Abstract: A performance management engine may be implemented to continuously detecting entity performance issues. The performance management engine may calculate one or more key performance indicators (KPIs) that measure performance of an entity. The performance management engine may further receive one or more additional sources of data regarding the entity via a data management platform that interfaces with multiple data sources. The performance management engine may aggregate the KPIs and the one or more additional sources of data into datasets according to one or more grouping parameters. The data in one or more datasets may be analyzed by the performance management engine to generate one or more comprehensive performance indicators. The comprehensive performance indicators are then provided for display on a user device. Each KPI or comprehensive performance indicator measures performance of a device, a component, a node, or a service of the entity.

Abstract: A communication analytics engine that executes in conjunction with a data collection platform may provide a unified and scalable solution for call data aggregation and processing. A data collection platform may establish a communication connection with a wireless carrier network. The data collection platform may collect call data of multiple user devices via the communication connection, in which the multiple user devices may use the wireless carrier network to initiate and receive calls to one or more additional devices. The data collection platform may convert the call data into a format that is readable by the communication analytics engine. The communication analytics engine may analyze the call data to generate analytic results that includes one or more key performance indicators (KPIs).

Abstract: An analytic application may automatically determine a root cause of an issue with a wireless carrier network and generate a solution for the root cause. Initially, a data management platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. Subsequently, the analytic application may receive an indication of an issue affecting one or more user devices that are using the wireless carrier network. The analytic application may analyze the performance data using a trained machine learning model to determine a root cause for the issue affecting the one or more user devices. The trained machine learning model may employ multiple types of machine learning algorithms to analyze the performance data. The analytic application may provide the root cause or the solution that resolves the root cause for presentation.

Abstract: Techniques are described herein for receiving, by node of a telecommunication service provider, a network data packet from one of an application client of a telecommunication device and an application server. The node may then retrieve application information from a header of the network data packet and apply the application information to adapt radio delivery. Alternatively or additionally, the node may then insert radio information into the header of the network data packet in place of the application information. After performing the inserting or the retrieving, the node may transmit the network data packet to the other of the application client and the application server.

Abstract: Techniques for determining a guardband for a frequency channel based at least in part on a roll-off of a filter or a type of a filter are described herein. The filter may be a filter of a base station and the frequency channel may be used for transmissions from the base station to a mobile device. Alternatively, the filter may be a filter of a mobile device and the frequency channel may be used for transmissions from the mobile device to the base station. Further, because different filters of different mobile devices may have different roll-offs or types of filters, different guardbands may be determined for different mobile devices communicating over a same frequency channel. Upon determining the guardband, a base station may select a subcarrier based at least in part on the determined guardband.

Abstract: Described herein are techniques for limiting transmission of plurality of messages from one or more self-organizing network (SON) tools to a network support node based at least in part on performance information and on either or both of priorities associated with the plurality of messages or priorities associated with the SON tool(s). The performance information is associated with performance of a network support node.

Abstract: Systems and methods for providing high power channel state notification, management, and optimization are provided. In some embodiments, data transmissions from mobile devices to remote servers are managed. For example, the operating system, lower level apparatus, or software bundle, sequentially align, or otherwise coordinate the messages to be transmitted during each high power channel state. In addition, the impact to the application and user experience can be utilized in managing the transmissions. In some cases, various embodiments provide the application with the knowledge (e.g., the optimal moment, transmission schedule, etc.) for the transmission of its data. In addition, some embodiments allow the application to piggy back a data transmission that might otherwise be delayed on already open high speed channel to increase the devices performance data transfer.

Abstract: A set of key performance indicators (KPIs) is calculated for a first set of user devices based on device performance data of the first set of more user devices or network performance data of a communication network that provides communication services to the first set of user devices. The device performance data has at least one of temporal or geographical commonality with the network performance data. A machine learning (ML) model is then trained based on training data, in which the training data includes the network performance data and the set of KPIs calculated for the first set of user devices. The ML model is applied to additional network performance data of the communication network to extrapolate one or more extrapolated KPIs for the first set of user devices or a second set of user devices.

Abstract: Techniques are described for using artificial intelligence (i.e., machine learning) to identify a system problem. Multiple machine learning stages, or models, are used to better categorize inputs and more quickly derive a reliable solution. Each subsequent model identifies a more specific category than a previous model, i.e., each successive model operates on a more granular level. The described techniques include staged machine learning models and user interface elements that are used to train a system and support an application development process. These techniques can be used to more easily create logic that is directed to solving a problem in a particular system.

Abstract: An analytic application may automatically determine a root cause of an issue with a wireless carrier network and generate a solution for the root cause. Initially, a data management platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. Subsequently, the analytic application may receive an indication of an issue affecting one or more user devices that are using the wireless carrier network. The analytic application may analyze the performance data using a trained machine learning model to determine a root cause for the issue affecting the one or more user devices. The trained machine learning model may employ multiple types of machine learning algorithms to analyze the performance data. The analytic application may provide the root cause or the solution that resolves the root cause for presentation.

Abstract: A method and system of managing fixed line network elements. Data from disparate sources is received by a processing layer of a monitoring server via a wireline communication network. The intelligence layer determines whether a first node from the disparate nodes is new or pre-existing. Based on a determination by the intelligence layer whether a node is new or pre-existing, different static rules are applied to the received data from the first node. Contextual information is retrieved from the measurements megastore related to the first node. A root cause of a malfunction of the first node is determined. A notification is generated based on the root cause of the malfunction.

Abstract: A method and system of managing a utility system having a plurality of subsystems. A utility management server receives performance measurement data of a subsystem of a first utility system is received, from a first utility monitoring device (UMD). A type of the subsystem and a type of the first UMD is determined. Static rules are applied based on the type of subsystem and the type of UMD. Upon determining that the predetermined condition based on the static rules is not met, identifying a subsystem and its corresponding UMD responsible for a malfunction by retrieving contextual information from the measurements megastore server, analyzing the data from the first UMD and the contextual information, and sending a notification to the UMD having the subsystem that has been identified as being the source of the malfunction.

Abstract: Techniques to optimize quality of service and quality of user experience for multi-media mobile applications are described. A traffic detection component detects the video and audio data components of a video call. Detection may be via a modified traffic detection component or via a software quality of service component exposing traffic detection component functionality to a multi-media application via an application programming interface. Based on available bandwidth for a session of the multi-media application and heuristics, video and audio data components may be placed in different contexts with different priorities. In the specific case of a video call, the video and audio data components are each associated with a quality of user experience threshold, which when available bandwidth fails to meet those thresholds, an optimizing heuristic to trigger the traffic detection component to change contexts and priorities of the video and audio data components.

Abstract: A communication cell may receive a request to establish a communication session for delivery to a core network of carrier network, the request originating from a user device connected to the communication cell. A lookup table stored in the communication cell is populated with an association of a session identifier assigned to the communication session and a caller identifier of the user device. The request is placed into an uplink buffer portion of the communication cell that is set aside for the user device. The request is encoded into one or more physical resource blocks reserved for the communication cell by a macrocell, the physical resource blocks being a part of a wireless in-band backhaul between the communication cell and the macrocell. The one or more physical resource blocks that include the request from the communication cell are then transmitted to the macrocell for delivery to the core network.

Abstract: A self-organizing network includes one or more tools. Such tools may be configured to determine, based on one or more performance indicators, that network usage in a first portion of a frequency spectrum satisfies a first usage threshold of the first portion. Such tools may also be configured to transition, in response to the determining, the plurality of users from the first portion to a second portion of the frequency spectrum different from the first portion. Such tools may further be configured to hinder the plurality of users from returning to the first portion from the second portion.

Abstract: A network fix application may automatically determine a root cause of an issue with a wireless carrier network and generate a network fix prioritization to implement a solution for the root cause before receiving a customer or network trouble ticket. Initially, a data adaptor platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. The network fix application may analyze the performance data using a trained machine learning model to predict a root cause for the issue affecting the one or more user devices based on the symptoms indicated in the performance data. Additionally, the network fix application may analyze the performance data using another trained machine learning model to provide a network fix prioritization to implement a resolution for each predicted root cause in the most optimal order.

Abstract: A computing device, which is associated with a telecommunication access network, is configured to detect (i) congestion in uplink traffic from a plurality of user equipments (UEs) to a base station (BS), and (ii) a level of the congestion in the uplink traffic from the plurality of UEs to the BS. The computing device is further configured to modify a network or UE setting to generate a modified setting, and transmit the modified setting to a first UE of the plurality of UEs, to facilitate the first UE to transmit to the BS in accordance with the modified setting. In an embodiment, the computing device is the BS.

Abstract: Techniques to optimize quality of service and quality of user experience for multi-media mobile applications are described. A traffic detection component detects the video and audio data components of a video call. Detection may be via a modified traffic detection component or via a software quality of service component exposing traffic detection component functionality to a multi-media application via an application programming interface. Based on available bandwidth for a session of the multi-media application and heuristics, video and audio data components may be placed in different contexts with different priorities. In the specific case of a video call, the video and audio data components are each associated with a quality of user experience threshold, which when available bandwidth fails to meet those thresholds, an optimizing heuristic to trigger the traffic detection component to change contexts and priorities of the video and audio data components.

Abstract: Techniques described herein relate to adjusting a quality level of media streaming. A user device may transmit a request for a first segment of a media file at a first streaming quality level. The user device may determine changes in network communication quality associated with a wireless communication in that the user device is engaged. In response to a determination, the user device may adjust quality levels of media streaming.

Abstract: A communication cell may use a wireless in-band backhaul to route backhaul traffic to a macrocell of a carrier network such that the backhaul traffic is delivered to a core network of the carrier network. The communication cell may route backhaul traffic of user devices via the wireless in-band backhaul between the communication cell and the macrocell. The wireless in-band backhaul may take place of a dedicated backhaul between the communication cell and the core network. As the backhaul traffic is routed, if a characteristic of the wireless communication between the communication cell and the macrocell fails to meet a threshold, an antenna of the communication cell may be electrically or mechanically adjusted to improve the characteristic of the wireless communication. The adjustment of the antenna includes performing a beam forming or moving one or more antenna elements of the antenna.