Methods and devices for power configurations in radio communication devices

A device comprising:

• a memory configured to store communication activity data comprising information indicating a plurality of attributes with respect to communication activities over radio connections between one or more user equipments (UEs) and a base station (BS), wherein the communication activity data pertaining to each UE comprise network data indicating one or more network related attributes, device data indicating one or more device related attributes, and application data indicating one or more application related attributes including Quality of Service (QoS) requirements for one or more running applications;
• a processor configured to:
• provide the communication activity data pertaining to the respective UE of the one or more UEs to a trained machine learning model configured to predict a future period of communication inactivity for one of the radio connections between the respective UE of the one or more UEs and the BS based on the plurality of attributes including the QoS requirements pertaining to the UE;
• and
• in response to the future period of communication inactivity meeting a criterion related to duration of the future period of communication inactivity and an impact on the QoS requirements of the one or more running applications, configure one or more network parameters for the radio connection between the respective UE of the one or more UEs and the BS.

A device comprising:

• a memory configured to store one or more measurement results indicating measurements of downlink communication signals received from a base station (BS);
• a processor configured to:
• provide the one or more measurement results to a first trained machine learning module configured to determine a first transmission power parameter for an open-loop power control configuration based on the one or more measurement results;
• provide the one or more measurement results to a second trained machine learning module configured to determine a second transmission power parameter for a closed-loop power control configuration based on the one or more measurement results;
• selectively use one of the first or second trained machine learning module based on a current power control configuration of the device to obtain a determined transmission power parameter being the first transmission power parameter or the second transmission power parameter;
• and
• set a transmit power to transmit uplink communication signals from a user equipment (UE) to the BS based on the determined transmission power parameter.

A device comprising:

• a memory configured to store one or more measurement results indicating measurements of uplink communication signals received from a user equipment (UE) by a base station (BS);
• a processor configured to:
• provide the one or more measurement results to a first trained machine learning module configured to determine a first transmission power parameter for an open-loop power control configuration for the UE based on the one or more measurement results;
• provide the one or more measurement results to a second trained machine learning module configured to determine a second transmission power parameter for a closed-loop power control configuration for the UE based on the one or more measurement results;
• selectively use one of the first or second trained machine learning modules based on a current power control configuration of the device to obtain a determined transmission power parameter being the first transmission power parameter or the second transmission power parameter;
• and
• encode information indicating a transmit power level for the UE based on the determined transmission power parameter.