Abstract: Systems and methods are provided for controlling network congestion. A processor of UE is configured by machine-readable instructions to communicate data packets between the UE and a wireless network that further communicates with an additional UE. The UE is low latency, low loss, scalable throughput (L4S) enabled and the additional UE is not L4S enabled. The UE that is L4S enabled receives a first notification of wireless network congestion for the wireless network and sends a second notification to the additional UE of the wireless network congestion by the UE. The second notification causes the additional UE that is not L4S enabled to mitigate the wireless network congestion.

Abstract: The disclosed technology manages temperature-induced signal degradation in terrestrial wireless telecommunications networks. The technology involves monitoring the temperature of an active radio antenna at a base station. The technology determines a triggering temperature that causes signal degradation and determines an available passive radio antenna to offload the user data within the same base station. Upon detecting the triggering temperature, user data is offloaded to the passive radio antenna. Communication is restored to the active radio antenna once normal temperature conditions along with quality signal are restored. The technology can dynamically distribute the offloading of user data by using artificial intelligence (AI)/machine learning (ML) algorithms to offload user data to the available passive radio that can maintain signal quality for the users.

Abstract: The system receives activity data generated from a wireless device connected to a base station of a telecommunication network. The activity data includes an account status of a subscriber, subscriber traffic type, or service type. The account status of the subscriber is classified as a premium subscriber or a standard subscriber. The system causes the activity data to be inputted into a machine learning (ML) model. The system receives, as an output from the ML model, a beamforming plan for the base station. The beamforming plan includes a direction to transmit a beam, a time period to transmit the beam, and at least one network slice on which to transmit the beam. The system generates the beam on the at least one network slice in accordance with the beamforming plan.

Abstract: Aspects herein provide systems, methods, and media for dynamically scheduling multiplexing in a wireless network. In aspects, a base station determines whether to utilize multiplexing without power boosting or to utilize power boosting without multiplexing when scheduling and communicating a reference signal over a downlink channel for a user device. These autonomous determinations of the base station are based on an evaluation of signal metrics of a user device and/or base station characteristics relative to one or more customized thresholds.

Abstract: Systems, methods, and software are disclosed herein for anomaly detection in a wireless communication network based on congestion notification in various implementations. In one example, a computing apparatus processes network telemetry data and congestion data using a machine learning model trained to detect anomalous behavior on wireless communication network. In response to detecting the anomalous behavior, the computing apparatus identifies a source of the anomalous behavior on the network and initiates an action with respect to a network function associated with the source of the anomalous behavior to mitigate one or more effects of the anomalous behavior.

Abstract: Systems, methods, and software are disclosed herein for allocating radio resources of an access node of a wireless communication network based on congestion notification in various implementations. In one example, a computing apparatus processes congestion notification data to detect a level of congestion in data traffic carried of a network slice by an access node of a wireless communication network. The computing apparatus determines that the level of congestion exceeds a threshold value for reallocating radio resources of the access node and reallocates the radio resources of the access node to provide additional carrying capacity for the data traffic of the network slice based on determining that the level of congestion exceeds the threshold value.

Abstract: Techniques are described herein for allocating bandwidth parts to user devices to enable a range of the user devices to be boosted when they are further away from a base station. In embodiments, such techniques may comprise receiving information about at least one user device operating on a network and determining, based on that information, a signal strength of the at least one user device within a cell. The techniques further comprise determining an allocation of bandwidth parts to be applied to a cell, and determining, based on the signal strength of the user device and the allocation of bandwidth parts, an assigned bandwidth part for the at least one user device. Once such a bandwidth assignment has been determined, the techniques further involve providing the assigned bandwidth part to be used by the at least one user device.

Abstract: Systems, methods, and software are disclosed herein for allocating beamforming resources of a base station of a wireless communication network based on congestion notification which includes detecting Explicit Congestion Notification (ECN) data of data traffic of user equipment (UEs) in communication with a base station; determining that the ECN data comprising a congestion notification exceeds a threshold value; and determining an allocation of beamforming resources of the base station among the UEs based on determining that the ECN data comprising a congestion notification exceeding the threshold value.

Abstract: Aspects herein provide a system and method for intelligently addressing the technological problems created by bursty traffic. In aspects, throughput estimations across various carriers are determined and utilized to perform beneficial handovers of user devices that improve service.

Abstract: A wireless communication device exchanges user data with a wireless network slice. The wireless network slice has Radio Frequency (RF) information that controls slice usage. The wireless communication device determines an RF metric for a wireless communication link. The wireless communication device or the wireless communication network process the RF metric and the RF information to select another network slice. In response to the slice selection, the wireless communication device and the wireless communication network stop the exchange of the user data with the wireless network slice and start to exchange user data with another wireless network slice.

Abstract: A wireless communication device exchanges user data to use a wireless network slice. The wireless network slice has Radio Frequency (RF) information that controls slice usage. The wireless communication device determines an RF metric for a wireless communication link. The wireless communication device or the wireless communication network process the RF metric and the RF information to select another network slice. In response to the slice selection, the wireless communication device and the wireless communication network stop the exchange of the user data to use the wireless network slice and start an exchange user data to use another wireless network slice.

Abstract: Aspects herein provide systems, methods, and media for dynamically scheduling multiplexing in a wireless network. In aspects, a base station determines whether to utilize multiplexing without power boosting or to utilize power boosting without multiplexing when scheduling and communicating a reference signal over a downlink channel for a user device. These autonomous determinations of the base station are based on an evaluation of signal metrics of a user device and/or base station characteristics relative to one or more customized thresholds.

Abstract: At a high level, the technology disclosed herein relates to dynamic Radio Resource Partitioning (RRP). In embodiments, radio frequency (RF) coverage data for one or more Fixed Wireless Access (FWA) devices (or other devices) may be received. The RF coverage data may correspond to one or more of reported channel state information feedback (e.g., Channel Quality Indicator (CQI)) from Enhanced Mobile Broadband (eMBB) user devices, particular identifiers (e.g., Service Profile Identifier (SPID)), slicing data, etc., or one or more combinations thereof. A threshold for the FWA device may be determined based on historical eMBB resource data for a particular access point. If particular RF coverage data is below the threshold, the FWA device may be blocked from RRP. If the RF coverage data is above the threshold, the FWA device may be included for RRP.

Abstract: Computerized systems and methods are provided that utilize a machine learning model to predict anomalies for a radio access network site device and taking corrective action. After a radio access network site device has received a software update, key performance indicators are extracted from the data from the radio access network site device. The key performance indicators are utilized with an anomaly risk model to determine if one or more of the key performance indicators exceeds a baseline threshold for the one or more radio access network devices. Responsive to the one or more key performance indicators exceeding a baseline threshold, a corrective action is initiated modifying the one or more radio access network devices.

Abstract: Systems and methods are provided for selecting and dynamically adjusting beamforming techniques offered to and applied to one or more devices based on a type of the device. Specifically, a device that is determined to be stationary can utilize a different beamforming technique than a device that is determined to be mobile (i.e., not stationary). Based on the determinations of whether a device is stationary or mobile, a specific beamforming technique can be offered to that device. Further, devices that are located in a same location in the service area (e.g., both devices are located at cell edge, both are near cell, etc.) can utilize different beamforming techniques such that multiple beamforming techniques are employed in the same location.

Abstract: Methods provided herein include grouping wireless devices connected to an access node in a network into one of a mobile group and a stationary group when at least some of the wireless devices in the network utilize time division duplexing (TDD) and frequency division duplexing (FDD) carrier aggregation (CA) and further utilize sounding reference signal (SRS) antenna switching to send SRS to the access node from receiving antennas of the wireless devices. The method further includes adjusting a periodicity for receiving the SRS from the wireless devices belonging to the stationary group, causing the wireless devices in the stationary group to send the SRS to the access node less frequently than the wireless devices in the mobile group.

Abstract: Techniques are described herein for allocating bandwidth parts to user devices to enable a range of the user devices to be boosted when they are further away from a base station. In embodiments, such techniques may comprise receiving information about at least one user device operating on a network and determining, based on that information, a signal strength of the at least one user device within a cell. The techniques further comprise determining an allocation of bandwidth parts to be applied to a cell, and determining, based on the signal strength of the user device and the allocation of bandwidth parts, an assigned bandwidth part for the at least one user device. Once such a bandwidth assignment has been determined, the techniques further involve providing the assigned bandwidth part to be used by the at least one user device.

Abstract: Examples provide a network testing solution using a remote-controlled testing device. A test device includes a computing device for executing network performance testing logic and a cellular device. The test device controls the cellular device via a series of commands issued to the cellular device by the computing device. The test device is placed onto or inside a vehicle. As the vehicle moves through a geographical area, the test device automatically and autonomously performs network testing operations. The test data generated during the test is periodically uploaded to a central controller. The central controller aggregates test data received from a plurality of test devices assigned to a plurality of vehicles for a given campaign. The aggregated test data is analyzed and filtered to generate performance test results. A user can dynamically set up each campaign and assign test devices and vehicles to each campaign using a graphical user interface.

Abstract: Systems, methods, and devices for managing network resources perform and/or comprise: setting a communication threshold; monitoring a communication parameter for a wireless device connected to a network, wherein the wireless device is configured for communicating with the network using a first communication technology and for communicating with the network using a second communication technology; receiving a resource status from the network; and in response to a determination that the communication parameter is below the communication threshold and based on the resource status, causing the wireless device to switch from communicating with the network using the first communication technology to communicating with the network using the second communication technology.

Abstract: Aspects herein provide systems, methods, and media for dynamically switching between multiple input multiple output algorithms to improve spectral efficiency and capacity. In aspects, based on data encoding traffic, user device mobility, and coverage, a base station automatically and intelligently selects and implements a particular downlink operating schema. Using various periodicity, the base station dynamically switches between various downlink operating schemas to reflect changing conditions in the date that encodes traffic, user device mobility, and coverage.