Abstract: Systems, methods, apparatuses, and computer program products for multi-user (MU) multiple-input multiple-output (MIMO) user pairing selection are provided. One method may include selecting multi-user multiple input multiple output (MU MIMO) candidate beams using deep neural network(s) (DNNs), and selecting paired users based on the selected beams. The deep neural network(s) (DNNs) are trained to maximize multi-user priority metric (MU-PM) or a heuristic of the multi-user priority metric (MU-PM).

Abstract: An apparatus includes circuitry configured to: receive a request from a radio access network algorithm to determine whether there is a distribution shift related to a temporal characteristic of a cell of a communication network; request data from a radio access network node or a controller platform related to the temporal characteristic; receive the requested data related to the cell from the radio access network node or the controller platform; determine whether there is a distribution shift related to the temporal characteristic; in response to determining that there is a distribution shift, select a learning type for an update to a model; and update the model such that, when the model is provided to an inference server, causes the radio access network algorithm to use the updated model to perform at least one action to optimize the performance of the radio access network node or other radio access network node.

Abstract: A method includes receiving, from a radio access network (RAN) node within a wireless network, connection event information for one or more user devices and associated channel condition information; and determining a connection behavior status of a user device based on at least a portion of the connection event information and associated channel condition information and a connection behavior status model, wherein the connection behavior status model provides a mapping or association between connection event information and associated channel condition information for one or more user devices and a connection behavior status.

Abstract: An apparatus including an input configured to receive at least one notification from at least one radio access network node controller, the at least one notification caused to notify the apparatus of at least one physical channel assignment policy indication; an assigner configured to implement at least one physical channel assignment based on the at least one physical channel assignment policy indication; an output configured to generate and transmit at least one assignment notification to at least one user equipment associated with the apparatus, the assignment notification caused to notify the at least one user equipment of the at least one physical channel assignment.

Abstract: Apparatuses and methods in a communication system are provided. A method comprises receiving from network instructions of how to control multi-user multiple input multiple output connections maintained by one or more radio access nodes, the connections utilising one or more slices. One or more radio access nodes perform, based at least in part on the received network instructions, multi-user pairing of terminal devices of the same or different slices, and determine, based at least in part on the received network instructions, slice-based quota taking multi-user pairing and interference arising from paired allocations into account.

Abstract: To maximize power saving in a radio access network comprising cells, an optimal action amongst actions comprising switching on one or more cells, switching off one or more cells, and doing nothing is determined using a trained model, which maximizes a long term reward on tradeoff between throughput and power, the trained model taking as input a load estimate. The trained model may be updated online using measurement results on load, throughput and power consumption.

Abstract: To maximize power saving in a radio access network comprising cells, an optimal action amongst actions comprising switching on one or more cells, switching off one or more cells, and doing nothing is determined using a trained model, which maximizes a long term reward on tradeoff between throughput and power, the trained model taking as input a load estimate. The trained model may be updated online using measurement results on load, throughput and power consumption.

Abstract: Apparatuses and methods in a communication system are provided. A method comprises receiving from network instructions of how to control multi-user multiple input multiple output connections maintained by one or more radio access nodes, the connections utilising one or more slices. One or more radio access nodes perform, based at least in part on the received network instructions, multi-user pairing of terminal devices of the same or different slices, and determine, based at least in part on the received network instructions, slice-based quota taking multi-user pairing and interference arising from paired allocations into account.

Abstract: Apparatuses and methods in a communication system are provided. A method comprises receiving from network instructions of how to control multi-user multiple input multiple output connections maintained by one or more radio access nodes, the connections utilising one or more slices. One or more radio access nodes perform, based at least in part on the received network instructions, multi-user pairing of terminal devices of the same or different slices, and determine, based at least in part on the received network instructions, slice-based quota taking multi-user pairing and interference arising from paired allocations into account.

Abstract: To maximize power saving in a radio access network comprising cells, an optimal action amongst actions comprising switching on one or more cells, switching off one or more cells, and doing nothing is determined using a trained model, which maximizes a long term reward on tradeoff between throughput and power, the trained model taking as input a load estimate. The trained model may be updated online using measurement results on load, throughput and power consumption.

Abstract: An apparatus includes a beam selection hardware accelerator for determining a set of beams to be used for data scheduling by a wireless node for a transmission time interval, the beam selection hardware accelerator being configured to: receive a beam information and information indicating an angular separation of beams for a set of selected beams; create a graph based on the beam information and the minimum angular separation; select a set of beams, out of a plurality of beams, as a maximum weight independent set of beams based on the created graph; and provide a notification of the selected set of beams.

Abstract: An apparatus includes at least one processor; and at least one non-transitory memory including computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to: transmit an indication of a transformation function to a user equipment, wherein at least one input to the transformation function comprises a location of a user equipment and at least one measurement of a radio channel; receive a representation from the user equipment, the representation being a result of a calculation using the transformation function and the at least one input to the transformation function; and determine, using the representation, a channel quality of at least one secondary cell.

Abstract: Apparatuses and methods in a communication system are provided. A method comprises receiving from network instructions of how to control multi-user multiple input multiple output connections maintained by one or more radio access nodes, the connections utilising one or more slices. One or more radio access nodes perform, based at least in part on the received network instructions, multi-user pairing of terminal devices of the same or different slices, and determine, based at least in part on the received network instructions, slice-based quota taking multi-user pairing and interference arising from paired allocations into account.

Abstract: Systems, methods, apparatuses, and computer program products for determining a grid-of-beams (GoB) are provided. One method may include collecting network data for training a neural network, train the neural network, using the collected data, to learn a non-discounted cumulative reward Q that evaluates a benefit of including a given beam into a grid-of-beams (GoB), iteratively applying the trained neural network to select at least one optimal beam to include in the grid-of-beams (GoB), and selecting one or more beams from the grid-of-beams (GoB) to transmit to a user equipment or to receive transmission from the user equipment.

Abstract: An apparatus, method and computer program product of a new functional entity, namely an RRC-Inactive Context Hosting (RICH) entity, receiving, from a radio access node, a Push UE context notification or a Fetch UE Context Request. In response to the receiving of the Push UE context notification, the RICH entity sends the radio access node an ACK or NACK, while in response to the receiving of the Fetch UE Context Request, the RICH entity retrieves information requested. In response to the sending of the ACK, the RICH entity stores information contained in the notification, while in response to the retrieving, the RICH entity sends the radio access node the retrieved information.

Abstract: A server associated with a core network may include a memory storing computer-readable instructions; and at least one processor coupled to the memory, the at least one processor configured to execute the computer-readable instructions to, generate a list of preferred instances of a first network function, transmit the list of the preferred instances to a server associated with a third network function, and receive a request to establish a communication session with a selected instance selected from the list of the preferred instances, if the server is associated with a selected instance of a second network function associated with the selected instance of the first network function.

Abstract: In case a first set of N user equipments attached to a radio access network via an apparatus does not exceed a maximum number M, the apparatus performs (S41) real-time and non-real-time processing for the N user equipments. In case N exceeds M, the apparatus performs (S43) real-time and non-real-time processing for a second set of M user equipments contained within the first set and forwards non-real-time processing of a third set of N-M user equipments contained within the first set but not contained within the second set to a central unit which stores (S51) context information of the user equipments of the first set and performs (S53) non-real-time processing of the user equipments of the third set.

Abstract: According to an example embodiment, a method may include receiving, by a controller from a radio access network (RAN) node within a wireless network, at least one of a neural network support information, and a measurement information that includes one or more measurements by the radio access network node or one or more measurements by a wireless device that is in communication with the radio access network node; determining, by the controller based on the at least one of the neural network support information and the measurement information, a configuration of a neural network for the radio access network node; an sending, by the controller to the radio access network node, neural network configuration information that indicates the configuration of the neural network for the radio access network node.

Abstract: This document discloses a solution for configuring a radio resource control connection. According to an aspect, a method comprises: storing, in a database, an identifier of a terminal device and a first set of parameters of a first radio resource control connection of a terminal device; retrieving, from the database by using the identifier after the first radio resource control connection has been terminated, the parameters of the first radio resource control connection; and configuring, on the basis of the retrieved parameters of the first radio resource control connection, at least one operational parameter of a second radio resource control connection of the terminal device identified by the identifier.

Abstract: Provided is a central server, including a memory storing computer-readable instructions; and at least one processor coupled to the memory, the at least one processor configured to execute the computer-readable instructions to receive a physical location of a distributed unit; generate a list of one or more measurement servers based on the physical location; and send the list of one or more measurement servers to the distributed unit.