T-mobile Usa, Inc.

Suchit Satpathy

Florendo Atienza

Vijay Veggalam

Jeremy Babb

Kendall Bush

Muhammad Tawhidur Rahman

Kevin Lau

Jie Hui

Yinjun Zhu

Samson Kim-Sun Kwong

Nishant Patel

Kranthi Sontineni

Yunhan Jia

Robert Berrier

Yun Hong Lee

Yanbing Su

Jan Olav Opedal

Srikrishna Srinivasan

Mohamed Youssef Mohamed Madian

Peter Bucko

Venu Mudunuri

Andrew Rogers

Senthil Ravindranath

Brian Barnhart

Jonathan Sarbillon Ramirez

A network assessment system for generating subjective quality ratings for Internet protocol multimedia subsystem (IMS) data sessions in real-time. The system measures real-time telecommunications network data during an IMS data session, processes the data using a trained model, and receives a subjective quality rating usable to modify the performance of a node in instances where the node does not typically have an associated subjective quality rating or in instances where the node is not associated with a standardized subjective quality rating.

Machine learning model for assessing network performance

Solutions for early cellular offloading include: receiving, at a node of a wireless network, from a user equipment (UE), a first message (e.g., an A3, A5, B1, or B2 event report) containing information regarding a serving cell of a first wireless technology generation and information regarding a neighbor cell of the first wireless technology generation (e.g., reference signal receive power (RSRP), reference signal received quality (RSRQ), or signal to interference and noise ratio (SINR) measurement for fifth generation cellular technology (5G)); determining that a handover to the neighbor cell will not be performed; and based on at least the information regarding the serving cell and determining that the handover to the neighbor cell will not be performed, triggering an offload from the serving cell to a cell of a second wireless technology generation (e.g., fourth generation cellular technology (4G)).

Efficient radio access technology offloading without dedicated measurement report

This disclosure describes techniques for optimizing operational performance of femtocell devices deployed within a telecommunications network. More particularly, a femtocell Optimization (FCO) system is described that monitors a performance state of femtocell devices within a telecommunications network, detects a change in performance state of a particular femtocell device, and preemptively deploys a first set of service resolution data to detect a service issue. In response to detecting a service issue, a second set of service resolution data is deployed to preemptively resolve the service issue.

Femtocell provisioning and service issue optimization

Processes and systems for automatically configuring small cells, microcells, picocells, and femtocells for deployment in a cellular network are described herein. The system uses an orchestrator in an Orchestration Platform to direct the generation of the configuration for network assets to be deployed. The Orchestration Platform interacts with components to generate the data and parameters necessary for the configuration. The Orchestration Platform directs system components to generate the configuration, validate the configuration, execute the configuration, and download the configuration. The processes and systems include a database to maintain the state of a system instance during the configuration process, allowing an orchestrator to start, suspend, abort, or restart its workflow process at any time without the loss of any work.

Network deployment orchestration

This disclosure describes techniques for optimizing operational performance of femtocell devices deployed within a telecommunications network. More particularly, a femtocell Optimization (FCO) system is described that detects service issues that affect femtocell device(s). In some instances, the FCO system may automatically deploy a service resolution for known service issues or alerts network representatives for unresolved service issues. Moreover, the FCO system may be further configured to optimize resource utilization of a femtocell device network by preemptively correcting femtocell provisioning issues, based on patterns of historic service issues. The FCO system may further optimize resource usage of femtocell devices by selectively intercepting and terminating connectivity requests (i.e. rejecting issuance of Internet Protocol (IP) addresses) from client devices, or client device types, that have not historically overwhelmed femtocell network resources. The FCO system may further generate a femtocell analysis model to preemptively deploy service resolutions that protect against probable degradations in performance.

Described herein are systems and methods for determining IP backhaul issues in a femtocell network. A fault analysis tool retrieves log files from various components within the femtocell network and, using programmed logic, parses the log files and determines whether it is likely that an issue exists with the IP backhaul that prevents the femtocell network from communicating with the network of a wireless carrier. Additional automated tools are able to identify issues within the femtocell network and send instructions to one or more components in the femtocell network to correct the issues.

Backhaul fault analysis for femto network

A telecommunication carrier may use data collected from user devices to pinpoint sources of data interruptions in the communication connection between a carrier network and the user devices. The telecommunication carrier may receive multiple reports of detected data interruptions at one or more computing devices of a carrier network. The detected data interruptions include a data interruption to a user device that is detected by an agent application on the user device that monitors of at least one of an audio pathway or a video pathway of the user device. The telecommunication carrier may aggregate data interruption information from the multiple reports of the detected data interruptions, and analyze the data interruption information to pinpoint one or more sources of a detected data interruption.

Pathway-based data interruption detection

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Hackettstown, NJ, United States of America

Suchit Satpathy