Telefonaktiebolaget Lm Ericsson (publ)

Valentin Kulyk

Konstantinos Vandikas

Christofer Flinta

Lackis Eleftheriadis

Abhishek Sarkar

Mats Folkesson

Martin Pettersson

Bo Burman

Selim Ickin

Farnaz Moradi

Junaid Shaikh

Jawwad Ahmed

Amos Kao

Xiaoyu Lan

A method by a first wireless device, for determining a status of a first cell is described herein. The first wireless device operates in a communications network. The first wireless device sends a request to a plurality of second wireless devices operating in the communications network. The plurality of second wireless devices is within radio range. The request inquires whether or not the first cell is in sleeping state. The first wireless device receives, in response to the sent request, one or more responses from the plurality of second wireless devices. The first wireless device determines whether or not the first cell is in sleeping state, based on the received responses. The methods by a network node and another wireless device receiving an indication indicating a result of the determination are also described.

First wireless device, first network node, second wireless device, and methods performed thereby, for determining a status of a cell

Methods and devices optimize backup power management for network devices connected to backup power sources including two different batteries. Machine learning techniques are used to predict upcoming power outages affecting the network device based on power-related historic information and current conditions. A backup-power operation plan prescribing usage of the backup power sources during the predicted power outages is then generated. The backup-power operation plan schedules a battery among the backup power devices to be used at least twice without being recharged.

Method and devices for optimizing backup power control using machine learning

Systems and methods are provided for generating a predicted number of viewers in support of selecting an advertisement to be displayed during an advertisement break. The method includes: generating, by an advertisement break class identifier module, a plurality of advertisement break classes based on historical advertisement break information and prediction errors generated by a regression model analysis of advertisement break data samples; evaluating, by the advertisement break class identifier module, the plurality of advertisement break classes; redefining and rearranging, by the advertisement break class identifier module, advertisement break classes from the plurality of advertisement break classes based on the step of evaluating which results in an updated set of advertisement break classes; forwarding, by the advertisement break class identifier module, the updated set of advertisement break classes and trained model information to a prediction module; receiving, modifying and returning prediction model information to the prediction module by a training function in the advertisement break class identifier module; generating, by the prediction module, the prediction of a number of viewers for the advertisement break, wherein a regression model uses the updated set of advertisement break classes and data associated with a specific advertisement break to generate the prediction; and sending, by the prediction module, the prediction of a number of viewers for the advertisement break to a scheduler of advertisements.

Dynamic viewer prediction system for advertisement scheduling

A communication device and method provide selective control of a level of buffering of at least one data stream. The communication device includes a jitter buffer (), a jitter buffer control unit () and a user interface (). An instruction received via an input to a user interface () indicates a jitter buffer strategy (), such as enabling a jitter buffer or setting a size of a jitter buffer, based on the user input. The control unit () sets the buffer strategy based in the instruction, and a data stream transmitted via a packet-switched network is received () and buffered for play out based on the buffer strategy ().

Method for manually optimizing jitter, delay and synch levels in audio-video transmission

An apparatus () and method () provides an adaptive end-to-end (E2E) delay threshold (DT) for one-way transmission of information blocks in an information stream of a conversation. Information streams of the conversation are monitored (), and the E2E DT duration is determined based on detected occurrences of one or more interactive propertiesassociated with the information streams of the conversation (). Using the adaptive E2E DT duration value, a determination is made as to whether to perform at least one Quality of Service (QoS) function ().

Conversational interactivity measurement and estimation for real-time media

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Täby, Sweden

Valentin Kulyk