Abstract: A system described herein may identify one or more Key Performance Indicators (“KPIs”) associated with a first base station. The system may identify, based on the one or more KPIs, an occurrence of a particular event, and select a second base station and a repeater device. The repeater device and the second base station may implement the same set of wireless frequencies. The system may cause the repeater device to repeat wireless signals transmitted to or from the second base station, and may cause the first base station to shut down or to enter a low-power mode. A UE that is wirelessly connected to the first base station prior to the first base station shutting down or entering the low-power mode, may wirelessly connect to the second base station via the repeater device based on the first base station shutting down or entering the low-power mode.

Abstract: A device may receive location data identifying a geographic location. The device may generate, based on the location data, a plurality of spatial regions including a primary spatial region centered on the geographic location and a set of surrounding spatial regions adjacent to the primary spatial region. The device may retrieve network measurement data collected within the plurality of spatial regions, and may generate, for each spatial region, a statistical distribution representing network conditions based on the network measurement data within that spatial region. The device may analyze relationships between the statistical distributions of adjacent spatial regions to determine spatial variations in network conditions, and may adjust network equipment configurations based on the relationships to improve network performance in regions where the statistical distributions indicate degraded network conditions.

Abstract: A system described herein may identify one or more Key Performance Indicators (“KPIs”) associated with a first base station. The system may identify, based on the one or more KPIs, an occurrence of a particular event, and select a second base station and a repeater device. The repeater device and the second base station may implement the same set of wireless frequencies. The system may cause the repeater device to repeat wireless signals transmitted to or from the second base station, and may cause the first base station to shut down or to enter a low-power mode. A UE that is wirelessly connected to the first base station prior to the first base station shutting down or entering the low-power mode, may wirelessly connect to the second base station via the repeater device based on the first base station shutting down or entering the low-power mode.

Abstract: A system described herein may receive a plurality of data sets; generate, for each data set, an Eigenvector representing a maximum variance of the data set; generate, for each data set, a projected vector, wherein generating a particular projected vector includes identifying a lowest distance between respective values of the particular data set and the particular Eigenvector, wherein the particular projected vector includes values along the Eigenvector that are each a lowest distance from a corresponding value of the particular data set; compare respective projected vectors, associated with one or more data sets, with one or more other data sets of the plurality of data sets; generate a plurality of clusters based on the comparing, wherein each cluster includes one or more data sets of the plurality of data sets; and train one or more artificial intelligence/machine learning (“AI/ML”) models based on the plurality of clusters.

Abstract: A method, a device, and a non-transitory computer-readable storage medium are described in which an predictive discontinuous reception (DRX) bypass service is provided. The bypass service may provide flow control signaling that enables an uplink grant to be transmitted to an end device regardless of the DRX mode. The bypass service may provide for an immediate grant for uplink data and may improve latency. The bypass service may also provide flow control signaling for downlink data that may cause the end device to wake up from a DRX mode and receive downlink data. The bypass service also provides predictive scheduling that allows an external network, such as a multi-access edge computing network to establish a DRX-free downlink connection before completion of data processing. The flow control signaling may include a quality of service flow identifier value that correlates to the bypass service.

Abstract: A method, a device, and a non-transitory storage medium are described in which a cellular device-satellite communications service is provided. The service may provide establishment, maintenance, and termination of uplink and downlink connections via a satellite network, a terrestrial network, and both based on network information and satellite information. The service may also provide scheduling for user plane traffic via the uplink and downlink connections.

Abstract: One or more computing devices, systems, and/or methods for identifying interference patterns associated with wireless communication sites and/or grouping wireless communication sites based upon identified interference patterns are provided. In an example, signal strength information associated with a wireless communication site communicating with a user equipment (UE) may be determined. An interference pattern representation of one or more interference patterns associated with the wireless communication site may be generated based upon the signal strength information. A plurality of wireless communication sites, including the wireless communication site, may be grouped into groups of wireless communication sites based upon interference pattern representations associated with the plurality of wireless communication sites. The interference pattern representations include the interference pattern representation.

Abstract: In the various embodiments, a radio communication system implementing an Switched Antenna Array (SAA) is provided that minimizes the number of radio chains required for a given number of antennas by implementing a radio frequency (RF) switch that connects the radio chains to the antennas. In some embodiments, the RF switch can activate a subset of antennas in the antenna array to generate an appropriate beam pattern for communications with another device. In some embodiments, a method is provided to determine a configuration matrix corresponding to a beam pattern with a desired signal conformity level.

Abstract: One or more computing devices, systems, and/or methods for dynamic remote configuration of a reconfigurable intelligent surfaces component are provided. A controller is hosted remote to a reconfigurable intelligent surfaces network, such as within a cloud computing environment. The controller receives characteristics (e.g., signal degradation information from a base station and/or user equipment) of signals transmitted through the reconfigurable intelligent surfaces network between devices. The controller evaluates the characteristics to generate tuning parameter values to apply to cells of the reconfigurable intelligent surfaces component of the reconfigurable intelligent surfaces network. The controller transmits a control signal over a communication channel to the reconfigurable intelligent surfaces component for modifying operation of the cells using the tuning parameter values.

Abstract: In the various embodiments, a radio communication system implementing an Switched Antenna Array (SAA) is provided that minimizes the number of radio chains required for a given number of antennas by implementing a radio frequency (RF) switch that connects the radio chains to the antennas. In some embodiments, the RF switch can activate a subset of antennas in the antenna array to generate an appropriate beam pattern for communications with another device. In some embodiments, a method is provided to determine a configuration matrix corresponding to a beam pattern with a desired signal conformity level.

Abstract: A method, a device, and a non-transitory computer-readable storage medium are described in which an predictive discontinuous reception (DRX) bypass service is provided. The bypass service may provide flow control signaling that enables an uplink grant to be transmitted to an end device regardless of the DRX mode. The bypass service may provide for an immediate grant for uplink data and may improve latency. The bypass service may also provide flow control signaling for downlink data that may cause the end device to wake up from a DRX mode and receive downlink data. The bypass service also provides predictive scheduling that allows an external network, such as a multi-access edge computing network to establish a DRX-free downlink connection before completion of data processing. The flow control signaling may include a quality of service flow identifier value that correlates to the bypass service.

Abstract: A management system obtains, from a user device, information indicating a power measurement of a beam set that is utilized to communicate with the user device. The beam set includes one or more active beams, of a plurality of beams, that are associated with a single beam identifier. The management system identifies a location of the user device and thereby determines an expected power measurement of the beam set. The management system determines that a difference between the power measurement of the beam set and the expected power measurement of the beam set satisfies (e.g., is greater than or equal to) a difference threshold. The management system therefore causes the beam set to be modified. The management system may use a machine learning model (e.g., a neural network machine learning model) to facilitate modification of the beam set.

Abstract: In some implementations, a base station may provide a first continuous wave signal during a first period of time. The base station may receive, from a first device, a first response signal based on providing the first continuous wave signal. The base station may provide, to the first device, a second continuous wave signal during a second period of time subsequent to the first period of time, wherein the second continuous wave signal is provided based on receiving the first response. The base station may receive, from the first device, a second response signal based on providing the second continuous wave, wherein the second response signal includes device data obtained by the first device.

Abstract: In some implementations, a base station may provide a first continuous wave signal during a first period of time. The base station may receive, from a first device, a first response signal based on providing the first continuous wave signal. The base station may provide, to the first device, a second continuous wave signal during a second period of time subsequent to the first period of time, wherein the second continuous wave signal is provided based on receiving the first response. The base station may receive, from the first device, a second response signal based on providing the second continuous wave, wherein the second response signal includes device data obtained by the first device.

Abstract: Systems and methods provide decentralized MEC compute services. A network device receives, from a user device associated with a user account, an access request for Multi-access Edge Computing (MEC) services. The user account includes a MEC service token that indicates parameters for the MEC services. The network device validates a user of the user device to access MEC services for the user device; removes, after the validating, the MEC service token from the first user account; and grants, based on the removing, access to a MEC cluster by the user device, wherein granting access includes granting access according to the parameters.

Abstract: A device may receive capacity information associated with a plurality of base stations, and may receive user equipment demands associated with the plurality of base stations. The device may receive, from a satellite, a satellite backhaul demand associated with the satellite, and may calculate excess backhaul capacities associated with the plurality of base stations, based on the user equipment demands and the capacity information. The device may identify a base station, of the plurality of base stations, to provide a satellite backhaul path for the satellite, based on the excess backhaul capacities and the satellite backhaul demand, and may provide, to the base station, a message instructing the base station to activate a satellite antenna associated with the base station. The device may provide, to the satellite, data identifying the base station, and may establish the satellite backhaul path for the satellite, via the base station.

Abstract: One or more computing devices, systems, and/or methods for identifying interference patterns associated with wireless communication sites and/or grouping wireless communication sites based upon identified interference patterns are provided. In an example, signal strength information associated with a wireless communication site communicating with a user equipment (UE) may be determined. An interference pattern representation of one or more interference patterns associated with the wireless communication site may be generated based upon the signal strength information. A plurality of wireless communication sites, including the wireless communication site, may be grouped into groups of wireless communication sites based upon interference pattern representations associated with the plurality of wireless communication sites. The interference pattern representations include the interference pattern representation.

Abstract: A method may include obtaining connection-related data associated with user equipment (UE) devices operating in a network, wherein the UE devices include unmanned aerial vehicles (UAVs) and devices other than UAVs. The method may include storing the connection-related data; identifying, in the stored connection-related data, data associated with known UAVs and filtering the stored connection-related data based on a distance associated with a known UAV. The method may further include training a machine learning classifier using the filtered data and executing the machine learning classifier to identity UAVs operating in the network.

Abstract: A method for generating, at a mobile device, a first flow control sequence for demodulating a first wireless channel transmitted by a base station; transitioning, by the user equipment device (UE), to a first power consumption state; monitoring, by the UE while in the first power consumption state, the first wireless channel for a second flow control sequence; detecting, at the UE, that the first flow control sequence matches the second flow control sequence; transitioning, by the UE from the first power consumption state to a second power consumption state, upon detecting that the first flow control sequence matches the second flow control sequence; and receiving, at the UE, a data flow from the base station via a second wireless channel.

Abstract: A user equipment (UE) device may determine its location with a high degree of precision, beyond the capability of other current methodologies. Specifically, a UE device may obtain High Precision (HIP) coordinates of its location based on Random Access Channel (RACH) messages that the UE device exchanges with multiple wireless stations. Using RACH messages to obtain HIP coordinates imposes little communication overhead or computational burden on the UE device and the network.