Abstract: A computer-implemented method performed in a multi-agent system by a first network node is provided for transferring historical data from an operating agent to a second agent for an action controlling a performance of the multi-agent system. The method includes selecting at least one operating agent for transfer of historical data to the second agent. The historical data acquired from executions of an action by the at least one operating agent that at least partially fulfills an input parameter. The selecting is based on one or more criteria including (i) a performance of the at least one operating agent on the parameter or on a related parameter; (ii) an availability of the at least one operating agent; and (iii) an identity of an actuation target system for receipt of the action. The method further includes transferring the historical data to the second agent.

Abstract: A computer implemented method for managing QoS of wireless devices in a communication network is disclosed. The method includes receiving a QoS intent from a first node, the QoS intent including an identification of a wireless device to which the QoS intent applies and a QoS requirement for the identified wireless device. The method further includes obtaining a specification of available QoS in the communication network and a specification of QoS policies in the communication network, using an ML model to determine, based on the received QoS intent and obtained specifications, at what time the at least one QoS requirement of the QoS intent can be fulfilled for the identified wireless device, and informing the first node of a result of the determination. Also disclosed is a QoS management node.

Abstract: A method performed by a control node (800) for determining whether two wireless devices meet a location criterion for closeness, the method comprising: obtaining (701), from the two wireless devices, measurements of a reference signal transmitted in a beam by a radio network node to a plurality of measurement points that are spatially distributed around the two wireless devices; and determining (702) whether the two wireless devices meet the location criterion based on the obtained measurements.

Abstract: A computer-implemented method performed by a network node is provided. The method includes receiving a request for retrieving or executing a machine learning (ML) model or a combination of ML models. The request includes a first description of a specified output feature and specified input data type and distribution of input values for a ML model or combination of ML models. The method further includes obtaining an identification of a ML model, or a combination of ML models, having a second description that at least partially satisfies a match to the first description; identifying a candidate ML model, or combination of ML models, that produces the specified output feature of the first description based on a comparison of the first and second descriptions. The method further includes selecting a third description of the identified candidate ML model, or combination of ML models, based on a convergence.

Abstract: A method of operating a protection node for protecting a pattern classification node from malicious requests may be provided. The protection node may receive, from a user node, a request containing an original pattern to be classified by a machine learning algorithm performed by the pattern classification node. The protection node may add noise to the original pattern to generate a noisy pattern. The protection node may obtain a first classification of the noisy pattern based on processing of the noisy pattern by a first clone of the machine learning algorithm at the protection node; obtain a second classification of the original pattern based forwarding the request for processing of the original pattern by the machine learning algorithm performed at the pattern classification node; and compare the first and second classifications to determine whether the first and second classifications satisfy a defined similarity rule. The protection node may use the comparison to manage the request from the user node.

Abstract: A method and system for deployment of services for customers. Network service templates (NSTs) are determined, from a permissioned distributed ledger that is distributed between network operator systems of one or more network operators and customer systems. The NSTs include respective descriptions of network characteristics that provide respective logical networks. A subset of the NSTs and a corresponding subset of the network operator systems are selected based on a service description of the first service for deployment of the first service. Instantiation of the subset of the NSTs is requested on the corresponding subset of network operator systems as a subset of network slice instances to form the first service deployed for the first customer.

Abstract: Methods (500) and devices (800) for determining a priority level for a first application or a first application type. The method comprises receiving (s502) a first usage data reporting message, the first usage data reporting message comprising a first masked usage value generated by a first UE (102) using i) a first usage value associated with a first application or a first application type and ii) a mask value. The method further comprises receiving (s504) a second usage data reporting message, the second usage data reporting message comprising a second masked usage value generated by a second UE (104) using i) a second usage value associated with the first application or the first application type and ii) the mask value. The method further comprises combining (s506) the first masked usage value and the second masked usage value, thereby generating a combined usage value; and using (s508) the combined usage value to determine a priority level for the first application or the first application type.

Abstract: Techniques for distributed object detection and tracking are described. In an example method, a first current frame from a series of frames is sent to a first node, for detection of a first object. After object detection information for the first object is received in return, a second node is selected, and a second current frame is sent to the second node for an updated object detection. In addition, while waiting for the results of the updated object detection, two or more frames following the second current frame are sent to respective tracking nodes. Object modelling information indicating location and/or classification of one or more objects, as derived from the previously received object detection information is also sent to each of the respective tracking nodes. Tracking information for the first object is received from each of the respective tracking nodes.

Abstract: A coordination node (1000) is disclosed for coordinating generation of an accident information graph comprising information representative of a vehicle accident environment. The coordination node comprises processing circuitry (1010) configured to detect an event associated with occurrence of a vehicle accident (110) and obtain environment data representative of the vehicle accident environment in which the event was detected (120). The processing circuitry is further configured to generate an accident information graph based on the obtained environment data, wherein the accident information graph comprises a structured representation of the obtained environment data and at least one semantic annotation to the obtained environment data (130).

Abstract: A user device is configured to receive Hypertext Transfer Protocol, HTTP, requests sent by a user of the device. Information is obtained from the received HTTP requests about areas of interest to the user. The information obtained from the received HTTP requests is combined to generate a machine-generated representation of the areas of interest to the user. Then, data traffic sent to the user is received, and is modified based on the machine-generated representation of the areas of interest to the user.

Abstract: There is provided a method for handling training of a machine learning model. The method is performed by a coordinating entity that is operable to coordinate the training of the machine learning model at one or more network nodes. In response to receiving a request to train the machine learning model, a first network node is selected (402), from a plurality of network nodes, to train the machine learning model based on information indicative of a performance of each of the plurality of network nodes and/or information indicative of a quality of a network connection to each of the plurality of network nodes. Transmission of the machine learning model is initiated (404) towards the first network node for the first network node to train the machine learning model.

Abstract: AM and LM parameters to be used for adapting an ASR model are derived for each audio segment of an audio stream comprising multiple audio programs. A set of identifiers, including a speaker identifier, a speaker domain identifier and a program domain identifier, is obtained for each audio segment. The set of identifiers are used to select most suitable AM and LM parameters for the particular audio segment. The embodiments enable provision of maximum constraints on the AMs and LMs and enable adaptation of the ASR model on the fly for audio streams of multiple audio programs, such as broadcast audio. This means that the embodiments enable selecting AM and LM parameters that are most suitable in terms of ASR performance for each audio segment.

Abstract: Methods and devices enable connecting devices to cellular networks using the devices' hardware identifiers. Subscriber records include a hardware identifier assigned when the devices are manufactured. A target hardware identifier included in an attachment request is associated with an International Mobile Subscriber Identity, IMSI, available to the cellular network if, according to subscriber records, the device is registered.

Abstract: Reporting information included in data records generated for network traffic activities of a plurality of mobile devices is described. A data record includes a traffic type of a traffic activity of a mobile device, a timestamp of the traffic activity, and an identifier of the mobile device. A method is provided that includes receiving a monitoring request specifying a monitoring type, and calculating from the data records a number of mobile devices having, within a given monitoring period, traffic activities that fulfil the following conditions: i) a traffic type of the traffic activity matches the monitoring type; ii) a timestamp of the traffic activity falls within the monitoring period; and iii) traffic activities associated with the same identifier and the same traffic activity are considered only once per monitoring period. The method further comprises returning, a monitoring report that is based on the calculated number of mobile devices.

Abstract: A user device is configured to receive Hypertext Transfer Protocol, HTTP, requests sent by a user of the device. Information is obtained from the received HTTP requests about areas of interest to the user. The information obtained from the received HTTP requests is combined to generate a machine-generated representation of the areas of interest to the user. Then, data traffic sent to the user is received, and is modified based on the machine-generated representation of the areas of interest to the user.

Abstract: Embodiments herein relate to a method performed by a transmitting device (12) for transferring background user data to a receiving device (10) in a communication network (1). The transmitting device (12) intercepts a packet, which packet comprises foreground user data in a payload field of the packet. The transmitting device (12) determines that the packet is intended for the receiving device (10). The transmitting device (12) establishes an available amount of data in the payload field of the packet. The transmitting device (12) adds the background user data for the receiving device (10) to the established available amount of data in the payload field. The transmitting device (12) transmits the packet with the foreground user data and the background user data to the receiving device (10).

Abstract: AM and LM parameters to be used for adapting an ASR model are derived for each audio segment of an audio stream comprising multiple audio programs. A set of identifiers, including a speaker identifier, a speaker domain identifier and a program domain identifier, is obtained for each audio segment. The set of identifiers are used to select most suitable AM and LM parameters for the particular audio segment. The embodiments enable provision of maximum constraints on the AMs and LMs and enable adaptation of the ASR model on the fly for audio streams of multiple audio programs, such as broadcast audio. This means that the embodiments enable selecting AM and LM parameters that are most suitable in terms of ASR performance for each audio segment.

Abstract: A method and system for deployment of services for customers. Network service templates (NSTs) are determined, from a permissioned distributed ledger that is distributed between network operator systems of one or more network operators and customer systems. The NSTs include respective descriptions of network characteristics that provide respective logical networks. A subset of the NSTs and a corresponding subset of the network operator systems are selected based on a service description of the first service for deployment of the first service. Instantiation of the subset of the NSTs is requested on the corresponding subset of network operator systems as a subset of network slice instances to form the first service deployed for the first customer.

Abstract: A method performed by a mobile device for handling identification of equipment. The mobile device records an image, in a recording direction at a first location, of the equipment. Upon recording the image, the mobile device further obtains one or more radiation indications for determining a direction of radiation from the equipment; and provides the obtained one or more radiation indications associated with the recorded image, to an internal identifying process at the mobile device and/or a network node for identifying the equipment.

Abstract: A method performed by a first network node (111). The method is for handling charging of a wireless device (130). The first network node (111) and the wireless device (130) operate in a wireless communications network (100). The first network node (111) modulates (307) one or more beam forming beams (121) in an antenna array (124) controlled by the first network node (111) with a pulse width modulation. The first network node (111) then charges (308), wirelessly, the wireless device (130), with the modulated one or more beam forming beams (121).