Nokia Solutions and Networks Oy

Alcatel Lucent

Nokia Technologies Oy

Other

Inria

Alcatel Lecent

Veronique Capdevielle

Afef Feki

Fahad Syed Muhammad

Suresh Kalyanasundaram

Nidham Ben Rached

Claudiu Mihailescu

Eitan Altman

Deepak Kumar Nayak

Muhammad Majid Butt

Majed Haddad

Anand Bedekar

Rajeev Agrawal

Jakob Hoydis

Denis Rouffet

Anna Pantelidou

Jean-Michel Pugeat

Richa Gupta

Laurent Roullet

Lorenzo Maggi

Hua Xu

Marie Line Alberi-Morel

Qi Liao

Pavan Koteshwar Srinath

Claire-Sabine Randriamasy

Sabine Randriamasy

Jean-Claude Faye

Alvaro Valcarce Rial

Ilaria Malanchini

Chandrashekhar Thejaswi

Patrick Albert Krief

Philippe Picquet

Udaya Raju Chowta

Bertold Dickhaus

Wael Motamed

Anil Rao

Tinhinane Ouadda

Mohammad Saad Khan

Nicolas Rots

Boris Kouassi

Sreenath Ramanath

Frédéric Ratovelomanana

A method and apparatus () for beam failure management for a user equipment (UE) () are described. A beam failure instance counter (BFI_counter) is determined, that is indicative of a number of consecutive beam failure instances occurred at the UE (), at a time instance. A location of the UE () is determined at the time instance. A beam failure probability factor is determined, based at least on the location of the UE () at the time instance and the BFI_counter. The beam failure probability factor is indicative of a probability of occurrence of a beam failure at the location of the UE (), after a plurality of further time instances. Further, the beam failure probability factor is compared with a beam failure threshold probability (beamFailureThresholdProb). Thereafter, a beam failure is declared if the beam failure probability factor is higher than the beamFailureThresholdProb.

Method and system for beam failure management

A deep transfer reinforcement learning (DTRL) method based on transfer learning within a deep reinforcement learning (DRL) framework is provided to accelerate the GoB optimization decisions when experiencing environment changes in the same source radio network agent or when being applied from a source radio network agent to a target radio network agent. The transferability of the knowledge embedded in a pre-trained neural network model as a Q-approximator is exploited, and a mechanism to transfer parameters from a source agent to a target agent is provided, where the transferability criterion is based on the similarity measure between the source and target domain.

Apparatus, method and computer program for accelerating grid-of-beams optimization with transfer learning

An apparatus, method and computer program is described including: obtaining first channel measurement data for a primary component carrier used for communications between a device and a network node of a mobile communication system; providing the first channel measurement data as an input to an algorithm to obtain a first embedding output; comparing the first embedding output with embedding outputs of a plurality of reference channel measurement data input to said algorithm to identify a closest reference channel measurement data to the first channel measurement data; identifying a set of reference channel information associated with the identified closest reference channel measurement data, wherein the identified set of reference channel information includes a carrier aggregation policy defining one or more secondary communication channels; and setting a carrier aggregation policy for the primary component carrier in accordance with the carrier aggregation policy.

Apparatuses, methods and computer program using channel measurement data for a primary component carrier

Disclosed is a solution for managing a radio map based on radio fingerprinting measurements. A method comprises: acquiring a radio map of an area, the radio map based on radio frequency measurements performed between at least one access node of a wireless network and terminal devices within the area; detecting at least one gap in the radio map and determining geographical coordinates of the at least one gap; causing transmission of a message comprising at least one information element requesting for additional measurements and comprising the geographical coordinates of the at least one gap; in response to the message, receiving at least one radio frequency measurement report related to at least one terminal device and comprising radio frequency measurement data and at least one measurement location where the radio frequency measurement data has been measured; and updating the radio map on the basis of the radio frequency measurement data.

Radio map improvements

Apparatuses, methods and computer programs are described including, receiving user equipment downlink power measurements from one or more base stations of a communication system, wherein the one or more base stations are configured to provide a plurality of user equipment downlink power measurements for user equipment in communication with a respective base station of the one or more base stations; determining inter-beam interference for multiple directive beams of the or each base station based on the user equipment download power measurements; and assigning one or more beams to one or more clusters such that, for all beams within a cluster, inter-beam interference is below a threshold, wherein beams within a cluster share time and/or frequency resources.

Resource scheduling in communication systems using beam-specific power control

An apparatus comprises means for performing, at a CU of a master node: receiving an individual PDU from one or more incoming PDUs, wherein each PDU is to be transmitted to a UE via one amongst respective paths towards at least one DU of the master node and at least one secondary node, the UE being in DC or MC with the master node and the at least one secondary node; collecting a respective data set for each of the paths; receiving, from a ML model inputting each data set, a respective estimated delay of transmission for each of the paths; selecting, from each of the paths, a path based on the estimated delay of transmission; and transmitting the PDU to the UE via the selected path.

Apparatus, method and computer program for routing data in a dual or multi-connectivity configuration

Disclosed is a method for determining open loop power control parameters. A first set of key performance indicators associated with a first set of open loop power control parameters is obtained from one or more first base stations. A statistical model is determined based at least partly on the first set of key performance indicators and the first set of open loop power control parameters. A second set of open loop power control parameters is determined based at least partly on the statistical model.

Determining open loop power control parameters

Disclosed is a method comprising obtaining a plurality of handover parameter values, using a first machine learning model to select a subset of handover parameter values from the plurality of handover parameter values, obtaining historical information of a plurality of terminal devices, determining a first set of optimal handover parameter values for the plurality of terminal devices from the subset of handover parameter values, tagging the first set of optimal handover parameter values with the historical information of the plurality of terminal devices to obtain a labelled dataset, and training a second machine learning model with the labelled dataset, wherein the trained second machine learning model is capable of predicting a second set of optimal handover parameter values for a first terminal device based on historical information of the first terminal device.

Machine learning based handover parameter optimization

A method comprising receiving a first indication, from a terminal device, indicating that the terminal device is capable of supporting carrier aggregation, obtaining information regarding a battery level of the terminal device, estimating battery consumption per one carrier component, and based, at least partly, on the estimated battery consumption and information regarding the battery level, determining a number of additional carrier components to be activated for the terminal device.

Battery aware carrier activation

An apparatus for anomaly detection in a network, using an autoencoder including an encoder and a decoder. The apparatus includes a processor and a memory including computer program code, causing the apparatus to: providing the decoder with network configuration parameters used to obtain calculated network performance indicators, obtaining reconstructed network performance indicators from the decoder based on the network configuration parameters used to obtain the calculated network performance indicators, comparing the reconstructed network performance indicators with the calculated network performance indicators, detecting an anomaly when observing a deviation between the reconstructed network performance indicators and the calculated network performance indicators, providing the encoder with the calculated network performance indicators, obtaining estimated network configuration parameters from the encoder based on the calculated network performance indicators, detecting that the anomaly is related to the network configuration parameters.

Method and apparatus for anomaly detection in a network

Systems, methods, apparatuses, and computer program products for determining a grid-of-beams (GoB) are provided. One method may include collecting network data for training a neural network, train the neural network, using the collected data, to learn a non-discounted cumulative reward Q that evaluates a benefit of including a given beam into a grid-of-beams (GoB), iteratively applying the trained neural network to select at least one optimal beam to include in the grid-of-beams (GoB), and selecting one or more beams from the grid-of-beams (GoB) to transmit to a user equipment or to receive transmission from the user equipment.

Apparatus and method for designing a grid-of-beams using machine learning

An apparatus and method is disclosed in relation to antenna arrays. The method may include transmitting a reference signal to one or more remote user terminals from each of a plurality of sub-arrays of an antenna array, each sub-array including a quantity of radiating elements of the antenna array capable of establishing a backhaul link with a remote communications node. The method may also include receiving measurement signals from the one or more remote user terminals, indicative of one or more characteristics of the received reference signals. The method may also include selecting, based on received measurement signals, a first subset of the sub-arrays for backhaul communications with the remote communications node and a second subset of the sub-arrays, including one or more of the remaining sub-arrays, for access communications with the one or more remote user terminals.

Antenna arrays

In some embodiments, a computing system maintains, in a memory, information on one or more terminal devices, a dictionary of beams and information on a spatial grid. The computing system maps each terminal device to the spatial grid based on up-to-date results of radio measurements and calculates, for each spatial element, a load caused by the one or more terminal devices based on the mapping. The computing system evaluates, for each combination of a beam and a terminal device, a reference signal received power, RSRP, based on results of the radio measurements. The computing system calculates a first map of expected spatial distribution of traffic based on the calculated loads and beam-specific second maps of expected RSRP based on the values of the RSRP. Finally, the computing system causes performing beamforming optimization based on the first map and second maps.

Efficient data generation for beam pattern optimization

A method for estimating the speed of a user equipment connected to a base station of a wireless network, the method comprising the following steps: measuring the power of a signal transmitted between the user equipment and the base station; computing the derivative of the measured signal power with respect to time; computing the standard deviation of the computed derivative; estimating, from previously established reference data, the speed of the user equipment that corresponds to the computed standard deviation, the reference data associating a given user equipment speed with a certain computed standard deviation.

Temporal analysis for user speed estimation in wireless networks

A method for estimating the speed of a user equipment connected to a base station of a wireless network, the method comprising the following steps: &#x2014;performing signal strength measurements (S) of a radio signal transmitted between the user equipment and the base station; &#x2014;performing a spectral analysis () of the signal strength measurements; &#x2014;determining the frequency of a local maximum in the power spectrum of the signal strength measurements; &#x2014;estimating (), from previously established reference data, the speed of the user equipment that corresponds to the determined frequency, the reference data associating a given user equipment speed with a certain determined frequency.

Method and system for user speed estimation in wireless networks

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Magny les Hameaux, France

Veronique Capdevielle