Telefonaktiebolaget Lm Ericsson (publ)

Sakib Bin Redhwan

Pradeepa Ramachandra

Henrik Rydén

Reza Moosavi

Xingqin Lin

Nicklas Johansson

Mirsad Cirkic

Joel Berglund

Sofia Ek

Zhenhua Zou

Ali Parichehrehteroujeni

Ursula Challita

Roman Zhohov

A computer implemented method in a communications network for determining location information about an actual location of a drone comprises obtaining a reported location of the drone at a first time point and obtaining a measurement of radio conditions between the drone and a node in the telecommunications network, at the first time point. The method then comprises predicting radio conditions at one or more locations related to the reported location of the drone, and determining the location information about the actual location of the drone based on the measured radio conditions and the predicted radio conditions.

Determining location information about a drone

Methods and apparatus in a communications network as described herein are suitable for determining a first model for use in predicting conditions on carrier frequencies in the communications network. In a method, network measurements are obtained () of conditions on a plurality of carrier frequencies. A first model is then determined () based on the obtained measurements that takes as input the conditions on a first subset of the plurality of carrier frequencies and outputs a prediction of the conditions on a second subset of the plurality of carrier frequencies, based on the conditions of the first subset of carrier frequencies.

Predicting conditions on carrier frequencies in a communications network

A first network node transmits, to a wireless device, a first indication. The first indication indicates to select, out of a plurality of target links simultaneously fulfilling a respective condition to switch from a source link to a target link, a first target link to switch from the source link to the selected first target link. The selecting is based on at least one of: a Reference Signal Received Power (RSRP) value, a Reference Signal Received Quality (RSRQ) value, a Signal to Interference and noise ratio (SINR) value, a priority, Random Access Channel (RACH) resources, a cell in which latest measurements were made, or a frequency, of the respective target links in the plurality of target links. The first network node then handles the link switch from the source link to the target link, based on the transmitted first indication.

First network node, wireless device and methods performed thereby for handling a link switch

Embodiments include methods performed by a network node, in a radio access network, RAN, that is a target node candidate for a mobility operation of a user equipment, UE. Such methods include receiving, from a source node serving the UE, a request to prepare a mobility procedure for the UE in relation to a candidate target cell associated with the network node. The request can include characteristics associated with a data connection of the UE. Such methods include determining that the UE can be admitted for the requested mobility procedure based on the characteristics, and determining to activate bicasting of the data connection. Different bicasting modes can be selected. Such methods also include transmitting, to the source node, a response that includes a bicasting configuration associated with the UE. Other embodiments include complementary methods performed by source nodes, as well as network nodes configured to perform such methods.

Techniques for conditional handover and bi-casting

Embodiments herein relate to methods and apparatus for determining whether each of a plurality of wireless devices are drones or non-drones. The method includes determining based on binary classification of the first information which of the wireless devices meet all of at least one primary criterion; transmitting a request for second information to the wireless devices that meet all of the at least one primary criterion; receiving second information from each of the wireless device that meet all of the at least one primary criterion; determining based on binary classification of the second information which of the wireless devices that meet all of the at least one primary criterion also meet all of at least one secondary criterion; and classifying the wireless devices that meet both all of the at least one primary criterion and all of the at least one secondary criterion into the first category.

Methods and apparatus for categorising wireless devices

Systems and methods for providing unlicensed drone User Equipment (UE) detection in a cellular communications network are disclosed. In this regard, embodiments of a method of operation of a server for providing unlicensed drone UE detection in a cellular communications network are disclosed. In some embodiments, the method includes receiving, from a network node, a measurement report for a UE and predicting that the UE is an unlicensed drone UE based on the measurement report for the UE. The method further includes taking one or more actions upon predicting that the UE is an unlicensed drone UE. In this manner, an efficient unlicensed drone detection mechanism is provided.

Systems and methods for efficient drone detection

It is provided a method for detecting when a user equipment, UE, is airborne. The method is performed in a UE status detector and comprises the steps of: obtaining an indicator of variation of signal strengths for signals received in the UE, wherein the signals are transmitted for at least three different cells; and determining, based on the indicator of variation, when the UE is airborne.

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Linköping, Sweden

Sakib Bin Redhwan