Abstract: A method for operating a telecom network having an SLA agreement is disclosed. The method comprises obtaining annotated alarm data comprising an indication of a threshold crossing of at least one state variable of the telecom network defined by the SLA. The annotated alarm data further comprises an indication of a desired value of the at least one state variable of the telecom network. Moreover, the method comprises determining a desired state of the telecom network based on the desired value of at least one state variable, and selecting a set of policy actions from a policy action bank. The policy action bank comprises a plurality of policy actions, where each policy action is associated with at least one estimated action effect.

Abstract: Methods provide wireless communication using a plurality of Antenna Processing Units APUs distributed along a radio stripe and sharing a bus along the radio stripe. Access is provided to a plurality of APU activation/deactivation states for a respective plurality of environmental conditions, wherein each one of the plurality of APU activation/deactivation states defines APUs of the plurality of APUs that are activated and APUs of the plurality of APUs that are deactivated for the respective one of the plurality of environmental conditions. Responsive to detecting a first one of the plurality of environmental conditions, a first one of the plurality of APU activation/deactivation states corresponding to the first one of the plurality of environmental conditions is applied to activate a first subset of the APUs and to deactivate a second subset of the APUs, wherein the first and second subsets of APUs are mutually exclusive.

Abstract: A computer implemented method performed by a node in a communications network for scheduling transmissions of a plurality of Internet of Things (IoT) devices to network resources in the communications network includes obtaining transmission patterns for the IoT devices. The method then includes clustering the IoT devices into clusters based on the obtained transmission patterns. The method then includes scheduling transmissions of IoT devices in different clusters to different network resources, thereby increasing synchronisation of the transmissions scheduled on each network resource and allowing for increased periods of inactivity of the network resources between transmissions.

Abstract: Embodiments described herein relate to methods and apparatuses for training a neural network. A method comprises receiving an input data set at a layer of the neural network; performing a forward pass and a backward pass on the input data set to determine regular output data; calculating a first loss associated with the regular output data; performing a quantized forward pass and a quantized backward pass on the input data set to determine quantized output data; calculating a second loss associated with the quantized output data; comparing the first loss to the second loss; and based on the comparison determining whether to reduce the input data set to provide a reduced data set.

Abstract: Embodiments herein relate to a method performed by a first network node (111) configured to operate in a communication network, wherein the first network node (111) is configured with a first machine learning, ML, model and being connected to a second network node (112) configured with a second ML model associated with the first ML model. The first network node obtains first data, from the second network node (112), associated with the second ML model; and upon a condition being fulfilled relating to the obtained first data, the first network node (111) keeps the first ML model as is, following a first evolution branch, and creates an updated version of the first ML model, following a second evolution branch, taking the obtained first data into account.

Abstract: A method for operating a telecom network having an SLA agreement is disclosed. The method comprises obtaining annotated alarm data comprising an indication of a threshold crossing of at least one state variable of the telecom network defined by the SLA. The annotated alarm data further comprises an indication of a desired value of the at least one state variable of the telecom network. Moreover, the method comprises determining a desired state of the telecom network based on the desired value of at least one state variable, and selecting a set of policy actions from a policy action bank. The policy action bank comprises a plurality of policy actions, where each policy action is associated with at least one estimated action effect.

Abstract: A first network node operating in a communication node can receive a plan indicating tasks to be performed by at least one second network node operating in the communication network. The first network node can determine a network slice schedule based on the tasks to be performed by the at least one second network node operating in the communication network. The first network node can provide the network slice schedule to a network slice orchestrator operating in the communication network.

Abstract: In one aspect there is a method for detecting whether a first system should be declared as an impostor. In one embodiment, the method includes generating baseline system output information using first system input; exposing the first system to the first system input; obtaining first system output information generated by the first system based on the first system's exposure to the first system input; determining a first similarity measure that indicates a similarity between the baseline system output information and the first system output information generated by the first system; and using the first similarity measure, determining whether or not to declare the first system as an impostor.

Abstract: Methods provide wireless communication using a plurality of Antenna Processing Units APUs distributed along a radio stripe and sharing a bus along the radio stripe. Access is provided to a plurality of APU activation/deactivation states for a respective plurality of environmental conditions, wherein each one of the plurality of APU activation/deactivation states defines APUs of the plurality of APUs that are activated and APUs of the plurality of APUs that are deactivated for the respective one of the plurality of environmental conditions. Responsive to detecting a first one of the plurality of environmental conditions, a first one of the plurality of APU activation/deactivation states corresponding to the first one of the plurality of environmental conditions is applied to activate a first subset of the APUs and to deactivate a second subset of the APUs, wherein the first and second subsets of APUs are mutually exclusive.

Abstract: A mobile device for travelling to a destination using a communication network is provided. The mobile device obtains from one or more network nodes in the communication network, a first path over a first sub-region of a region, comprising one or more sub-regions, towards the destination. The mobile device further follows the first path; and upon entering, or being in, a second sub-region of the region having a level of connectivity below a threshold, switches to follow a second path calculated locally at the mobile device.

Abstract: A method for configuring devices for a user is provided. The method includes creating a device-set profile for the user. The device-set profile includes a first set of configuration parameters for a first set of devices at a first location. The device-set profile further includes usage characteristics information and device interactions information for devices in the first set of devices. The method further includes retrieving the device-set profile for the user; discovering a second set of devices at a second location; and automatically configuring the second set of devices based on the device-set profile for the user.

Abstract: A method for managing an air quality control system is disclosed. The method includes monitoring air quality changes in an environment caused by a deployment of units, estimating individual rates of change of air quality achieved by specific units, and using the estimated rates of change to train a prediction model. The method further includes receiving a request for air quality control of a specified environment, using the trained prediction model to predict unit rates of change that would be achieved by units if deployed within the specified environment and generating an assignment of units for the specified environment on the basis of the predicted unit rates of change and a target air quality parameter.