Telefonaktiebolaget Lm Ericsson (Publ)

Nokia Technologies Oy

Muhammad Ikram Ashraf

John Walter Diachina

Fedor Chernogorov

Robert Baldemair

Paul Schliwa-Bertling

Yi-Pin Eric Wang

Sorour Falahati

Pradeepa Ramachandra

Johan Torsner

Miguel Lopez

Kumar Balachandran

Joachim Sachs

Torsten Dudda

Osman Nuri Can Yilmaz

Jonas Fröberg Olsson

Jose Luis Pradas

Niklas Andgart

Gustav Wikström

Mattias Andersson

Sándor Rácz

János Farkas

Ying Sun

Dinand Roeland

György Miklós

Henrik Enbuske

Patrik Salmela

Stefano Ruffini

Nianshan Shi

Bernard Smeets

Jonas Kronander

Zhenhua Zou

José Araújo

Sara Sandberg

Anna Larmo

Oana-Elena Barbu

Ryan Keating

Balázs Varga

Magnus Sandgren

Kittipong Kittichokechai

Tao Tao

Geza Szabo

Harald Gustafsson

Antonino Orsino

Diomidis Michalopoulos

Alexey Shapin

Per Persson

Norbert Reider

Abdulrahman Alabbasi

András Kern

Joakim Persson

Alexandros Palaios

Gabor Nemeth

Ola Angelsmark

Zsolt Kenesi

Majid Gerami

Kun Wang

Bikramjit Singh

Johan Lundsjö

Dhruvin Patel

Hubertus Andreas Munz

Taylan Sahin

Athul Prasad

Mårten Wahlström

Fredrik Svensson

Hyun-Su Cha

Johannes Nygren

Anders Höglund

Torgny Holmberg

Per Skarin

Mikko SÄILY

Malgorzata Svensson

Rodrigo Berg

Wolfgang Tonutti

Shi Ming Zhang

Li Yu Cai

A method may include receiving, by a first user device from a network node or a second user device, 1) a positioning measurement report including at least one positioning measurement measured by a reference device, and 2) reference positioning-related information to be used for testing and/or validating a machine learning model; determining estimated positioning-related information as outputs of the machine learning model based on at least a portion of the positioning measurement report as inputs to the machine learning model; determining a performance indication of the machine learning model based on the reference positioning-related information and the estimated positioning-related information, wherein the performance indication indicates a performance or accuracy of the machine learning model; and performing, by the first user device, an action based on the performance indication.

Machine learning model validation for UE positioning based on reference device information for wireless networks

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

Embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media for implicit indication of positioning related information. A first device selects a reference signal (RS) sequence from a plurality of available RS sequences. Based on the selected RS sequence, the first device generates a RS for positioning and then transmits the generated RS to a second device to indicate, with the selection of the reference signal sequence, at least part of side information related to the positioning.

Indication of positioning related information

Embodiments described herein provide methods and apparatus for transmitting at least one data stream comprising a plurality of samples between a first wireless device and a second wireless device using machine-to-machine communication. A method in the first wireless device comprises receiving the at least one data stream; generating a first data packet comprising N of the plurality of samples, wherein N is an integer value of greater than or equal to 2; and transmitting the first data packet to the second wireless device.

Method for bundling sampling data for wireless transmission

A method performed by a network node () in a wireless communications network () for enabling a timing reference in a second wireless device () for use in Sidelink, SL, transmissions over a SL communication link () with a first wireless device () is provided. The network node estimates () a propagation delay of SL transmissions over the SL communication link () between the first and second wireless device (). Then, the network node () transmits, to the second wireless device (), timing reference information based on a timing reference originating from a time reference node in a wireless communications network (), and on the estimated propagation delay of SL transmissions over the SL communication link () between the first and second wireless device (). A network node () for enabling a timing reference in a second wireless device () for use in SL transmissions over a SL communication link () with a first wireless device () is also provided. A first wireless (), a second wireless device () and methods therein are also provided, as well as, computer programs and carriers.

Network node, a first wireless device, a second wireless device and methods therein for enabling a timing reference

Growing community of inventors

Espoo, Finland

Muhammad Ikram Ashraf