Telefonaktiebolaget Lm Ericsson (publ)

Bin Sun

Rafia Inam

Yifei Jin

Athanasios Karapantelakis

Lackis Eleftheriadis

Yang Zuo

Leonid Mokrushin

Aneta Vulgarakis Feljan

Joerg Niemoeller

Marin Orlic

Daniel Lindström

Adam Bergkvist

Saurabh Singh

Xiaoyu Lan

Marios Daoutis

Erik Sanders

The present disclosure relates to a service terminal, a network device and a method for access security at Operation and Maintenance, O&M, support of the network device. The network device () and the service terminal () are configured to establish a communication using at least one access setting for establishing a communication. The at least one access setting comprising one of the following: an IP address, one or several serial communication parameters, access protocol, authentication method. The method comprises to receive a trigger for changing the at least one access setting for establishing a communication with the service terminal, and to change the at least one access setting for establishing the communication with the service terminal to at least one new access setting.

Methods for access security at operation and maintenance, O and M, support

The invention relates to a method for operating a policy control entity in a cellular network, the method comprising: —determining a quality of service parameter for a data packet session in which one trained model from a plurality of trained models is downloaded to a mobile entity, —determining at least one capacity parameter of the mobile entity, —determining a network transmission parameter of the cellular network, —determining said one trained model from the plurality of different trained models based on a dataset which maps different capacity parameters and transmission capabilities to the plurality of trained models, on the determined capacity parameter, and on the network transmission parameter, —determining routing information indicating where said one trained model is accessible for a transmission to the mobile entity, —transmitting the routing information to a session management entity configured to manage the data packet session in the cellular network.

Optimized model transmission

A wireless device, network node and network management node are disclosed. The wireless device, network node and management node may cooperate to facilitate monitoring of the wireless device and detection of an incident involving a user of the wireless device. The wireless device is operable to connect to a network and comprises processing circuitry configured to cause the wireless device to enter an enhanced monitoring mode, receive, from a network node, configuration information specifying a measuring configuration for measuring signal strength, and measure signal strength in accordance with the received configuration information.

Enhanced monitoring and incident detection in a network

A method of detecting a defect in a connecting member of a radio unit in a radio site includes applying an artificial radio traffic load to a first radio unit and at least a second radio unit, such that the radio traffic load experienced by the first and the second radio unit is at a same level, measuring power supplied to the first radio unit via a first connecting member and power supplied to the second radio unit via a second connecting member at an end of each connecting member terminating at a device configured to supply power to the radio units, and determining from the measured power and an expected nominal power loss of the first and the second connecting member if there is power loss in at least one of the first and the second connecting member indicating a defect.

Remote diagnostics of power cables supplying radio units in a radio site

The present invention enables accelerated feature vector crafting with a high level of trustworthiness. Heretofore, a system () is set up from a data source verification apparatus () for verifying the at least one data source (--) that generates the new specimen data and a feature vector crafting apparatus () for crafting at least one new feature vector from the new specimen data. The feature vector crafting apparatus () receiving data after verification of data sources (--). The feature vector crafting apparatus () automatically generates new feature vectors from new data for forwarding there to an artificial intelligence infrastructure ().

Feature vector generation using neural networks

The present disclosure relates to a method of controlling power supply units (-) of a base station (), and a device () performing the method. In an aspect, a method of a base station scheduling device () of controlling power supply units (-) of a base station () is provided. The method comprises acquiring (S-) information indicating a value of voltage input to at least one of the power supply units (-) of the base station (), determining (S) from said value if the voltage input to said at least one of the power supply units (-) is sufficient, and if not determining (S) power demand of the base station (), and deactivating (S) said at least one power supply unit, if remaining power supply units (-) is capable of supplying the demanded power.

Method for improving base station efficiency and power consumption

A method is proposed for managing a tree-based learner as following. In an initialisation phase: training the tree-based learner with a first set of specimen data to process input data with an active model chain comprising at least a root model to generate an output, each member of the first set of specimen data having a value of each of a first set of features; in an automated reconfiguration phase: receiving a new set of specimen data; performing a comparison between the new set of specimen data and the first set of specimen data; responding to the executed comparison indicating new values of a feature in the new set of specimen data, by reconfiguring the tree-based learner by the addition of a new sub-model to the active model chain, the new sub-model being trained to process at least the new values of the feature.

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Luleå, Sweden

Bin Sun