Abstract: An XR environment server communicates XR data meta-frames to an XR device for rendering as an XR environment. The XR environment server includes a network interface, at least one processor, and at least one memory storing instructions executable by the at least one processor to perform operations. The operations include obtaining input XR data meta-frames which define objects for rendering through the XR device as the XR environment to a user, and determining relevance of individual objects to interests of the user of the XR device. The operations adjust renderable details of the individual objects responsive to the determined relevance to the interests of the user to the individual objects, and generate compressed output XR data meta-frames from the input XR data meta-frames based on the adjusted renderable details of the individual objects. The operations communicate the compressed output XR data meta-frames toward the XR device for rendering.

Abstract: There is provided a method for assessing network performance. The method includes acquiring network measurements indicative of any changes in a network following a change to a configuration of the network and data indicative of one or more factors capable of causing the changes in the network. The one or more factors are independent of the change to the configuration of the network. The method includes analysing the acquired network measurements and data to identify a contribution of the one or more factors to a key performance indicator (KPI) and a contribution of the change to the configuration of the network to the KPI. The KPI is predicted by a machine learning model and is a measure of the network performance following the change to the configuration of the network.

Abstract: A technique for assessing positioning qualities within a localization area of a positioning system comprising a plurality of anchor nodes for determining positions of tag devices within the localization area using radio technology is disclosed. A method implementation of the technique comprises determining (S202) a positioning deviation between an absolute position of a tag device and a relative position of the tag device, the absolute position of the tag device being determined by the positioning system using the plurality of anchor nodes and the relative position of the tag device being determined based on movement related measurements performed by the tag device relative to a previously determined absolute position of the tag device, and assessing (S204) a positioning quality for the absolute position based on the determined positioning deviation.

Abstract: A computer-implemented method performed by a first node (101). The method is for handling managing one or more indications. The first node (101) operates in a communications system (100). The first node (101) determines (304) a scheduling of a transfer of data to or from a device (130) along a predicted route (140). The predicted route (140) is to be followed by the device (130) during a time period. The determining (304) of the scheduling is further based on a type of energy used by a plurality of cells (121, 122) providing radio coverage along the predicted route (140). The first node (101) initiates (305) providing one or more indications to the device (130) based on a first result of the determining (304) of the scheduling. The device (130) receives (402) the one or more indications, determines (403) whether or not to perform the data transfer based on them, and initiates (404) performing the data transfer accordingly.

Abstract: Embodiments herein relate to method performed by a radio network node for handling communication in a wireless communication network. The radio network node dynamically applies different muting patterns for muting an active component of one or more antenna branches of the radio network node and/or of one or more antenna panels of the radio network node, wherein the different muting patterns are associated with one or more types of physical channels used for communicating and/or a communication parameter related to one or more UEs. The radio network node performs a communication using the dynamically applied different muting patterns.

Abstract: A system can be configured to provide root cause analysis (“RCA”) of an issue associated with a label generated by a machine learning (“ML”) model. The system can perform operations that include determining a plurality of categories associated with a plurality of features of the ML model. The operations can further include determining a causality relationship between each category of the plurality of categories. The operations can further include determining data associated with each feature of the plurality of features. The operations can further include determining the root cause of the issue using a model explainer with ordering constraints based on the causality relationship between each category of the plurality of categories. The operations can further include performing an action associated with the issue based on the root cause of the issue.

Abstract: A technique for locating a target tag (110) using a short range radio based positioning system comprising a plurality of localization components (120) is provided, wherein the target tag (110) and the plurality of localization components (120) are configured to perform ranging measurements among each other using short range radio technology. A method implementation of the technique is performed by an orchestration component (100) of the positioning system and comprises sending, using long range radio technology, a ranging plan to the target tag (110) and one or more of the plurality of localization components (120), the ranging plan instructing the target tag (110) and the one or more of the plurality of localization components (120) to perform, using the short range radio technology, ranging measurements among each other enabling to locate the target tag (110).

Abstract: Equipment that supports a non-public communication network trains a machine learning model with a training dataset to make a prediction or decision in the network. The equipment determines whether the trained model is valid or invalid based on whether predictions or decisions that the trained model makes from a validation dataset satisfy performance requirements. Based on the trained model being invalid, the equipment analyzes the training dataset and/or the trained model to determine what additional training data to add to the training dataset. The equipment transmits signaling for configuring one or more autonomous or automated mobile devices served by the network to help collect the additional training data. The equipment then re-trains the model with the training dataset as supplemented with the additional training data.

Abstract: The correlation of per-session network logs with trouble reports provided by the users/user devices via a trouble reporting app generates labeled training information used to train Machine Learning (ML) models that are subsequently used to infer, explain, and address service issues associated with an application service session. As such, the level of automation for Quality of Experience (QoE) management increases, while the accuracy of such QoE management increases and a subscriber's experience improves.

Abstract: Calibrating a positioning system comprising a plurality of anchor nodes used to determine tag positions within a localization area using radio technology.

Abstract: A technique for predicting radio quality in a wireless communication network depending on assumed positions of one or more base stations in an area to be covered by the wireless communication network is disclosed. A method implementation of the technique is performed by a computing unit and comprises the steps of determining, for a selected position in the area with respect to assumed positions of the one or more base stations, blocking object features indicative of a spatial pattern of blocking objects present in fields of view between the selected position and the assumed positions of the one or more base stations, and determining, based on the determined blocking object features, a predicted radio quality at the selected position using a machine learning model trained to map blocking object features for selected positions with respect to one or more base station positions to corresponding radio qualities at the selected positions.

Abstract: Methods and apparatus for root cause analysis. A method includes obtaining measurement data including measurements data of features of a system. The method further includes generating a prediction value by applying a trained machine learning model to the measurement data, and also generating feature impact values by applying a generated machine learning model explainer to the measurement data. The method further includes updating an ontological representation of connections between the features of the system and the prediction value using the generated feature impact values and, based on the updated ontological representation, outputting a proposed root cause that is responsible for the prediction value.

Abstract: The correlation of per-session network logs with trouble reports provided by the users/user devices via a trouble reporting app generates labeled training information used to train Machine Learning (ML) models that are subsequently used to infer, explain, and address service issues associated with an application service session. As such, the level of automation for Quality of Experience (QoE) management increases, while the accuracy of such QoE management increases and a subscriber's experience improves.

Abstract: There is provided a method for assessing network performance. The method includes acquiring network measurements indicative of any changes in a network following a change to a configuration of the network and data indicative of one or more factors capable of causing the changes in the network. The one or more factors are independent of the change to the configuration of the network. The method includes analysing the acquired network measurements and data to identify a contribution of the one or more factors to a key performance indicator (KPI) and a contribution of the change to the configuration of the network to the KPI. The KPI is predicted by a machine learning model and is a measure of the network performance following the change to the configuration of the network.

Abstract: The present disclosure relates an evacuation management system, EMS, (40, 52, 60, 00, 200) operative to provide real-time evacuation information for evacuation of a building, triggered by alarm notification (S202). Based on determined (S214) precise real-time positions of personal ultra-wide band, UWB, devices, as determined by UWB real-time localization system, RTLS, a controller determines (S210) evacuation plans being personal UWB device specific in real-time. Based on individual evacuation plans and input from building facilities, real-time guidance information is defined (S208) and sent to each personal UWB device, providing guidance to person carrying said personal UWB device, in what direction to move (S212), to reach a safe area. Based on localization signals the UWB RTLSA then calculates updated positions of the personal UWB devices and sends to the evacuation management system. It is an advantage that trapped or injured people can be found, even in low visibility areas.

Abstract: An anchor system for a location system tracks a location of a tag device mounted to a mobile entity using a plurality of anchor devices. The anchor system comprises an anchor cable, a first anchor device affixed to the anchor cable, one or more second anchor devices affixed to the anchor cable, and a power supply circuit. Each of the second anchor device(s) is spaced from the first anchor device along a length of the anchor cable by a predetermined distance. The power supply circuit is operatively connected to the anchor cable and is configured to supply power to each of the anchor devices via the anchor cable. Each of the anchor devices is configured to wirelessly communicate with the tag device, e.g., which enables a remote network of processors in communication with the anchor devices to determine location data for the tag device.

Abstract: A technique for assessing positioning qualities within a localization area of a positioning system comprising a plurality of anchor nodes for determining positions of tag devices within the localization area using radio technology is disclosed. A method implementation of the technique comprises determining (S202) a positioning deviation between an absolute position of a tag device and a relative position of the tag device, the absolute position of the tag device being determined by the positioning system using the plurality of anchor nodes and the relative position of the tag device being determined based on movement related measurements performed by the tag device relative to a previously determined absolute position of the tag device, and assessing (S204) a positioning quality for the absolute position based on the determined positioning deviation.

Abstract: We generally describe a collision prevention system (100) comprising: a localization system (402) for determining positions of an autonomous vehicle (104) and a human (106); and a collision determination unit (404) coupled to or in communication with the localization system (402), wherein the collision determination unit (404) is configured to determine, based on the determined positions of the autonomous vehicle (104) and the human (106), whether a predefined condition for an anticipated collision of the autonomous vehicle (104) with the human (106) is met; wherein the collision prevention system (100) is configured to: lock the autonomous vehicle (104) if the predefined condition is met; alert the human (106) for whom the predefined condition for colliding with the autonomous vehicle (104) is met; and allow unlocking of the autonomous vehicle (104) to be performed or initialized by the alerted human (106) only.

Abstract: The invention relates to method and system (1) for centrally controlling uplink streaming from a plurality of devices (D) to a server (S) for data processing. The method comprises to centrally measure (S10) performance of data processing for providing a performance measurement result (r). The method continues to be executed on the device (D) by providing (D12) a control instruction (ci), which is based on the performance measurement result (r) for controlling (D13) uplink streaming parameters for sending data to the server (S).

Abstract: A technique for locating a target tag (110) using a short range radio based positioning system comprising a plurality of localization components (120) is provided, wherein the target tag (110) and the plurality of localization components (120) are configured to perform ranging measurements among each other using short range radio technology. A method implementation of the technique is performed by an orchestration component (100) of the positioning system and comprises sending, using long range radio technology, a ranging plan to the target tag (110) and one or more of the plurality of localization components (120), the ranging plan instructing the target tag (110) and the one or more of the plurality of localization components (120) to perform, using the short range radio technology, ranging measurements among each other enabling to locate the target tag (110).