Bastille Networks, Inc.

Apple Inc.

Sebastian Balint Seeber

Robert Baxley

Shahram Talakoub

Christian Sepulveda

Sandor Szilvasi

Luke Harwood

Roy S Thompson, Iii

Venkateswara Rao Manepalli

Sanjeevi Balasubramanian

Shiva Krishna Narra

Dhruv Khati

Anjaneyulu Maganti

Sudhir K Baghel

Matthew N Ettus

Ian Buckley

Jeremiah Hsu

Logan Michael Lamb

A communications system may include a satellite and user equipment (UE) devices. When the UE devices have uplink (UL) packets to transmit, each UE device may randomly select a time slot within a finite time window associated with a time reference of the satellite. The UE device may identify a path length between itself and the satellite and may generate a timing advance based on the path length, the time reference, and the time slot. The satellite may begin to receive the UL packets within the time window and may search received signals over the time window to identify the UL packets. The satellite may recover data payloads from the identified UL packets and may pass the recovered data payloads up a protocol stack. By limiting the search to the time window, the satellite may correctly distinguish the UL packets while using a minimal amount of processing resources.

Multiple user access channel

Methods, devices, and apparatus to adapt operating parameters for satellite signal reception and transmission by a wireless device to mitigate effects of fading due to specular reflections are described herein. The wireless device measures received signal power levels and compares characteristics of the measurements over an observation duration to at least one fading criteria to determine whether to operate in a normal or adaptive mode. While operating in the adaptive mode, the wireless device alternates between high performance mode time periods and low performance mode time periods. The wireless device indicates to a ground station associated with the satellite in which operating mode the wireless device is operating via an uplink data message transmitted during a data cycle at the start of a high or low performance mode time period. The ground station schedules data transmissions accordingly during subsequent data cycles of the high or low performance mode time periods.

Adaptive operation to mitigate specular reflections

A communications system may include user equipment (UE) devices, communications satellites, gateways, and a terrestrial network. The UE devices may receive broadcast signals from the constellation. The UE devices may transmit registration requests to the gateways via the satellites in response to the broadcast signals. The registration requests may include information identifying the geographic locations of the UE devices and may include two-line element (TLE) identifiers. A scheduler on the terrestrial network may receive forward link traffic requests for the UE devices, each with a corresponding priority. The scheduler may also receive satellite information that includes thermal constraints, position information, and power information associated with the satellites. The scheduler may generate forward link traffic grants for the UE devices based on the forward link traffic requests, the thermal constraints, the TLE versions, the geographic locations, and the priorities.

Communication scheduler

Systems and methods can support identifying pairings and channel parameters in short-range wireless communications such as Bluetooth low energy interfaces. Radio frequency sensors may be positioned within an electromagnetic environment where a master wireless device and a slave wireless device share short-range wireless communications. Signals transmitted between the master wireless device and the slave wireless device can be received by the radio frequency sensors. Inter-arrival times for packets within the received signals may be identified. Statistics of the inter-arrival times can be analyzed to identify connection intervals between the master wireless device and the slave wireless device, as well as back-to-back intervals exchanged within the connection intervals. Packet header contents may be used to reconcile the estimated timing parameters and time slots. Pairings between the master wireless device and the slave wireless device may be identified and tracked along with communication channel parameters.

Passive determination of pairing and channel parameters for short-range wireless communications

Systems and methods can support identifying pairings and channel parameters in short-range wireless communications such as bluetooth low energy interfaces. Radio frequency sensors may be positioned within an electromagnetic environment where a master wireless device and a slave wireless device share short-range wireless communications. Signals transmitted between the master wireless device and the slave wireless device can be received by the radio frequency sensors. Inter-arrival times for packets within the received signals may be identified. Statistics of the inter-arrival times can be analyzed to identify connection intervals between the master wireless device and the slave wireless device as well as back-to-back interval exchanged within the connection intervals. Packet header contents may be used to reconcile the estimated timing parameters and time slots. Pairings between the master wireless device and the slave wireless device may be identified and tracked along with communication channel parameters.

Systems and methods can support identifying threats in short-range wireless communications, such as Bluetooth, using one or more radio frequency sensors to receive signals transmitted between a master device and a slave device. Packets can be identified within the received signals and designated as originating from the master device or from the slave device. The wireless interface can be identified as synchronous or asynchronous. Lengths of data may be identified for data payloads within the packets. Total aggregate data lengths may be calculated for both the master and the slave transmissions. Time slot utilization statistics can be computed. A connection type category may be determined using these wireless connection features. The connection type may be for peripherals, streaming audio, two-way headsets, object exchange, data tethering, and so forth. Potential security threats associated with the wireless interface may be identified from the determined connection type and from the wireless connection features.

Traffic and threat classification for short-range wireless channels

Systems and methods can support improved position locating of wireless devices. A suite of machine learning models may be established. Radio frequency sensors may be positioned within an electromagnetic environment where user equipment devices are serviced by a base station. The radio frequency sensors can receive wireless signals associated with communications between the user equipment devices and the base station. The suite of machine learning models may be trained using wireless signals received from user equipment devices in known positions. The trained suite of machine learning models can be applied to wireless signals received from user equipment devices in unknown positions. The trained suite of machine learning models may be used to estimate the unknown positions. The estimated positions may be refined using additional information from the user equipment devices.

Localization calibration and refinement in high-speed mobile wireless systems

Systems and methods can support determining a physical position of wireless devices. Radio frequency sensors may be positioned within an electromagnetic environment where user equipment devices are serviced by a base station. The radio frequency sensors can receive wireless downlink signals transmitted from the base station to the user equipment devices. Network identifiers may be extracted from the received wireless downlink signals. User equipment devices may be associated with the extracted network identifiers. Radio channel allocations may be determined for the extracted network identifiers. The radio frequency sensors can receive wireless uplink signals transmitted from the user equipment devices to the base station. Signal strength indicators from the received wireless uplink signals can be associated with the extracted network identifiers. Physical positions of the user equipment devices can be determined by analyzing the associated signal strength indicators.

Localization of mobile high-speed wireless user equipment from downlink channels

Systems and methods can support identifying wireless devices from radio frequency sensors positioned within an electromagnetic environment where one or more user equipment devices are serviced by a base station. The radio frequency sensors can receive wireless uplink signals transmitted from the user equipment devices to the base station. Data samples can be generated from the received signals. Frequency domain samples can be computed from the data samples. The data samples can be partitioned in time and frequency to generate spectrum tiles. The spectrum tiles can be statistically aggregated in a frequency domain to reduce the quantity of data samples. A clustering algorithm may be applied to the statistically aggregated spectrum tiles. Unique instances of the user equipment devices may be identified from the clustered spectrum tiles to enumerate the instances of the user equipment devices.

User equipment identification from mobile high-speed wireless uplink channels

Systems and methods can support determining the physical position of a wireless device. Radio frequency sensors may be positioned within an electromagnetic environment where user equipment devices are serviced by a base station. The radio frequency sensors can receive wireless uplink signals transmitted from the user equipment devices to the base station. Data samples can be generated from the received signals. The data samples may be partitioned in time and frequency to generate spectrum tiles. The spectrum tiles may be statistically aggregated to reduce the quantity of data samples. A clustering algorithm may be applied to the statistically aggregated spectrum tiles to determine clusters of spectrum tiles. Signal parameters associated with respective clusters of spectrum tiles may be computed. Physical locations associated with user equipment devices can be estimated from the signal parameters associated with the respective clusters of spectrum tiles.

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San Francisco, CA, United States of America

Sebastian Balint Seeber