T-mobile Usa, Inc.

T-moblle Usa, Inc.

Otto Fonseca Escudero

Paul Bongaarts

Andrew Gapin

Khrum Kashan Jat

Marie Grace Jacinto

Gary Dousson

Salvador Mendoza

Egil Gronstad

Mallika Deshpande

Grant Morgan Castle

Spoorthy Kondapally

Kirti Krishnan

Ahmed Mahdaoui

Dinesh Kumar

Jatinder Singh Sandhu

Elisa Hwei-Shan Yuen

A telecommunication system can include routing devices, a bearer-management device, and a policy-management device. The bearer-management device can receive a request from a terminal to create a specialized bearer (SB) for a non-audio, non-video media type. The bearer-management device can determine that the request is associated with an authorized user, and then send a setup message comprising a Quality of Service (QoS) indicator to the policy-management device. The policy-management device can create the SB permitting data exchange between the terminal and a routing device. The SB can have QoS characteristics associated with the QoS indicator. In some examples, the terminal can receive a network address, determine an associated network port, and send a SIP INVITE message indicating the non-audio, non-video media type. The terminal can then exchange data on the network port with a peer network terminal.

Latency-sensitive network-traffic quality of service

Systems and methods for computing a standardized composite gain metric value for each solution that has been previously deployed to fix degradation issues at cell sites or other wireless nodes is disclosed. The method selects a set of Key Performance Indicators (KPIs), each of which is highly correlated to customer experience. For example, the method selects the following KPIs: traffic, numbers of users, Physical Resource Block (PRB) utilization, Channel Quality Indicator (CQI), throughput, and so on. The method then assigns a weight to each KPI, such that the weight reflects each KPI's relative importance and ensures that the KPIs are not double counted. For each solution deployed at a cell site, the method computes values of the following composite gain metrics: weighted gain and offload index. The method then can rank the solutions based on the computed composite gain metric values so that an optimum solution can be selected.

Optimum network performance improvement solutions selection systems and methods

A telecommunication system can include a control device and a network gateway. The control device can determine cache-update instructions by operating trained computational models. The network gateway can receive cache-update instructions from the control device and transmit corresponding items of content to network terminals. In some examples, the network terminals can receive the items of content and store them in respective content caches at the at the network terminals. In some examples, the control device can determine respective content scores for at least two items of content; cluster the at least two items of content based at least in part on usage data associated with the network terminals to determine respective cluster labels for the at least two items of content; and determine the cache-update instructions based at least in part on the content scores, the cluster labels, and network-resource information.

Telecommunications-network content caching

Systems and methods are described for monitoring performance and allocating resources to improve the performance of a wireless telecommunications network. A wireless telecommunications network may be comprised of base stations and other infrastructure equipment, which may be sourced from various suppliers. Users may generate traffic on the wireless network, and performance metrics relating to the user experience may be collected from individual base stations. The set of available metrics for a particular base station may vary according to the supplier. A machine learning model is thus trained using metrics from multiple base stations, and used to estimate values for metrics that a particular base station does not provide. The metrics are then further characterized according to the service classes of the users, and resources for improving the performance of base stations are allocated according to the reported and estimated metrics for various service classes.

Managing LTE network capacity

Systems and methods for improved efficiency in content streaming and downloading. The system enables a first list including a plurality of user equipment (UE) in communication with a wireless base station (WBS) to be identified based on the likelihood that each UE will download a piece of content. The process starts in response to a UE requesting the content from the WBS or some other triggering event. The system can use the content and subscriber history from the plurality of UEs along with machine learning, or some other algorithm, to identify likely candidates. The system can calculate a similarity score, or similar, comparing the requested content to the content history for each of the plurality of UEs. The system can add each UE with a sufficiently high similarity score to a second list. The content can be broadcast to all UEs on the second list in a single broadcast transmission.

Wireless delivery of broadcast data

Systems and methods for computing a standardized composite gain metric value (e.g., weighted gain or offload index) for each solution that has been previously deployed to fix degradation issues at cell sites or other wireless nodes is disclosed. The method selects a set of Key Performance Indicators (KPIs), each of which is highly correlated to customer experience. For example, the method selects the following KPIs: traffic, number of users, Physical Resource Block (PRB) utilization, Channel Quality Indicator (CQI), throughput, and so on. The method then assigns a weight to each KPI, such that the weight reflects each KPI's relative importance and ensures that the KPIs are not double counted. For each solution deployed at a cell site, the method computes values of the following composite gain metrics: weighted gain and offload index. The method then can rank the solutions based on the computed composite gain metric values so that an optimum solution can be selected.

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Snoqualmie, WA, United States of America

Otto Fonseca Escudero