Telefonaktiebolaget Lm Ericsson (publ)

Johan Haraldson

Yu Wang

Jaeseong Jeong

Tor Kvernvik

Matthew John Lawrenson

Sandra Bäckström

Mathhew John Lawrenson

A computing device for supporting an Augmented-Reality (AR) software application is provided. The computing device is operative to select a physical location for placing a current virtual object, where the current virtual object appears to be placed when overlaid onto a video sequence capturing a physical scene in the surroundings of a user, based on an expected physical location which the user assumes in response to displaying the physical scene and the overlaid current virtual object to the user, and an attribute which is spatially dependent and which has an impact on a user experience of the AR software application. Taking the spatially-dependent attribute at the expected physical location of the user into consideration in selecting physical locations for placing virtual objects is advantageous in that virtual objects may be deployed at physical locations so as to provide an improved, or at least satisfactory, user experience to the users.

Supporting an augmented-reality software application

A method for enabling forecasting of key performance indicators, KPIs, in a communication network is presented. The method is performed by a network node and comprises collecting (S) time series data of KPIs in the communication network, extracting (S) k-principal components of the collected time series data, determining (S) a principal component score, PCS, from the collected time series data and the extracted k-principal components, and building (S) a PCS forecast model from the determined PCS and period of time-attributes. Network nodes and computer program products thereof are also presented.

Forcasting time series data

A method for analysing performance of a telecommunications network is disclosed. The method comprises assembling values observed for a network performance parameter over a time window and constructing a time series by associating each performance parameter value with a representation of a time at which the value was observed. The method further comprises encoding the time series to generate a compressed representation of the time series, decoding the compressed representation of the time series to reconstruct the time series, calculating a reconstruction error between the time series and the reconstructed time series, and analysing the reconstruction error to determine if the assembled performance parameter values indicate an anomalous behaviour during the time window. Also disclosed are an apparatus and a computer program product configured to conduct methods for analysing performance of a telecommunications network.

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Stockholm, Sweden

Johan Haraldson