Telefonaktiebolaget Lm Ericsson (publ)

Peiliang Chang

Torbjörn Wigren

Zhang Fu

Akram Bin Sediq

Yifei Jin

Sholeh Yasini

Mats Zachrison

Juhani Kauppi

A Data Compression Manager (DCM) that can help a data provider (DP) and a data consumer (DC) to establish a data transfer using an advantageous data compression method. In one embodiment, when a DC wants to get some data from a DC, the DP will contact the DCM and the DCM will then choose data compression information based on (i.e., based at least on), for example, current conditions within the network (e.g., a maximum available network bandwidth), information about the data to be compressed (e.g., the type of the data), and/or the DC's data error tolerance. Then the DCM will indicate to the DP the chosen data compression information. The DP will then i) inform the DC of the compression information that is needed by the DC to decompress the data and ii) provide the requested data to the DC in compressed form.

Reducing network traffic

A method performed by a node in a wireless communication network. The method comprises obtaining measurement data for one or more measurements performed, by a wireless device in the wireless communication network, on at least one first radio signal transmitted by one or more base stations in the wireless communication network. The method further comprises determining whether or not the wireless device is airborne by inputting the measurement data to a model developed using a machine learning algorithm.

Methods and apparatus and machine-readable media relating to airborne wireless devices

A network node, computer program, computer program product, and a method performed in a network node includes obtaining an estimated data amount of a user equipment, UE, and a resource utilization rate. A percentile R of the estimated data amount is obtained based on a data amount distribution table. The percentile R is compared to the resource utilization rate. Responsive to the percentile R being higher than the resource utilization rate, a resource is allocated to the UE.

Machine learning assisted user prioritization method for asynchronous resource allocation problems

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Åkersberga, Sweden

Peiliang Chang