Abstract: According to example embodiment, a method may include transmitting, by a master node (MN) to a target-secondary node (T-SN), a request for the target-secondary node (T-SN) to prepare a set of one or more candidate target primary cells of a secondary cell group (candidate target PSCells) for a conditional PSCell change for the user device; and transmitting, by the master node (MN) to a source-secondary node (S-SN) that provides dual connectivity for a user device, information indicating or relating to an arrival probability of a cell change for the user device to the target-secondary node (T-SN).

Abstract: An apparatus comprising: means for establishing a connection to a network; means for predicting, by an algorithm-based model implemented in said apparatus, whether any of configurable features of the apparatus infers a predetermined likelihood to cause an anomalous operating condition in said apparatus; and means for signalling information about said configurable features to the network.

Abstract: Example embodiments may relate to controlling re-training of a machine learning (ML) model deployed at a device. A method may comprise: performing, by a device associated with a communication network, a task with a ML model to obtain an output, wherein the output is configured to be used for performance of a network operation of the communication network; receiving, from an access node of the communication network, feedback data indicative of a cause of a failure of the network operation; and determining, based on the feedback data, to perform at least one of the following: re-training the machine learning model for performing the task, updating at least one parameter of a non-machine learning algorithm associated with performance of the task with the machine learning model, refraining from re-training the machine learning model, or refraining from updating the at least one parameter of the non-machine learning algorithm.

Abstract: Apparatus comprising: one or more processors, and memory storing instructions that, when executed by the one or more processors, cause the apparatus to perform: monitoring whether a terminal suffers a performance issue due to an artificial intelligence/machine learning operation performed by the terminal; performing an action related to the artificial intelligence/machine learning operation to remove or reduce the performance issue if the terminal suffers the performance issue due to the artificial intelligence/machine learning operation.

Abstract: There is provided an apparatus, a method and a computer program product. In accordance with an embodiment the method includes measuring signals of one or more beams of a cell of a wireless communication network for handover; obtaining information of an identity of the one or more beams from the measured signals; storing the measurement results and the identity of the one or more beams; and sending the measurement results and the identity of the one or more beams to the wireless communication network when at least one predetermined condition is fulfilled.

Abstract: A system, apparatus, method, and non-transitory computer readable medium for providing location management function (LMF) assisted mobility robustness optimization (MRO) may include a radio access network (RAN) node which is caused to, collect network handover information associated with at least one first user equipment (UE) device, determine whether to update a mobility policy associated with the RAN node based on the collected network handover information and a desired threshold condition, perform a first mobility policy update procedure for the RAN node based on results of the determination, receive current location information corresponding to at least one second UE device traveling between the at least one cell pair from a location management function (LMF) network device, and assign updated mobility configuration parameters to the at least one second UE device.

Abstract: An apparatus including: at least one processor; and at least one non-transitory memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: associate communication beams into at least two different groups, where at least one of the groups has at least two of the communication beams; based upon beam-group specific key performance indicators, where the beam-group specific key performance indicators have been based upon the association of the communication beams into the at least two different groups, use the beam-group specific key performance indicators to determine at least one beam-group specific mobility parameter for at least one of the groups of communication beams; and transmit the at least one beam-group specific mobility parameters to a base station.

Abstract: An apparatus including: at least one processor; and at least one non-transitory memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: associate communication beams into at least two different groups, where at least one of the groups has at least two of the communication beams; based upon beam-group specific key performance indicators, where the beam-group specific key performance indicators have been based upon the association of the communication beams into the at least two different groups, use the beam-group specific key performance indicators to determine at least one beam-group specific mobility parameter for at least one of the groups of communication beams; and transmit the at least one beam-group specific mobility parameters to a base station.