Abstract:
A monitoring system is provided for monitoring transport of data through interconnected nodes for processing data packets in a communication system, wherein said data packets conform to a layered transmission protocol, the system comprising : (1) a marking node for marking a packet selected according to a marking rule by placing a monitoring indicator in the lowest protocol layer thereof, said data packet having a first number of protocol layers, (2) at least, one packet processing node for forming a data packet based or the marked packet, such that said formed data packet comprises a second number of protocol layers that is different from said first number of protocol layers and such that said indicator is in the lowest protocol layer of said formed data packet, and (3) a monitoring node for monitoring said transport of data on the basis of the indicators in data packets that have passed through the at least one packet processing node.
Abstract:
A technique for traffic monitoring in a network (100) comprising monitoring components (N1, N2) and a management centre (MC) is described. A method implementation comprises the steps of selecting a first set of local identifiers from a larger second set of local identifiers, wherein the local identifiers are capable of providing a unique identification of a network connection at the first monitoring component, filtering network connections, allocating a local identifier of the first set of local identifiers to a network connection in case a filter condition applies during the filtering, checking associations of network traffic with local identifiers, and selectively monitoring network traffic associated with a local identifier from the first set of local identifiers.
Abstract:
Embodiments herein relate to, for example, a method performed by a UE (10) for handling positioning of the UE in a wireless communication network. The UE measures a CIR of a signal from a radio network node; and initiates a process for determining whether the UE is indoors or outdoors using an ML model with the measured CIR as input.
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 (a) determining (S202), 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 (b) determining (S204), 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:
A network node (140) leverages machine learning models and their corresponding model explainers (86) to automatically optimize network monitoring configuration for service assurance. The active services of a user session serve to identify applicable service assurance scenarios. Using a knowledge base representing corresponding machine learning models and their corresponding model explainers, one or more low-level features to be reported are selected. The selected features are those that are determined to have greatest relative importance on service-level performance indicators. The metrics associated with the selected features are then input into the network configuration management system.
Abstract:
A safety system 16 safeguards a physical object 14 in a hazardous environment 10. The safety system 16 obtains a risk score 30 that reflects an extent to which the physical object 14 is in danger in the hazardous environment 10. Based on the risk score 30, the safety system 16 adapts one or more parameters 32 that govern measurement of one or more kinematic properties of the physical object 14 in the hazardous environment 10.
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 method by a neuromorphic device in a wireless communication network which communicates using radio frames and carrier frequencies. The method includes obtaining a high dimensional (HD) vector containing symbols. At least some symbols have a value indicating a pattern of firing events for associated one or more neurons of a neural network (NN). For each symbol in the HD vector having a nonzero value, selecting a subframe of a radio frame and/or a carrier frequency among a set of carrier frequencies, based on a defined mapping between subframes of the radio frame and/or carrier frequencies of the set and the locations of symbols in the HD vector, determining a time offset relative to the selected subframe and/or a frequency offset relative to the selected carrier frequency, based on the value of the symbol, and transmitting an impulse at the determined time offset relative to the selected subframe and/or at the determined frequency offset relative to the selected carrier frequency. (Figure 7)
Abstract:
A method by a neuromorphic device in a wireless communication network which communicates using radio resource elements. The method includes obtaining a high dimensional (HD) vector containing symbols indicating whether a firing event occurred for associated neurons of a neural network. For each of at least some symbols in the HD vector which indicate the firing event occurred for an associated at least one neuron, the method includes transmitting an impulse using a radio resource element which is mapped to a location of the symbol in the HD vector. Individual locations of symbols in the HD vector have a defined mapping to individual ones of the radio resource elements.
Abstract:
The disclosure provides a method for estimating channel quality in a wireless network. The method comprises: obtaining information relating to a channel quality for a first time period, as measured by a wireless node located in an environment comprising one or more machines having mechanical parts which are movable in a periodic pattern; and providing the information as an input to a predictive model, developed using a machine-learning algorithm, to obtain a predicted channel quality in the environment for a second, subsequent time period.