Patents by Inventor Teemu Mikael Veijalainen
Teemu Mikael Veijalainen has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20240147339Abstract: According to example embodiment, a method may include transmitting, by a master node (MN) to a target-secondary node (T-SN), a request for the target-secondary node (T-SN) to prepare a set of one or more candidate target primary cells of a secondary cell group (candidate target PSCells) for a conditional PSCell change for the user device; and transmitting, by the master node (MN) to a source-secondary node (S-SN) that provides dual connectivity for a user device, information indicating or relating to an arrival probability of a cell change for the user device to the target-secondary node (T-SN).Type: ApplicationFiled: October 24, 2023Publication date: May 2, 2024Inventors: Ahmad AWADA, Amaanat ALI, Halit Murat GÜRSU, Panagiotis SPAPIS, Teemu Mikael VEIJALAINEN, Sina KHATIBI
-
Publication number: 20240137783Abstract: An improved NR-U framework allows a gNB to repeat RLM-RS with the same index over each sub-band of an unlicensed spectrum. For example, a RLM-RS with the same indices are repeated by the gNB over the sub-bands of a wideband channel in an unlicensed spectrum. By monitoring the different sub-bands, a UE may find one or more sub-bands in which the RLM-RS having a particular index is successfully transmitted at a subsequent time.Type: ApplicationFiled: February 23, 2021Publication date: April 25, 2024Inventors: István Zsolt Kovács, Teemu Mikael Veijalainen, Wolfgang Zirwas, Navin Hathiramani
-
Publication number: 20240056836Abstract: Systems, methods, apparatuses, and computer program products for testing user equipment (UE) machine learning-assisted radio resource management (RRM) functionalities are provided. One method may include selecting a radio resource management (RRM) functionality to be tested for a user equipment (UE) having advertised machine learning (ML)-assistance capabilities, initializing a machine learning (ML)-assistance model in the user equipment based on the advertised machine learning (ML)-assistance capabilities, generating one or more input test signals and corresponding reference output test conditions depending on the machine learning (ML)-assistance radio resource management (RRM) functionality under test, and activating UE machine learning (ML)-assistance functionality and provisioning, to the user equipment, a test sequence with the generated input test signals and corresponding reference output conditions.Type: ApplicationFiled: March 2, 2021Publication date: February 15, 2024Inventors: István Zsolt KOVÁCS, Teemu Mikael VEIJALAINEN, Wolfgang ZIRWAS, Navin HATHIRAMANI, Hans Thomas HÖHNE
-
Publication number: 20240057022Abstract: 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.Type: ApplicationFiled: August 9, 2023Publication date: February 15, 2024Inventors: Muhammad Ikram ASHRAF, Teemu Mikael VEIJALAINEN, Mikko SÄILY, Oana-Elena BARBU, Taylan SAHIN, Afef FEKI, Athul PRASAD
-
Publication number: 20240048219Abstract: There is provided an apparatus comprising at least one processor and at least one memory storing instructions. When the instructions are executed by the at least one processor, the apparatus is caused to perform determining a first beam and a second beam for receiving at least one data packet from an access node of a network. The apparatus is further caused to perform receiving, from the access node, a re-transmission of the at least one data packet using the second beam when reception of the at least one data packet from the access node has failed using the first beam.Type: ApplicationFiled: July 20, 2023Publication date: February 8, 2024Inventors: Teemu Mikael VEIJALAINEN, Kalle Petteri KELA, Keeth Saliya Jayasinghe LADDU
-
Patent number: 11870528Abstract: Systems, methods, apparatuses, and computer program products for beam selection using data radio bearer specific machine learning are provided. For example, a method can include providing one or more inputs regarding a plurality of beams to a machine learning model. The method can also include obtaining at least one output value regarding the plurality of beams from the machine learning model. The machine learning model can be a data radio bearer specific machine learning model, a data radio bearer group specific machine learning model, or a model trained to output selectively data radio bearer specific values or data radio bearer group specific values.Type: GrantFiled: April 20, 2022Date of Patent: January 9, 2024Assignee: NOKIA TECHNOLOGIES OYInventors: Kalle Petteri Kela, Teemu Mikael Veijalainen, Hans Thomas Höhne
-
Publication number: 20240007884Abstract: An apparatus of a first communication node is provide that includes: means for synchronising a common reference timing with a second communication node; means for obtaining an indication of a time window that specifies a period of time between first and second time instances; and means for configuring a machine learning-based function at the first communication node, wherein the configuration of the machine learning-based function is common between the first and second communication nodes. The apparatus further includes means for executing the machine learning-based function; and means for obtaining information by measuring a performance metric, for the machine learning-based function, during the time window.Type: ApplicationFiled: June 30, 2023Publication date: January 4, 2024Applicant: NOKIA TECHNOLOGIES OYInventors: István Zsolt KOVÁCS, Teemu Mikael VEIJALAINEN, Kalle Petteri KELA, Jian SONG, Muhammad Majid BUTT
-
Publication number: 20230422126Abstract: A method comprising: storing a received first and machine learning model instance and a received second machine learning model instance in a cache of a terminal, wherein the first machine learning model instance is associated to a first cell and configured to make, if activated, a first prediction for the terminal, and the second machine learning model instance is associated to a second cell different from the first cell and configured to make, if activated, a second prediction for the terminal; checking if a predefined first requirement is fulfilled; activating the first machine learning model instance to make the first prediction if the predefined first requirement is fulfilled; inferring a decision involving the terminal based on the first prediction if the predefined first requirement is fulfilled; inhibiting to infer the decision involving the terminal based on the second prediction if the predefined first requirement is fulfilled.Type: ApplicationFiled: November 30, 2020Publication date: December 28, 2023Inventors: Janne Tapio ALI-TOLPPA, Teemu Mikael VEIJALAINEN, Ahmad AWADA, Muhammad Majid BUTT
-
Publication number: 20230344496Abstract: Systems, methods, apparatuses, and computer program products for beam selection using data radio bearer specific machine learning are provided. For example, a method can include providing one or more inputs regarding a plurality of beams to a machine learning model. The method can also include obtaining at least one output value regarding the plurality of beams from the machine learning model. The machine learning model can be a data radio bearer specific machine learning model, a data radio bearer group specific machine learning model, or a model trained to output selectively data radio bearer specific values or data radio bearer group specific values.Type: ApplicationFiled: April 20, 2022Publication date: October 26, 2023Inventors: Kalle Petteri KELA, Teemu Mikael VEIJALAINEN, Hans Thomas HÖHNE
-
Publication number: 20230345271Abstract: There are provided measures for evaluation and control of predictive machine learning models in mobile networks. Such measures exemplarily comprise receiving information on a predictive model related to a radio resource management function, obtaining behavior information on an intended behavior of said predicted model, obtaining difference determination information on difference determination with respect to a predictive model prediction and said intended behavior, measuring a network condition, determining a prediction result based on said network condition and said information on said predictive model, determining a behavior result based on said network condition and said behavior information, and evaluating validity of said predictive model based on said prediction result, said behavior result, and said difference determination information.Type: ApplicationFiled: September 18, 2020Publication date: October 26, 2023Inventors: Teemu Mikael VEIJALAINEN, Ahmad AWADA, Janne Tapio ALI-TOLPPA
-
Publication number: 20230269606Abstract: A method, apparatus, and a computer-readable storage medium are provided for a machine learning (ML) model based radio resource management. In one example embodiment, the method may include a network node defining a validity area and a measurement group for at least a ML model for one or more user equipments and transmitting the validity area and the measurement group of the at least one ML model to the user equipment.Type: ApplicationFiled: April 21, 2021Publication date: August 24, 2023Inventors: Mikko SÄILY, Teemu Mikael VEIJALAINEN
-
Publication number: 20220360501Abstract: An example method, apparatus, and computer-readable storage medium are provided for exploration procedures for network optimization. In one example implementation, the method may include generating, by a first network element, exploration data, the exploration data being generated by the first network element for evaluating performance at a second network element; transmitting, by the first network element, the exploration data to the second network element; and receiving, by the first network element, exploration data feedback from the second network element, the exploration data feedback received from the second network element based on processing of the exploration data by the second network element.Type: ApplicationFiled: October 23, 2019Publication date: November 10, 2022Inventors: Teemu Mikael Veijalainen, Jani Matti Johannes Moilanen, István Zsolt Kovács, Wolfgang Zirwas, Tero Henttonen
-
Patent number: 11418270Abstract: A technique includes receiving, from one or more sensors, sensor data samples; receiving radio network information data samples associated with a radio network; determining, based on an association of one or more received sensor data samples with one or more of the received radio network information data samples, a first set of one or more associated sensor and radio network information data samples; developing a model that is trained based on at least a portion of the first set the associated sensor and radio network information data samples that are relevant to performance of the radio network; and improving performance of the radio network based on at least the model.Type: GrantFiled: September 28, 2018Date of Patent: August 16, 2022Assignee: Nokia Technologies OyInventors: Teemu Mikael Veijalainen, Lauri Ilari Kuru, Jani Matti Johannes Moilanen, Mikko Johannes Honkala
-
Patent number: 11330450Abstract: A technique may include receiving, from one or more sensors, sensor data samples; receiving radio network information data samples associated with a radio network; determining one or more associated sensor and radio network information data samples based on an association of one or more received sensor data samples with one or more of the received radio network information data samples; selecting at least some of the one or more associated sensor and radio network information data samples that are relevant to performance of the radio network; and forwarding the selected associated sensor and radio network information data samples for subsequent use.Type: GrantFiled: September 28, 2018Date of Patent: May 10, 2022Assignee: Nokia Technologies OyInventors: Teemu Mikael Veijalainen, Lauri Ilari Kuru, Jani Matti Johannes Moilanen, Leo Mikko Johannes Kärkkäinen
-
Publication number: 20220038931Abstract: According to an aspect, there is provided a method comprising: determining, by a terminal device of a wireless communication system, one or more distribution measures, wherein distribution comprises one or more of a signal distribution, an interference distribution, mutual information distribution, block error probability distribution or a signal-to-noise-and-interference ratio distribution; producing, by the terminal device, a measurement report that comprises the one or more distribution measures; and transmitting, by the terminal device, the measurement report to an access node of the wireless communication system.Type: ApplicationFiled: September 28, 2018Publication date: February 3, 2022Inventors: Lauri Ilari KURU, Antti Anton TOSKALA, Jani Matti Johannes MOILANEN, Zexian LI, Teemu Mikael VEIJALAINEN
-
Publication number: 20220021469Abstract: A technique includes receiving, from one or more sensors, sensor data samples; receiving radio network information data samples associated with a radio network; determining, based on an association of one or more received sensor data samples with one or more of the received radio network information data samples, a first set of one or more associated sensor and radio network information data samples; developing a model that is trained based on at least a portion of the first set the associated sensor and radio network information data samples that are relevant to performance of the radio network; and improving performance of the radio network based on at least the model.Type: ApplicationFiled: September 28, 2018Publication date: January 20, 2022Inventors: Teemu Mikael Veijalainen, Lauri Ilari Kuru, Jani Matti Johannes Moilanen, Mikko Johannes Honkala
-
Publication number: 20210314790Abstract: A technique may include receiving, from one or more sensors, sensor data samples; receiving radio network information data samples associated with a radio network; determining one or more associated sensor and radio network information data samples based on an association of one or more received sensor data samples with one or more of the received radio network information data samples; selecting at least some of the one or more associated sensor and radio network information data samples that are relevant to performance of the radio network; and forwarding the selected associated sensor and radio network information data samples for subsequent use.Type: ApplicationFiled: September 28, 2018Publication date: October 7, 2021Inventors: Teemu Mikael Veijalainen, Lauri Ilari Kuru, Jani Matti Johannes Moilanen, Leo Mikko Johannes Kärkkäinen