T-Mobile USA, Inc.

T-Mobile Innovations LLC

Emile Minh Tran

Antoine T Tran

Julio Costa

Nan Xiao

Joshua Van De Walle

Chong Kiong

Muhammad Khadim

Tony Fung

Jie Hui

Michael J Mitchell

Vikas Ranjan

Dennis Jarret Guill, Jr

Robert Berrier

Julio C Costa

Daniel Howard Wilson

Muhammad Shakil

Syed Umair Ahmed

Danny Goswami

Murali Krishnan Govindan

Benjamin Yuen

Jeremy M Tran

An automated dependency graph builder system builds a dependency graph for managing a network. The automated dependency graph builder system and network management can utilize networks (e.g., telecommunication networks) and/or systems for providing, and/or being communicatively connected with, the telecommunication networks. The automated dependency graph builder system and network management can execute a script orchestration engine to sort database scripts, and execute database scripts according to script execution orchestrator information.

Automated dependency graph builder system and network management

A method for determining a reliability of a wireless device to estimate its location under a simulated environmental condition includes simulating an environmental condition inside a test chamber by controlling a physical parameter. The test chamber contains the wireless user device configured to estimate a location of the wireless user device based on reference signals received from a signal source. The method includes communicating a pattern of reference signals having varying signal propagation characteristics in the test chamber. The method includes receiving an indication of an estimated location calculated by the wireless user device based on the pattern of reference signals. The reliability of the wireless device to estimate its location under the simulated environmental condition is determined based on a comparison of the estimated location with the simulated location.

Location simulation for wireless devices

Techniques are described herein for providing hardware configuration updates relating to equipment nodes in a network using change messages. In embodiments, the techniques may comprise receiving a status update comprising status information for one or more equipment nodes, determining, based on the status information, one or more changes in status of the one or more equipment nodes since a prior status update, and generating a change message that includes the one or more changes. The techniques may further involve providing the change message to at least one second computing device, wherein the one or more changes is used to update aggregate data maintained by the second computing device.

Techniques for hardware configuration reporting using change messages

Techniques for calculating a location of a position consumer device is disclosed. In one example, a network server may create a fingerprint map from reference data points. Each of the reference data points may include a recorded geo-location of a position source device and signal measurements taken at that recorded geo-location. By initially estimating an initial position of the position consumer device, the network server may apply one or more threshold values to filter reference data points—candidates for interpolation. The network server may then perform an interpolation on one or more pairs of reference data points to find a pair of reference data points that is collinear with the estimated position of the position consumer device. The location of the position consumer device may then be calculated based upon geo-locations of position source devices that are associated with collinear reference data points.

Device position accuracy with network-based crowdsourcing

In some examples, a terminal can establish wireless communication with a base station. The terminal can determine a challenge, transmit the challenge, receive a response, and determine that the response is valid. The terminal can, in response, establish a secure network tunnel to a network node. In some examples, a terminal can determine a first communication parameter associated with communication with the base station. The terminal can receive data indicating a second communication parameter via a secure network tunnel. The terminal can determine that the communication parameters do not match, and, in response, provide an indication that an attack is under way against the network terminal. Some example terminals transmit a challenge, determine a response status associated with the challenge, and determine that an attack is under way based on the response status.

Wireless-network attack detection

A method for a base station in communication with a user device through a wireless communications network is described. The method includes communicating with a user device on a current frequency through a wireless communications network. The method may also include determining, based at least in part on a model, a probability that a higher capacity may be acquired by the user device on a frequency other than the current frequency; predicting a first recommended frequency for the user device that is likely to have a higher capacity than the current frequency; instructing the user device to scan the first recommended frequency; receiving an indication from the user device that the first recommended frequency has a higher capacity than the current frequency; and communicating with the user device on the first recommended frequency.

Predictive model for high-capacity frequencies in mobile broadband

A base station and computing resources to be used by a user equipment (UE) within a network can be selected based on information, such as an identification of base station(s) that may be used by the UE, and the location and performance of the base station(s) and the available computing resources. In some examples, when a mobility controller determines to switch the base station for a UE, the computing resources used to perform application processing can also be switched. For instance, when the current base station is switched, the computing resources used to perform application processing for the UE may be moved to computing resources that are closer to the different base station. In other examples, the mobility controller may determine to delay switching the UE to the different base station if the performance of the mobile application would be better using the current base station and current computing resources.

Mobility management for mobile device edge computing

Solutions for accelerating cell search and selection by a user equipment (UE) include: detecting, by the UE, a network exit; determining, by the UE, a network reentry condition; based on at least mobility data for the UE and a network connectivity context history, determining, by the UE, using a machine learning (ML) component, a set of priority reentry cells; attempting network reentry with the set of priority reentry cells; and based on at least failing network reentry with the set of priority reentry cells, attempting network reentry with a cell search. In some examples, mobility data for the UE is also used for determining the set of priority reentry cells. By searching the set of priority reentry cells first , rather than starting with a blind search, the UE may save not only battery power, but also reconnect to the network more quickly, thereby improving the user experience.

Accelerated cell search and selection

Solutions for focused cellular network paging of a user equipment (UE) include: detecting, by a network, a network exit of the UE from a last known cell and an exit condition for the UE; determining, by the network, a network paging condition; based on at least the last known cell and the exit condition for the UE, determining, by the network, a set of priority paging cells; paging the UE with the set of priority paging cells; and based on at least failing to receive a response by paging the UE with the set of priority paging cells, paging the UE with a larger set of cells. In some examples, the network topology is also used for determining the set of priority paging cells. By starting with the set of priority paging cells, rather than wider global paging, fewer cells are used for paging, thereby saving network bandwidth.

Focused cellular network paging

This disclosure describes techniques for capturing radio frequency (RF) signal over the air, processing spectrum power data, and uploading data to a central data repository for analysis and reporting. Captured RF signals are filtered and amplified via a front-end module of a probe that includes a filter and a low noise amplifier (LNA). Output signals can be decoded into digital TV metadata and image captures via a TV tuner and spectrum power, and then analyzed via a software defined radio (SDR). Digital TV metadata and images, as well as SDR data, can be uploaded and collected at a server. The server processes collected spectrum data from SDR into spectrum reports. The server can also analyze collected digital TV metadata to identify with increased accuracy RF sources originating from transmitting TV facilities.

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Sammamish, WA, United States of America

Emile Minh Tran