Telefonaktiebolaget Lm Ericsson (publ)

Torbjörn Wigren

Iana Siomina

Ari Kangas

Bo Göransson

Dirk Gerstenberger

Ying Sun

Meng Wang

Zhang Zhang

Jonas B Karlsson

Martin Skarve

Shiguang Guo

Billy Hogan

Muhammad Ali Kazmi

Robert Baldemair

Fredrik Gunnarsson

Walter Müller

Yuan Wang

Oskar Mauritz

Magnus Nilsson

Martin Israelsson

Mikael Wittberg

Xinyu Gu

Badawi Yamine

Stefan Wager

Johan Mikael Bergman

Torsten Dudda

Helka-Liina Määttanen

Reem Karaki

Patrik Torgny Karlsson

Carola Faronius

Anders Jonsson

Torsten John Carlsson

Stefan Parkvall

Daniel Chen Larsson

Henrik Sahlin

George Jöngren

Stephen J Grant

Claes Tidestav

Shuhui Chen

Niklas Johansson

Henrik Rydén

Alexander Vesely

Fredrik Huss

Svante Bergman

Per Hans Willars

Ylva Jading

Richard Middleton

Katrina Lau

Sholeh Yasini

Ramon Delgado

Christer Törnevik

Ramon Alejandro Delgado Pulgar

Anders Lamm

Yali Pei

Klas Johansson

Henrik Egnell

Linda Brus

Michael Anderson

Markus Ringström

Stephen G Craig

Hanzhi Zhang

Graham C Goodwin

Claudia Muñiz Garcia

Björn Thors

Karin Lagergren

Ken Huisman

Waikwok Kwong

Peter Jakobsson

Robert Karlsson

David Sandberg

Magnus Lundevall

Ulf Skärby

Björn Nordström

Johan Bolin

Alexander Langereis

Mats Åhlander

Pär Ankel

Erik Geijer Lundin

Magnus Persson

Anders Hangkan Persson

Gunnar Peters

Johan Thorebäck

Magnus Malmberg

Patrik Persson

Jing Rao

Petter Blomberg

Amr El-Keyi

Georgy Levin

Babak Alamshahi

Thomas Östman

Yang Zhang

Yufeng Zhao

Keke Zu

Daniel Larsson

Edison Shu

Aron Yu

Peiliang Chang

Mihai Parvan

Gunilla Sjöström

Mauricio Cea

A method of determining the position of a moving unmanned aerial vehicle (UAV) is provided. The method comprises obtaining, for each of three or more base stations, one or more measurements of a carrier frequency offset (CFO) for one or more signals sent between a moving UAV and the respective base station. The method further comprises inputting the CFO measurements into a model to determine a position of the UAV, in which inputs to the model do not include range measurements of the UAV with respect to the three or more base stations.

Methods and apparatus for positioning of a moving unmanned aerial vehicle

Embodiments include methods for determining a movement state of a user equipment (UE) operating in a radio access network (RAN). Such methods include performing positioning measurements on signals received from a plurality of transmission points (TPs) in the RAN, including first measurements of Doppler shift of signals from a first TP, second measurements of Doppler shift of signals from a second TP that is spatially separated from the first TP, and third measurements of signals from a third TP. The third TP can be the same as the first or second TP, or spatially separated from both. Such methods include determining a UE movement state based on the positioning measurements and an interacting multiple-model (IMM) that includes a first almost-constant velocity model, a second maneuver velocity model, and a Doppler shift bias state common to the first and second models. Other embodiments include complementary methods for a RAN node.

User equipment (UE) movement state estimation based on measurements for two or more sites in a wireless network

A method of determining a two-dimensional position of a moving wireless device is provided. The method comprises obtaining, for each of three or more base stations, one or more measurements of a carrier frequency offset for one or more signals sent between the moving wireless device and the respective base stations. The method further comprises inputting the carrier frequency offset measurements into a model to determine a two-dimensional position of the moving wireless device, in which inputs to the model do not include range measurements for the moving wireless device with respect to the three or more base stations.

Methods and apparatus for positioning of a moving wireless device

A method for kinematic state estimation of a UE in a wireless communication system. The method includes estimating of a kinematic state having two-dimensional position, two-dimensional velocity and a frequency bias of the UE. The estimation is based on and fully enabled by obtained measurements of Doppler shifts, relative two different antennas of the wireless communication system, of radio signals transmitted from the UE, and obtained distance-establishing measurements associated with the UE. A network node performing the method and a computer program therefore are also presented.

User equipment two-dimensional state estimation

An Advanced Antenna System (AAS) receiver and related methods are provided. According to one aspect an AAS receiver comprises a digital processing block of a Radio Frequency Integrated Circuit (RFIC). The digital processing block comprises an interface for communicating with a Central Unit (CU), and a plurality of Antenna Signal Processing Blocks (ASPBs), each receiving a digitized receive signal from a respective antenna element of an antenna array. Each ASPB comprises one or more receivers, each of which receives the signal from the respective antenna element, processes the received signal, and beamforms the processed signal to produce one or more data streams to be sent to the CU. Each ASPB also includes a narrowband receiver that processes an input signal (either the signal received from the respective antenna element or that signal after processing) to create a narrowband signal that is provided to the CU directly, without beamforming.

Versatile AAS receiver

A method and network node for predictive sectorized average power control. A method includes determining a beamforming gain for each of a plurality of directions. The method also includes determining a total power at each of a plurality of times within a window for each of the plurality of spatial directions, the total power being based at least in part on a weighted sum of products of a beamforming gain and a downlink power allocated to a wireless device in each of the plurality of spatial directions. The method further includes determining an average of the total power within the window to produce an average power; computing a control signal based on the average power and a threshold; and controlling the transmitted total power according to the control signal by limiting a fraction of scheduled physical resource blocks to an upper limit.

Predictive sectorized average power control

A method of monitoring a kinematic state of an unmanned aerial vehicle (UAV) is provided. The method comprises obtaining one or more predicted pathlosses between a UAV and one or more base stations at a first time instance, wherein the predicted pathlosses are determined using an estimate of a kinematic state of the UAV at the first time instance and one or more pathloss models developed using a machine-learning process. The method further comprises obtaining one or more measurements of a pathloss between each of the one or more base stations and the UAV at the first time instance, and re-determining the estimate of the kinematic state of the UAV at the first time instance based on the one or more predicted pathlosses and the one or more measurements of the pathloss.

Methods and apparatus for monitoring a kinematic state of an unmanned aerial vehicle

Embodiments include methods for estimating movement of an aerial user equipment (UE) by a first RAN node serving the aerial UE in a cell of the RAN. Such methods include determining initialization parameters for an interacting multiple-model (IMM) for movement of the aerial UE in the cell. The initialization parameters include a plurality of neighbor cells, in the RAN, in which positioning measurements should be performed for the aerial UE, and/or for at least one movement mode of the IMM, an initial state comprising a plurality of initial position estimates for the aerial UE. Such methods include determining a movement state for the aerial UE at a first time based on the initialization parameters and positioning measurements of the aerial UE that are performed in the cell and in at least a portion of the neighbor cells. Other embodiments include complementary methods for a second RAN node.

Initializing state estimation for aerial user equipment (UES) operating in a wireless network

A method for transmission control in a multi-connectivity communication system comprises obtaining (S) of an indication of decreased data rate through a first transmitting node of a multi-connectivity communication system. At least a subset of packets, originally scheduled for, and buffered in, the first transmitting node is rescheduled (S) to at least one second transmitting node, different from the first transmitting node, of the multi-connectivity communication system, in response to the obtaining of the indication. A network node for transmission control is also disclosed.

Method and arrangement for flow control in a split path communication system

A mechanism for average Equivalent Isotropic Radiated Power (EIRP) control of at least two radio signal paths. A method is performed by a coordinating controller of a site. The site comprises the at least two radio signal paths. The method comprises obtaining, from inner controllers of the radio signal paths, information of long-term time averaged incoming and outgoing traffic per radio signal path. The method comprises determining a time varying reference value of average transmission power per radio signal path based on equalizing terms determined from the information of long-term time averaged incoming and outgoing traffic, antenna gain information per radio signal path, and a condition on total average EIRP for the site. The method comprises performing individual average EIRP control per radio signal path by providing to each respective inner controller, the time varying reference value determined for the radio signal path controlled by that inner controller.

Coordinated control of average EIRP

A method performed by a node in a wireless communication network. The method comprises obtaining measurement data for one or more measurements performed, by a wireless device in the wireless communication network, on at least one first radio signal transmitted by one or more base stations in the wireless communication network. The method further comprises determining whether or not the wireless device is airborne by inputting the measurement data to a model developed using a machine learning algorithm.

Methods and apparatus and machine-readable media relating to airborne wireless devices

A method for kinematic state estimation of a UE connected to a wireless communication network. The method comprises obtaining (S) of measurement information related to a kinematic measurement concerning the UE. The kinematic measurement is achieved at a measuring time. The kinematic measurement belongs to a set of kinematic measurements. It is further determined (S) whether the measurement information is consistent with a measurement prediction for the UE valid for the measuring time based on a kinematic state estimation of the UE. The kinematic state estimation is created using kinematic measurements of the set of kinematic measurements. If the measurement information is determined not to be consistent, the measurement information is discarded (S). If the measurement information is determined to be consistent, the kinematic state estimation of the UE is updated (S) with the measurement information.

Method and apparatus for kinematic state estimation of a user equipment

According to one or more embodiments, a network node is provided. The network node includes processing circuitry configured to: feedback a total momentary carrier power associated with a plurality of co-sited carriers for controlling a respective power of each of the plurality of co-sited carriers. Further, according to one or more embodiments, a method performed by a network node is provided. The method includes feeding back a total momentary carrier power associated with a plurality of co-sited carriers for controlling a respective power of each of the plurality of co-sited carriers.

Dynamic electromagnetic field coordination of multiple carriers

A method for controlling acknowledgement signalling in a multi-point communication system comprises receiving (S), in a wireless device, a data item over a first signalling path out of a plurality of possible signalling paths. Signalling path information associated with the received data item is obtained (S). A transmission of an acknowledgement message for the data item is initiated (S) to be performed over a second signalling path out of the plurality of possible signalling paths selected in dependence of the obtained signalling path information. Alternatively, or in combination, initiating of a transmission of an acknowledgement message comprising attaching of information of the identity of the second signalling path to the acknowledgement message. Methods, performed in a network node, assisting the wireless device are also disclosed. Devices for the methods are also presented.

Management of acknowledgement signalling in a multi-point communication system

A method for state estimation of a UE connected to a wireless communication network, comprising obtaining (S) of measurement information related to a 5 range-related measurement concerning a UE. The measurement information comprises data of the range-related measurement, a time at which the range-related measurement was performed, an identity of the UE and data enabling determination of a measuring position. The range-related measurement consists of data defining a distance between the UE and the measuringposition. A state estimation of the UE is performed (S) based on the measurement information. Methods for propagating the measurement information through the network are also disclosed as well as network nodes performing such method.

User equipment state estimation

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Uppsala, Sweden

Torbjörn Wigren