Telefonaktiebolaget Lm Ericsson (publ)

Alexandros Palaios

Torsten Dudda

Reem Karaki

János Farkas

Henrik Rydén

György Miklós

Balázs Varga

Ali El Essaili

Mai-Anh Phan

Robert Baldemair

Paul Schliwa-Bertling

Yi-Pin Eric Wang

John Walter Diachina

Sorour Falahati

Pradeepa Ramachandra

Miguel Lopez

Kumar Balachandran

Joachim Sachs

Osman Nuri Can Yilmaz

Jonas Fröberg Olsson

Jose Luis Pradas

Niklas Andgart

Mattias Andersson

Sándor Rácz

Ying Sun

Dinand Roeland

Henrik Enbuske

Patrik Salmela

Stefano Ruffini

Nianshan Shi

Bernard Smeets

Reza Moosavi

José Araújo

Zhenhua Zou

Anna Larmo

Sara Sandberg

Guido Roland Hiertz

Magnus Sandgren

Kittipong Kittichokechai

Geza Szabo

Harald Gustafsson

Maksym Girnyk

Joel Berglund

Alexey Shapin

Per Persson

Dhruvin Patel

Abdulrahman Alabbasi

Hubertus Andreas Munz

Vijaya Yajnanarayana

Norbert Reider

András Kern

Joakim Persson

Gabor Nemeth

Zsolt Kenesi

Ola Angelsmark

Kun Wang

László Hévizi

Johan Lundsjö

Bikramjit Singh

Majid Gerami

Mårten Wahlström

Ursula Challita

Fredrik Svensson

Johannes Nygren

Anders Höglund

Ricardo Da Silva Souza

Muhammad Ikram Ashraf

Nikolas Hermanns

Torgny Holmberg

Per Skarin

Henrik RydÉn

Malgorzata Svensson

Fedor Chernogorov

Johan Olsson

Wolfgang Tonutti

Rodrigo Berg

Mazen Abdel Latif

Sarah Beschorner

Magued Sedra

Sujata Roy Chowdhury

Methods and nodes in a communications network for using a machine learning model that has been trained using training data from a first radio environment, in a second radio environment, wherein the machine learning model takes a first set of features as input and outputs a label based on a first labelling scheme, the first labelling scheme having been determined for the first radio environment. A method comprises obtaining () a dataset in the second radio environment comprising a plurality of data points comprising values of the first set of features, labelling () each data point in the dataset using the first labelling scheme, and determining () from the labelled dataset whether the first labelling scheme is suitable for use in the second radio environment. Responsive to determining that the first labelling scheme is unsuitable for use in the second radio environment, the method further comprises determining () a second labelling scheme for the machine learning model, using an unsupervised labelling method.

Dynamic labeling for machine learning models for use in dynamic radio environments of a communications network

Techniques for enhancing performance in Industrial Internet-of-Things (IIoT) scenarios, including techniques for time-sensitive networking (TSN) and 5G wireless network integration. An example method, performed by a wireless device, comprises receiving system information (SI) from a radio base station (RBS) of a radio access network (RAN), the SI being indicative of support for TSN through the RBS, and establishing at least one TSN stream with an external data network, through the RBS. The example method further includes receiving a first timing signal from the wireless communications network, via the RBS, receiving a second timing signal from the external TSN data network to which the wireless device is connected, comparing the first timing signal to the second timing signal to determine an offset, and transmitting the offset to the wireless communications network.

Industrial automation with 5G and beyond

A technique of training a model for determining a test case for software testing is presented, wherein the software testing is based on a set of test cases built for a set of software modules comprised by a software to be tested. The technique uses artificial intelligence and comprises obtaining log information resulting from execution of each of the test cases, wherein the log information is obtained per software module and per executed test case, and performing supervised machine learning based on the log information obtained per software module and per executed test case as input to train a model for predicting the executed test case.

Machine-learning based software testing technique

A method performed by a network node for a wireless telecommunications network performs operations including providing a resource allocation model that corresponds to a base station and that provides a recommendation regarding resource allocation for a user equipment, UE, that is in an operating zone of the base station during a limited resource condition of the base station. Operations may include identifying, based on the resource allocation model, a reduced priority zone in the operating zone of the base station that corresponds to the UE having a high risk of reduced service from the base station relative to other UEs in the operating range of the base station.

Methods for intelligent resource allocation based on throttling of user equipment traffic and related apparatus

A technique for determining segmentation parameters for use in segmenting Radio Link Control, RLC, Protocol Data Units, PDUs, in an RLC preprocessing procedure performed by a User Equipment, UE, prior to receiving an Uplink, UL, grant for transmission of the RLC PDUs is disclosed, wherein the segmentation parameters comprise a size of RLC PDU segments and a number of RLC PDU segments to be included into a physical layer Transport Block, TB. A method implementation of the technique comprises determining (S) a TBS prediction of an expected physical layer Transport Block Size, TBS, determining (S) an observation prediction of at least one of an expected channel quality, an expected traffic volume and an expected available bandwidth observable during transmission of the RLC PDUs, and determining (S) the size of RLC PDU segments and the number of RLC PDU segments based on the TBS prediction and the observation prediction, wherein the size of RLC PDU segments and the number of RLC PDU segments are determined to maximize the size of RLC PDU segments while keeping a total size of the number of RLC PDU segments within the expected TBS.

Technique for determining segmentation parameters for use in segmenting RLC PDUs

Methods and apparatus are provided. In an example aspect, a method in a network node is provided, the method comprising monitoring unlicensed spectrum access attempts for transmissions to and/or from at least one User Equipment, UE, in a first group of UEs configured to use unlicensed spectrum to send uplink transmissions and/or receive downlink transmissions and, in response to the monitoring, causing the UEs in the first group to use licensed spectrum to send uplink transmissions and/or receive downlink transmissions.

Using unlicensed and licensed spectrum

A computer-implemented method for acquiring new data samples and for maintaining a set of data samples in a database, wherein the set of data samples are configured to form input to a function associated with a predictive performance, the method including obtaining at least one relevance metric (M), where the relevance metric is indicative of an increase in the predictive performance of the function when using a data sample as input together with the set of data samples compared to when not using the data sample, obtaining a relevance criterion (C), where the relevance criterion identifies relevant data samples in a set of data samples based on the at least one relevance metric, signaling the at least one relevance metric (M) and the relevance criterion (C) to a data collecting network node.

Methods for processing data samples in communication networks

A method is disclosed of transmitting a communication. The method comprises performing a Clear Channel Assessment, CCA, procedure on a first channel in unlicensed spectrum, and, if the CCA procedure indicates that the first channel is occupied for at least a predetermined period, transmitting the communication on a second channel in licensed spectrum.

Transmitting a communication on a first channel or a second channel

Methods and apparatus are provided. In an example aspect, a method of transmitting data is provided. The method comprises determining if a first channel on a first cell is occupied and, if the first channel on the first cell is occupied for at least a predetermined period, transmitting the data on a second channel on a second cell.

Transmitting data when a first channel on a first cell is occupied

The invention relates to a method for grouping a plurality of user entities connected to a cellular network into different clusters, the method comprising: —collecting, for each of the plurality of user entities, activity information comprising different activity parameters, each activity parameter describing an activity of the corresponding user entities in the cellular network, —generating, for each of the plurality of user entities, a user profile comprising the activity parameters for the corresponding user entity, —grouping the plurality of user entities into the different clusters based on a similarity of the activity parameters of the user profiles.

Clustering of user entities in a cellular network

A method of and a network function arranged for enabling data exchange between a first communication network having first data communication capabilities, such as a 5G network, and a second communication network, such as a TSN, having second data communication capabilities different from the first data communication capabilities. Communication attributes of corresponding first and second data communication capabilities are mapped (). Communication capabilities available in the first communication network are allocated () for use by the second communication network, and the allocated data communication capabilities are advertised () to the second communication network, represented in accordance with the attributes mapping ().

Enabling data exchange between first and second communication networks having different data communication capabilities

Methods performed by network nodes in a radio access network may be provided. A first network node may receive an identification of data models supported by a second network node. Each of the identified data models may include a data model for calculating a compact representation of data collected, at least one correlation parameter, and an accuracy metric. The first network node may transmit a request that the second network node calculate an identified one of the data models. The first network node may receive the calculated data model from the second network node. The first network node may evaluate the received calculated data model based on determining whether the received calculated data model correlates to at least one correlation parameter.

Methods for data model sharing for a radio access network and related infrastructure

Communication of Measurement Results in Coordinated Multipoint Methods () performed by a wireless device (), Radio Access node() and training agent () are disclosed. The wireless device is operable to receive signals over a communication channel from a Transmission Point (TP) of a communication network, which TP is a member of a Coordinated Multipoint (CoMP) set and may be managed by the Radio Access node. The method () performed by the wireless device comprises performing a measurement on communication channels toeach of a plurality of TPs in the CoMP set (), and using an autoencoder to compress a vector of measurement results of the performed measurements (). The method further comprises transmitting the compressed vector of measurement results to TPs in the CoMP set () and receiving a joint transmission from TPs in the CoMP set (). The autoencoder comprises an autoencoder that has been trained by a training agentfor use by wireless devices in a coverage area of the CoMP set.

Communication of measurement results in coordinated multipoint

Embodiments of the disclosure provide methods, apparatus and machine-readable media relating to transport of data flows over cellular network. One method in a core network node comprises: obtaining configuration information for a data stream in an external data network, the configuration information indicating respective values for one or more fields within a header of data packets associated with the data stream which are to remain static; initiating transmission of the configuration information to a wireless device which is to receive the data stream; receiving a data packet associated with the data stream from the external data network; removing the one or more fields from the data packet to generate a compressed data packet; and initiating transmission of the compressed data packet to the wireless device.

Transport of data flows over cellular networks

A method performed by a core network node for a wireless communication network is provided. The method comprises: receiving a configuration message via an interface with a configuring node associated with a wired communication network, the configuration message comprising settings for a plurality of paths between a first node coupled to the wired communication network and a second node coupled to the wireless communication network, the plurality of paths carrying a plurality of data streams between the first and second nodes, the plurality of data streams comprising at least one redundant data stream; and configuring the plurality of paths within the wireless communication network according to the settings.

Methods, apparatus and computer-readable mediums relating to configuration of redundant paths

Growing community of inventors

Moers, Germany

Alexandros Palaios