Abstract: The described technology is generally directed towards jointly optimizing coverage, capacity, and layer balance in a wireless communications network while maintaining cell edge use device performance constraints. Aspects comprise monitoring edge user devices for performance information, and modifying the network based on the performance information, including jointly optimizing by changing antenna parameter data, layer balancing, handover biasing per cell neighbor pair, modifying scheduling priorities, and optimizing sector face harmonic throughput. Balancing uplink and downlink coverages are considered in the joint optimization. Further, interference is detected, predicted (as needed) and mitigated.

Abstract: The described technology is generally directed towards jointly optimizing coverage, capacity, and layer balance in a wireless communications network while maintaining cell edge use device performance constraints. Aspects comprise monitoring edge user devices for performance information, and modifying the network based on the performance information, including jointly optimizing by changing antenna parameter data, layer balancing, handover biasing per cell neighbor pair, modifying scheduling priorities, and optimizing sector face harmonic throughput. Balancing uplink and downlink coverages are considered in the joint optimization. Further, interference is detected, predicted (as needed) and mitigated.

Abstract: A system includes a base band unit pooling component that determines, via a base band unit pool of base station devices, respective uplink channel estimates of an uplink channel wirelessly coupling, using frequency division duplexing via respective modular antenna elements, a user equipment to the base band unit pool. A downlink channel estimation component of the system derives, based on the respective uplink channel estimates, a downlink channel estimate of a downlink channel wirelessly coupling, using the frequency division duplexing via a portion of the respective modular antenna elements corresponding to a base station device of the base band unit pool, the base station device to the user equipment. In turn, the system generates, using the downlink channel estimate, a group of downlink sector beams to be transmitted to the user equipment using the downlink channel via the portion of the respective modular antenna elements.

Abstract: The described technology is generally directed towards reducing latency in a wireless communications network. Radio access network latency data corresponding to a measured latency impact criterion is obtained by a network device of a wireless network. Based on the radio access network latency data, latency guidance data usable by the radio network device to achieve a reduction in communication latency that is experienced by a user equipment is predicted, e.g., by a learned model. The latency guidance data can be used to facilitate a reduction in the communication latency that is experienced by a user equipment.

Abstract: The described technology is generally directed towards jointly optimizing coverage, capacity, and layer balance in a wireless communications network while maintaining cell edge use device performance constraints. Aspects comprise monitoring edge user devices for performance information, and modifying the network based on the performance information, including jointly optimizing by changing antenna parameter data, layer balancing, handover biasing per cell neighbor pair, modifying scheduling priorities, and optimizing sector face harmonic throughput. Balancing uplink and downlink coverages are considered in the joint optimization. Further, interference is detected, predicted (as needed) and mitigated.

Abstract: The described technology is generally directed towards reducing latency in a wireless communications network. Radio access network latency data corresponding to a measured latency impact criterion is obtained by a network device of a wireless network. Based on the radio access network latency data, latency guidance data usable by the radio network device to achieve a reduction in communication latency that is experienced by a user equipment is predicted, e.g., by a learned model. The latency guidance data can be used to facilitate a reduction in the communication latency that is experienced by a user equipment.

Abstract: Aspects of the subject disclosure may include, for example, a system that provides for obtaining, by a server comprising a processor, network parameter data from an eNodeB of a wireless network. The server can determine a predicted bandwidth for a group of end user devices in a coverage area of the eNodeB according to the network parameter data. The server can receive, from an end user device of the group of end user devices, a request for the predicted bandwidth. The server can provide the predicted bandwidth to the end user device. The providing of the predicted bandwidth enables the end user device to provide a video chunk request to a content server that is based on a selected chunk delivery schedule and facilitates streaming of video content to the end user device from the content server. Other embodiments are disclosed.

Abstract: The described technology is generally directed towards reducing latency in a wireless communications network. Radio access network latency data corresponding to a measured latency impact criterion is obtained by a network device of a wireless network. Based on the radio access network latency data, latency guidance data usable by the radio network device to achieve a reduction in communication latency that is experienced by a user equipment is predicted, e.g., by a learned model. The latency guidance data can be used to facilitate a reduction in the communication latency that is experienced by a user equipment.

Abstract: An adaptive coordinator system in a self-organizing network, the system comprising a network coordinator communicating with a policy engine, the policy engine including a dynamic policy that governs at least one microservice, the network coordinator communicating with the at least one microservice; a machine learning tool in communication with the network coordinator and the plural microservices; the network coordinator including a decision algorithm establishing at least one trigger condition based on the dynamic policy, wherein when the network coordinator detects the at least one trigger condition, the network coordinator performs an action; and wherein the network coordinator communicates the action to the machine learning tool to monitor implementation of the at least one microservice according to the action, and wherein the machine learning tool generates a revised action based on implementation of the action on the plural microservices, and wherein the microservice coordinator reports the revised actio

Abstract: A more efficient network can be achieved using a network-based controller to configure routing tables to route data traffic to and from transmission points. Dynamic partitioning of network resources between the transmission points and a backhaul can be performed in conjunction with a resource scheduler of a network-based controller. The scheduler can relay scheduling metrics or benefit metrics from the network-based controller to the transmission points. Backhaul route optimization can also be used to select relay transmission points based upon conditions being determined to be satisfied.

Abstract: A passive intermodulation detection system is provided to remotely identify passive intermodulation at a base station site and diagnose the type of intermodulation and location of the non-linearity that is the source of the passive intermodulation. A passive intermodulation cancelation system can generate an equivalent signal to a received interference signal and use the equivalent signal to generate an error signal. The error signal can then be used to reinforce a learning system and converge on a steady state of the interference signal to cancel other interference signals.

Abstract: A more efficient network can be achieved using a network-based controller to configure routing tables to route data traffic to and from transmission points. Dynamic partitioning of network resources between the transmission points and a backhaul can be performed in conjunction with a resource scheduler of a network-based controller. The scheduler can relay scheduling metrics or benefit metrics from the network-based controller to the transmission points. Backhaul route optimization can also be used to select relay transmission points based upon conditions being determined to be satisfied.

Abstract: Concepts and technologies disclosed herein are directed to user equipment (“UE”) categories for machine-to-machine (“M2M”) devices operating in an Internet of things (“IoT”) network and future emerging devices. According to one aspect, a network node can receive, from an M2M device, an M2M device category for the M2M device. The network node can determine an action to perform based upon the M2M device category. The network node can cause the action to be performed.

Abstract: Dynamic grouping of cell site devices to network devices that include a group of baseband processing devices is facilitated. One method includes determining, by a device including a processor, respective load information for cell site devices of respective cell sites associated with a network; and determining, by the device, interference information associated with the cell site devices. The method also includes determining, by the device, configuration information of a switch device communicatively coupled between the cell site devices and network devices that include a group of baseband processing devices. The determining the configuration information is based on the respective load information of the cell site devices and the interference information associated with the cell site devices.

Abstract: A passive intermodulation detection system is provided to remotely identify passive intermodulation at a base station site and diagnose the type of intermodulation and location of the non-linearity that is the source of the passive intermodulation. A passive intermodulation cancelation system can generate an equivalent signal to a received interference signal and use the equivalent signal to generate an error signal. The error signal can then be used to reinforce a learning system and converge on a steady state of the interference signal to cancel other interference signals.

Abstract: A passive intermodulation detection system is provided to remotely identify passive intermodulation at a base station site and diagnose the type of intermodulation and location of the non-linearity that is the source of the passive intermodulation. A passive intermodulation cancelation system can generate an equivalent signal to a received interference signal and use the equivalent signal to generate an error signal. The error signal can then be used to reinforce a learning system and converge on a steady state of the interference signal to cancel other interference signals.

Abstract: A passive intermodulation detection system is provided to remotely identify passive intermodulation at a base station site and diagnose the type of intermodulation and location of the non-linearity that is the source of the passive intermodulation. A passive intermodulation cancelation system can generate an equivalent signal to a received interference signal and use the equivalent signal to generate an error signal. The error signal can then be used to reinforce a learning system and converge on a steady state of the interference signal to cancel other interference signals.

Abstract: Aspects of the subject disclosure may include, for example, a system that provides for obtaining, by a server comprising a processor, network parameter data from an eNodeB of a wireless network. The server can determine a predicted bandwidth for a group of end user devices in a coverage area of the eNodeB according to the network parameter data. The server can receive, from an end user device of the group of end user devices, a request for the predicted bandwidth. The server can provide the predicted bandwidth to the end user device. The providing of the predicted bandwidth enables the end user device to provide a video chunk request to a content server that is based on a selected chunk delivery schedule and facilitates streaming of video content to the end user device from the content server. Other embodiments are disclosed.

Abstract: Dynamic grouping of cell site devices to network devices that include a group of baseband processing devices is facilitated. One method includes determining, by a device including a processor, respective load information for cell site devices of respective cell sites associated with a network; and determining, by the device, interference information associated with the cell site devices. The method also includes determining, by the device, configuration information of a switch device communicatively coupled between the cell site devices and network devices that include a group of baseband processing devices. The determining the configuration information is based on the respective load information of the cell site devices and the interference information associated with the cell site devices.

Abstract: Concepts and technologies disclosed herein are directed to user equipment (“UE”) categories for machine-to-machine (“M2M”) devices operating in an Internet of things (“IoT”) network and future emerging devices. According to one aspect, a network node can receive, from an M2M device, an M2M device category for the M2M device. The network node can determine an action to perform based upon the M2M device category. The network node can cause the action to be performed.