Abstract: An apparatus, method and computer program is described comprising: receiving mobile communication network data for a user device; providing the received mobile communication network data to a model for generating a measurement gap setting based on the received data, wherein the measurement gap setting defines measurement gap parameters for use in scheduling radio measurements of neighbouring cells; and returning the generated measurement gap setting.

Abstract: In a system, apparatus, method, and non-transitory computer readable medium related to attachment procedures for passive Internet of Things (IoT) device communication with ambient energy sources, wherein a reader node is caused to, receive an association response message from a radio access network (RAN) node, the association response message including attachment information corresponding to at least one associated energy-harvesting (EH) user equipment (UE) device and the reader node, and transmit an attachment acknowledgement message to the RAN node in response to the association response message.

Abstract: In a system, apparatus, method, and non-transitory computer readable medium related to attachment procedures for passive Internet of Things (IoT) device communication with ambient energy sources, wherein a radio access network (RAN) node is caused to, receive an association request message transmitted by an energy-harvesting (EH) user equipment (UE) device based on an energy level of the EH UE device, assign a reader node from a plurality of reader nodes to the EH UE device based on the association request message, transmit an association response message to the EH UE device and the assigned reader node, the association response message including attachment information associated with the EH UE device and the assigned reader node, and receive an attachment acknowledgement message from the assigned reader node in response to the association response message.

Abstract: Systems, methods, apparatuses, and computer program products for positioning support are provided. One method may include receiving, by a UE configured with power saving feature(s), positioning performance requirements for a positioning session. The method may also include estimating an impact of one or more power saving or reduced capability features on positioning measurements associated with the positioning session and, based on the accuracy and latency requirements and the estimated impact, determining the power saving or reduced capability features that the UE can implement while still achieving the accuracy and latency requirements for the positioning session. The method may then include signaling, to a network node, information on the determined power saving or reduced capability features that the UE can implement while still achieving the required accuracy and latency requirements for the positioning session.

Abstract: According to an example embodiment, a client device is configured to receive a validation model from a centralised unit device, wherein the validation model includes a machine learning model configured to predict an output from an input based on a plurality of model parameters; collect radio measurements corresponding to the input of the validation model and parameters corresponding to the output of the validation model; obtain predicted parameters as the output of the validation model by feeding the collected radio measurements as the input into the validation model; compare the collected parameters and the predicted parameters; compute a plurality of gradient vectors for the plurality of model parameters of the validation model based on the comparison between the collected parameters and the predicted parameters; and transmit the plurality of gradient vectors for the plurality of model parameters of the validation model to the centralised unit device.

Abstract: Systems, methods, apparatuses, and computer program products for power state transition handling for energy harvesting aware user equipment are provided. For example, a method can include monitoring an energy level and power state of a user equipment. The method can also include determining whether the energy level satisfies a power state transition criterion. The method can further include transitioning from a first power state to a second power state based on the power state transition criterion being determined to be satisfied by the energy level of the user equipment.

Abstract: Systems, methods, apparatuses, and computer program products for power state transition handling for energy harvesting aware user equipment are provided. For example, a method can include sending, by a user equipment, a message to a network indicating either a power state transition or non-transition. The power state transition can correspond to the user equipment transitioning from a first power state to a second power state based on an available energy of the user equipment. The method can also include receiving, by the user equipment, an information message from the network in accordance with the power state transition.

Abstract: Embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media of energy harvesting information supported User Equipment (UE) scheduling. The method includes reporting, to a network device in the radio network, energy harvesting capability of the terminal device indicating a first energy value (?Et) collected during a first time interval (?t) and a second energy value (EAvg) averaged over a second time interval; and communicating with the network device to transmit data according to scheduling information received from the network device and determined based on the energy harvesting capability of the terminal device. In this way, the terminal device may be scheduled by the network based on its energy harvesting capability, to maintain a trade-off between harvested energy utilization and fairness in scheduling from Passive IoT UEs.

Abstract: Systems, methods, apparatuses, and computer program products for cluster based local ML model training host selection in asynchronous federated learning model collection. A method may include transmitting local model parameters following training of a model of at least one network element to a network node to be used to cluster the at least one network element with one or more other network elements. The method may also include training, by one or more network elements selected from the cluster, an aggregated model using the local model parameters. The method may further include transmitting, by the one or more network elements selected from the cluster, updated local model parameters of the at least one network element as a result of the training to the network node.

Abstract: Systems, methods, apparatuses, and computer program products for positioning support are provided. One method may include receiving, by a UE configured with power saving feature(s), positioning performance requirements for a positioning session. The method may also include estimating an impact of one or more power saving or reduced capability features on positioning measurements associated with the positioning session and, based on the accuracy and latency requirements and the estimated impact, determining the power saving or reduced capability features that the UE can implement while still achieving the accuracy and latency requirements for the positioning session. The method may then include signaling, to a network node, information on the determined power saving or reduced capability features that the UE can implement while still achieving the required accuracy and latency requirements for the positioning session.

Abstract: Disclosed is a solution for managing a radio map based on radio fingerprinting measurements. A method comprises: acquiring a radio map of an area, the radio map based on radio frequency measurements performed between at least one access node of a wireless network and terminal devices within the area; detecting at least one gap in the radio map and determining geographical coordinates of the at least one gap; causing transmission of a message comprising at least one information element requesting for additional measurements and comprising the geographical coordinates of the at least one gap; in response to the message, receiving at least one radio frequency measurement report related to at least one terminal device and comprising radio frequency measurement data and at least one measurement location where the radio frequency measurement data has been measured; and updating the radio map on the basis of the radio frequency measurement data.

Abstract: A method and a system for oil recovery are provided. An exemplary method includes injecting thickened carbon dioxide (CO2) into the top of a reservoir containing oil. An interface is formed between the thickened CO2 and the oil. The oil is mobilized by the thickened CO2. The mobilized oil is recovered with a recovery well drilled below the reservoir.

Abstract: A method for recovering hydrocarbons from a hydrocarbon bearing formation includes introducing a first solution having a first salt into the hydrocarbon bearing formation. A second solution is also introduced into the hydrocarbon bearing formation, wherein the second solution has a second salt and a foaming agent. The first salt and the second salt produces a nitrogen gas, and the nitrogen gas and the foaming agent produces a foam formed in-situ within the formation. The foam forms a foam barrier, and carbon dioxide is introduced into the formation to form a gas cap, wherein the carbon dioxide gas cap has a gas front that is separated from the hydrocarbons by the foam barrier.

Abstract: An apparatus of a first communication node is provide that includes: means for synchronising a common reference timing with a second communication node; means for obtaining an indication of a time window that specifies a period of time between first and second time instances; and means for configuring a machine learning-based function at the first communication node, wherein the configuration of the machine learning-based function is common between the first and second communication nodes. The apparatus further includes means for executing the machine learning-based function; and means for obtaining information by measuring a performance metric, for the machine learning-based function, during the time window.

Abstract: A method comprising: storing a received first and machine learning model instance and a received second machine learning model instance in a cache of a terminal, wherein the first machine learning model instance is associated to a first cell and configured to make, if activated, a first prediction for the terminal, and the second machine learning model instance is associated to a second cell different from the first cell and configured to make, if activated, a second prediction for the terminal; checking if a predefined first requirement is fulfilled; activating the first machine learning model instance to make the first prediction if the predefined first requirement is fulfilled; inferring a decision involving the terminal based on the first prediction if the predefined first requirement is fulfilled; inhibiting to infer the decision involving the terminal based on the second prediction if the predefined first requirement is fulfilled.

Abstract: First user equipments are detected out of a plurality of user equipments of a cellular communication system (S201). The user equipments respectively correspond to a distributed node of a federated machine-learning concept and respectively generate a partial machine-learning model, wherein partial machine-learning models generated by the plurality of user equipments are to be used to update a global machine-learning model at the network side of the cellular communication system. The first user equipments are user equipments comprising ready partial machine-learning models.

Abstract: A UE may be enabled to provide low latency, high reliability, and power savings. If a message of the UE is delay-sensitive, the UE may indicate to a gNB that fast retransmission scheduling may be necessary if a packet is not received over PUSCH. After transmitting the packet, the UE may monitor PDCCH for an indication that retransmission is required. This monitoring may occur sooner than a PDCCH monitoring period would otherwise allow. If the UE receives a DCI indicating that retransmission is required, the UE may retransmit the packet as well as an indication for a fast transmission request. This process may continue until an acknowledgement of the received packet is received in DL or no DCI indicating retransmission is received in DL. Accordingly, the gNB may quickly receive the retransmitted packet while the UE saves power by only performing additional monitoring when requested.

Abstract: Method comprising: receiving information related to an intended federated learning training, wherein the intended federated learning training involves a set of candidate members performing a respective local training; generating federated learning specific assistance information for the intended federated learning training based on the information related to the intended federated learning training; providing the federated learning specific assistance information in response to the receiving the information related to the intended federated learning training.

Abstract: It is provided a method comprising: monitoring if a distributed training host receives a request from a meta-training host to provide a machine learning model; checking whether a link from the distributed training host to the meta-training host is required for another data communication having higher priority than providing the machine learning model such that the other data communication will block the link for the providing the machine learning model to the meta-training host; informing the meta-training host, in response to the request, that the link is required for the other data communication if the link is required for the other data communication.

Abstract: A method for enhanced oil recovery from a hydrocarbon bearing subterranean formation includes withdrawing hydrocarbons from a production well extending into the formation, identifying a high permeability streak in the formation, and injecting a dense CO2 composition from an injection well into the high permeability streak. The dense CO2 composition includes dense CO2 and a thickener soluble in the dense CO2. The thickener includes copolymer. The method includes, after injecting the dense carbon dioxide composition into the high permeability streak, injecting an aqueous treatment fluid into the formation.