Telefonaktiebolaget LM Ericsson had 62 patents in digitalization during Q1 2024. The patents filed by Telefonaktiebolaget LM Ericsson in Q1 2024 cover a range of technologies including predicting user behavior in communication networks using artificial neural networks, tracking usage information for differentiated charging in communication networks, timing advance offset for uplink/downlink switching in New Radio (NR), performing handover of media stream capturing between devices, and supporting extended reality applications with dynamic content based on user location and pose information. GlobalData’s report on Telefonaktiebolaget LM Ericsson gives a 360-degree view of the company including its patenting strategy. Buy the report here.

Telefonaktiebolaget LM Ericsson grant share with digitalization as a theme is 37% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Node, and method performed thereby, for predicting a behavior of users of a communications network (Patent ID: US20240104365A1)

The patent filed by Telefonaktiebolaget LM Ericsson describes a method for predicting user behavior in a communications network using an artificial neural network. The method involves merging pre-existing predictive models of user behavior in different user groups, establishing connections between these models, learning connection weights based on data from a third user group, and obtaining a new predictive model for the third group. The process includes training and testing the new predictive model by adjusting weights and utilizing different learning rates in the neural network.

Additionally, the patent outlines the configuration of a node to manage the artificial neural network for predicting user behavior. The node merges pre-existing predictive models, learns connection weights based on user data, and generates a new predictive model for a specific user group. It also includes features such as ranking pre-existing models for merging, selecting models based on criteria and thresholds, and training the new predictive model by adjusting weights and learning rates in the neural network. The method and node described in the patent aim to enhance predictive accuracy and efficiency in forecasting user behavior in a communications network.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.