UE driven antenna tilt

Patent metadata

Field	Value
Publication number	US-12512586-B2
Application number	US-202118036854-A
Country	US
Kind code	B2
Filing date	Oct 14, 2021
Priority date	Nov 13, 2020
Publication date	Dec 30, 2025
Grant date	Dec 30, 2025

Abstract

The present disclosure relates to a method of a wireless communication device ( 103 ) of facilitating control of antenna tilt for a radio base station ( 101 ), a method of a radio base station ( 101 ) of facilitating control of antenna tilt at the radio base station ( 101 ) and further a wireless communication device ( 103 ) and a radio base station ( 101 ) performing the respective method. In a first aspect a method of a wireless communication device ( 103 ) of facilitating control of antenna tilt for a radio base station ( 101 ) is provided. The method comprises receiving (S 202 ), from the radio base station ( 101 ), information indicating a location of the radio base station ( 101 ), determining (S 203 ) a set of values of a measure of quality of a signal received from the radio base station and a distance of the wireless communication device ( 103 ) from the location of the radio base station ( 101 ) at which each value in the set is determined, supplying (S 204 ) a machine learning model with the determined set of values of said measure of quality and the distance of the wireless communication device ( 103 ) from the location of the radio base station ( 101 ) for each value, thereby creating a trained machine learning model associating a distance of the wireless communication device ( 101 ) from the location of the radio base station ( 103 ) with a value of a measure of quality of a signal received from the radio base station ( 101 ), and transmitting (S 205 ) the trained machine learning model to the radio base station ( 103 ), the trained machine learning model being used by the radio base station ( 101 ) to control antenna tilt.

First claim

The invention claimed is:

1 . A method of a wireless communication device of facilitating control of antenna tilt for a radio base station, comprising:
receiving, from the radio base station, information indicating a location of the radio base station; determining a set of values of a measure of quality of a signal received from the radio base station and a distance of the wireless communication device from the location of the radio base station at which each value in the set is determined; supplying a machine learning model with the determined set of values of said measure of quality and the distance of the wireless communication device from the location of the radio base station for each value, thereby creating a trained machine learning model associating a distance of the wireless communication device from the location of the radio base station with a value of a measure of quality of a signal received from the radio base station; and transmitting the trained machine learning model to the radio base station, the trained machine learning model being used by the radio base station to control antenna tilt.

2 . The method of claim 1 , the received information further comprising one or more of information indicating type of machine learning model being utilized, information indicating feature space of the machine learning model being utilized, information indicating amount of resources to be allocated by the wireless communication device when training the machine learning model.

3 . A non-transitory computer readable medium storing a computer program comprising a set of computer-executable instructions for causing a wireless communication device to perform the method of claim 1 when the computer-executable instructions are executed on a processing unit included in the wireless communication device.

4 . A method of a radio base station of facilitating control of antenna tilt at the radio base station, comprising:
transmitting, to a selected group of wireless communication devices served by the radio base station, information indicating a location of the radio base station; receiving, from each of at least a subset of the wireless communication devices in the group, a trained machine learning model associating a distance of said each wireless communication device from the location of the radio base station with a value of a measure of quality of a signal received from the radio base station at said each wireless communication device; and aggregating the received trained machine learning models into a single trained machine learning model, which single trained machine learning model is used to control antenna tilt at the radio base station.

5 . The method of claim 4 , further comprising:
computing, utilizing the single trained machine learning model, an expected value of the measure of quality of a signal received from the radio base station by a wireless communication device at a particular distance from the radio base station; determining whether or not the computed expected value exceeds a minimum threshold value for said measure of quality; and if not changing tilt of the antenna of the radio base station.

6 . The method of claim 5 , further comprising:
receiving a response from one or more wireless communication devices indicating whether or not a value of the measure of quality of the signal received from the radio base station upon changing the tilt of the antenna exceeds the minimum threshold value for said measure of quality; and if not changing tilt of the antenna of the radio base station until a response is received indicating that the value of the measure of quality of the signal exceeds the minimum threshold value.

7 . The method of claim 4 , further comprising:
selecting the group of wireless communication devices served by the radio base station to which information indicating a location of the radio base station is to be transmitted, the group being selected to comprise any one or more of: a selected number of wireless communication devices being in Radio Resource Control, RRC, connected state for a longest total time with the radio base station, wireless communication devices being located within a maximum allowable distance from each other, wireless communication devices having a particular Service Level Agreement, SLA, status, wireless communication devices being located closer to the radio base station as compared to another set of wireless communication devices, or wireless communication devices accessing a particular service.

8 . The method of claim 4 , further comprising:
effecting handover of a group of wireless communication devices not located within coverage of the antenna to another antenna of the radio base station or to a neighbouring radio base station.

9 . The method of claim 4 , further comprising:
acquiring a trained reinforcement learning model created during simulation, the reinforcement learning model created during simulation being trained to produce as output a value of the measure of quality of a signal received by a wireless communication device located on a particular distance from the radio base station.

10 . A non-transitory computer readable medium storing a computer program comprising a set of computer-executable instructions for causing a radio base station to perform the method of claim 4 when the computer-executable instructions are executed on a processing unit included in the radio base station.

11 . A wireless communication device configured to facilitate control of antenna tilt for a radio base station, the wireless communication device comprising a processing unit and a memory, said memory containing instructions executable by said processing unit, whereby the wireless communication device is operative to:
receive, from the radio base station, information indicating a location of the radio base station; determine a set of values of a measure of quality of a signal received from the radio base station and a distance of the wireless communication device from the location of the radio base station at which each value in the set is determined; supply a machine learning model with the determined set of values of said measure of quality and the distance of the wireless communication device from the location of the radio base station for each value, thereby creating a trained machine learning model associating a distance of the wireless communication device from the location of the radio base station with a value of a measure of quality of a signal received from the radio base station; and to transmit the trained machine learning model to the radio base station, the trained machine learning model being used by the radio base station to control antenna tilt.

12 . The wireless communication device of claim 11 , the received information being configured to further comprise one or more of information indicating type of machine learning model being utilized, information indicating feature space of the machine learning model being utilized, information indicating amount of resources to be allocated by the wireless communication device when training the machine learning model.

13 . The wireless communication device of claim 12 , wherein the feature space further is configured to include model type for the wireless communication device.

14 . The wireless communication device of claim 11 , the measure of quality being one of signal-to-interference-plus-noise ratio, SINR, signal-to-noise ratio, SNR, Quality of Service, QoS, Channel Quality Indicator, CQI, Reference Signal Received Quality, RSRQ, and Reference Signal Received Power, RSRP.

15

Assignees

• Ericsson Telefon Ab L M

Inventors

• Nikou Alexandros
• Vandikas Konstantinos
• Mohalik Swarup Kumar
• Dey Kaushik
• Eleftheriadis Lackis

Classifications

• H04W16/28

  using beam steering · CPC title

• H01Q3/04 Primary

  for varying one co-ordinate of the orientation · CPC title

• H04W24/02 Primary

  Arrangements for optimising operational condition · CPC title