. The wireless computing system selects a plurality of sections inside of the boundary and performs a coarse calculation of a location of the user device based on an angle of arrival of the received signal. The system determines sections of the plurality of sections that have results from the coarse calculation that are more likely to be a location of the user device. The system performs a fine calculation of the location based on the angle of arrival of the received signal within each of the sections. The system identifies a particular section as the location of the user device.
Abstract:
Techniques are presented herein to provide human mobility pattern based modeling and tracking of a group of network enabled user devices associated with the same person. An association is made, at a tracking device, between a plurality of user devices and a user. Location information for each of the plurality of user devices is derived through network activity of the plurality of user devices. Locations for the plurality of user devices are derived from the location information. One or more predetermined user mobility pattern rules are applied to the plurality of user devices. User anomalies are detected when the tracked locations indicate that one or more of the plurality of user devices has violated one or more the predetermined user mobility rules.
Abstract:
In an example embodiment, a wireless device is operable to advertise a policy on the inclusion of the wireless device in a radio frequency map. For example, the wireless device may transmit a signal comprising a field in an extended capabilities information that indicates whether mapping of the wireless device is permissible. As another example, the wireless device may perform certain actions, such as changing media access control address, changing transmit power, and/or vary response times to prevent accurate mapping of the location of the wireless device.
Abstract:
Heatmap data, such as Angle-of-Arrival heatmap data, is generated and stored for a plurality of antennas of wireless communication device. A centroid of the plurality of antennas is determined. A heatmap is computed for the centroid for a measured parameter across a plurality of bins at coordinates within a region of interest. Heatmap data for the centroid is stored. For a given one of the plurality of antennas, a difference is computed between a heatmap for the given antenna and the heatmap for the centroid. The difference data representing the difference is stored for the given antenna.
Abstract:
In an example embodiment, the orientation of a wireless device, such as an access point (AP) can be determined based on the location of neighboring wireless devices and the observed angle of arrival of signals from the wireless device at the neighboring wireless devices. For example, the angle of orientation can be determined by comparing an observed angle of arrival with the known actual angle between wireless devices. If a plurality of wireless devices measure the signal, the mean or median of the difference between observed angle of arrival of a signal from the wireless device with the actual angle for the plurality of wireless devices may be employed to determine the angular orientation.
Abstract:
In an example embodiment, a neighbor radio/access point (AP) list is obtained. The neighbor AP list is optimized for a client that is associated with a current access point. The list may be optimized based on any one or combination of techniques, including but not limited to roaming patterns of previous clients that were associated with the current access point, radio frequency metrics, bandwidth requirements for the client, and/or any other suitable criteria. In particular embodiments, requests from the client to associate with an access point that is not on the optimized neighbor AP list may be denied.
Abstract:
Techniques are presented to optimize location classification accuracy for wireless devices. A controller in communication with one or more wireless access points receives measurement data associated with signals received at one or more wireless access points from a plurality of wireless clients. The controller classifies each of the measurement data associated with a corresponding client as indicative a location inside of a particular region or outside of the particular region. The controller determines information of an actual location for each of the clients and classifies the information of the actual location as indicating a location inside of the particular region or outside of the particular region. For a given client whose classification of the information of the actual location does not match the classification of the corresponding measurement data, the controller modifies the information of the actual location of the given client.
Abstract:
Techniques are presented herein to provide human mobility pattern based modeling and tracking of a group of network enabled user devices associated with the same person. An association is made, at a tracking device, between a plurality of user devices and a user. Location information for each of the plurality of user devices is derived through network activity of the plurality of user devices. Locations for the plurality of user devices are derived from the location information. One or more predetermined user mobility pattern rules are applied to the plurality of user devices. User anomalies are detected when the tracked locations indicate that one or more of the plurality of user devices has violated one or more the predetermined user mobility rules.
Abstract:
In one embodiment, an apparatus includes a processor for processing a plurality of radio frequency chains at a wireless device in a block based modulation environment, recording subcarrier phases and differences between the subcarrier phases, and using the subcarrier phase differences to construct a feature vector for use in angle of arrival calculated positioning of a mobile device, and memory for storing the subcarrier phases and the feature vector.