Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The methods, systems, and computer readable media discussed herein are directed to determining a capacity of a network having solutions from available network options for meeting an expected demand increase for the network. Performance parameters, such as current traffic congestion level and current throughput level, may be evaluated based on the current network information of the network, and solutions, or builds, specific to the network may be obtained to maintain a given network quality level at the expected demand increase based on available network options specific to the network.

Abstract: Systems and methods for determining network congestion (e.g., reduced or low average user throughput with telecommunications networks, such as LTE networks, are described. The systems and methods described herein facilitate the identification and/or prediction of congestion at cell sites, which may enable telecommunications networks to prevent and/or remedy current or future occurrences of congestion at cell sites within their networks.

Abstract: The methods, systems, and computer readable media discussed herein are directed to determining a capacity of a network having solutions from available network options for meeting an expected demand increase for the network. Performance parameters, such as current traffic congestion level and current throughput level, may be evaluated based on the current network information of the network, and solutions, or builds, specific to the network may be obtained to maintain a given network quality level at the expected demand increase based on available network options specific to the network.

Abstract: Systems and methods for determining network congestion (e.g., reduced or low average user throughput with telecommunications networks, such as LTE networks, are described. The systems and methods described herein facilitate the identification and/or prediction of congestion at cell sites, which may enable telecommunications networks to prevent and/or remedy current or future occurrences of congestion at cell sites within their networks.

Abstract: 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.

Abstract: Systems and methods for determining network congestion (e.g., reduced or low average user throughput with telecommunications networks, such as LTE networks, are described. The systems and methods described herein facilitate the identification and/or prediction of congestion at cell sites, which may enable telecommunications networks to prevent and/or remedy current or future occurrences of congestion at cell sites within their networks.

Abstract: Systems and methods for determining network congestion (e.g., reduced or low average user throughput with telecommunications networks, such as LTE networks, are described. The systems and methods described herein facilitate the identification and/or prediction of congestion at cell sites, which may enable telecommunications networks to prevent and/or remedy current or future occurrences of congestion at cell sites within their networks.

Abstract: Systems and methods for determining network congestion (e.g., reduced or low average user throughput with telecommunications networks, such as LTE networks, are described. The systems and methods described herein facilitate the identification and/or prediction of congestion at cell sites, which may enable telecommunications networks to prevent and/or remedy current or future occurrences of congestion at cell sites within their networks.

Abstract: Systems and methods for determining network congestion (e.g., reduced or low average user throughput with telecommunications networks, such as LTE networks, are described. The systems and methods described herein facilitate the identification and/or prediction of congestion at cell sites, which may enable telecommunications networks to prevent and/or remedy current or future occurrences of congestion at cell sites within their networks.