Selection of power control parameters

Abstract

As solution for selection of power control parameters is presented. The solution comprises determining, from a given set of radio access network parameters, a selection of radio access network parameters which have an effect on uplink power control, and training a neural network to determine uplink power control parameters, utilising as an input the selection of radio access network parameter, and utilising the trained neural network, with as an input the selection of radio access network parameters, obtain as an output a set of initial uplink power control parameters.

A listing of the claims is as follows: 
     
         1 . An apparatus, comprising:
 at least one processor; and   at least one memory including computer program code,   the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform:   determine, from a given set of radio access network parameters, a selection of radio access network parameters which have an effect on uplink power control;   train a neural network using supervised learning to determine uplink power control parameters, utilizing as an input the selection of the radio access network parameters; and   utilize the trained neural network, with as an input the selection of the radio access network parameters, and obtain as an output a set of initial uplink power control parameters.   
     
     
         2 . The apparatus of  claim 1 , wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus further to perform:
 utilize as an input in the training of the neural network at least one of the following: one or more radio access network configuration, varying radio access network conditions, network inter site distance, number of users per cell.   
     
     
         3 . The apparatus of  claim 1 , wherein the uplink power control parameters comprise target received power P 0 , and a fractional pathloss compensation factor α. 
     
     
         4 . A network element in a radio access network, comprising:
 at least one processor; and   at least one memory including computer program code,   the at least one memory and the computer program code configured to, with the at least one processor, cause the network element at least to:   receive a set of initial uplink power control parameters provided by a supervised trained neural network; and   utilize the set of initial uplink power control parameters in an operating radio access network and select, from the received set, the parameters giving best performance as the uplink power control parameters to be applied in the radio access network, wherein when utilizing the set of initial uplink power control parameters in the operating radio access network, apply each uplink power control parameter of the set for a predetermined amount of time.   
     
     
         5 . A system comprising an apparatus and at least one network element, the apparatus comprising:
 at least one first processor; and   at least one first memory including first computer program code,   the at least one first memory and the first computer program code configured to, with the at least one first processor, cause the apparatus at least to:   determine, from a given set of radio access network parameters, a selection of radio access network parameters which have an effect on uplink power control;   train a neural network using supervised learning to determine uplink power control parameters, utilizing as an input the selection of radio access network parameter; and   utilize the trained neural network, with as an input the selection of radio access network parameters, to obtain as an output a set of initial uplink power control parameters;   and the network element in a radio access network comprising:   at least one second processor; and   at least one second memory including second computer program code,   the at least one second memory and the second computer program code configured to, with the at least one second processor, cause the network element at least to:   receive a set of initial uplink power control parameters provided by the supervised trained neural network; and   utilize the set of initial uplink power control parameters in an operating radio access network and select from the received set the parameters giving best performance as the uplink power control parameters to be applied in the radio access network wherein when utilizing the set of initial uplink power control parameters in an operating radio access network, apply each uplink power control parameter of the set for a predetermined amount of time.   
     
     
         6 . The system of  claim 5 , wherein the apparatus is configured to transmit the set of initial uplink power control parameters to the at least one network apparatus. 
     
     
         7 . A method in a radio access network, comprising:
 determining, from a given set of radio access network parameters, a selection of radio access network parameters which have an effect on uplink power control;   training a neural network using supervised learning to determine uplink power control parameters, utilizing as an input the selection of radio access network parameters, more than one radio access network configuration, one or more types of radio access network traffic and varying radio access network conditions; and   utilizing the trained neural network, with as an input the selection of radio access network parameters, obtain as an output a set of initial uplink power control parameters.   
     
     
         8 . The method of  claim 7 , further comprising:
 utilizing as an input in the training of the neural network at least one of the following: one or more radio access network configuration, varying radio access network conditions, network inter site distance, number of users per cell.   
     
     
         9 . The method of  claim 7 , wherein the uplink power control parameters comprise target received power P 0 , and a fractional pathloss compensation factor α. 
     
     
         10 . A method for a network element in a radio access network, comprising:
 receiving a set of initial uplink power control parameters provided by a supervised and trained neural network; and   utilizing the set of initial uplink power control parameters in an operating radio access network and select from the received set the parameters giving best performance as the uplink power control parameters to be applied in the radio access network, wherein when utilizing the set of initial uplink power control parameters in an operating radio access network, apply each uplink power control parameter of the set for a predetermined amount of time.   
     
     
         11 . A computer program embodied on a non-transitory computer-readable medium, the computer program comprising instructions for causing an apparatus to perform at least the following:
 determining, from a given set of radio access network parameters, a selection of radio access network parameters which have an effect on uplink power control;   training a neural network using supervised learning to determine uplink power control parameters, utilizing as an input the selection of radio access network parameters, more than one radio access network configuration, one or more types of radio access network traffic and varying radio access network conditions;   utilizing the trained neural network, with as an input the selection of radio access network parameters, obtain as an output a set of initial uplink power control parameters.   
     
     
         12 . A computer program embodied on a non-transitory computer-readable medium, the computer program comprising instructions for causing a network element in a radio access network to perform at least the following:
 receiving a set of initial uplink power control parameters provided by a supervised and trained neural network;   utilizing the set of initial uplink power control parameters in an operating radio access network and select from the received set the parameters giving best performance as the uplink power control parameters to be applied in the radio access network, wherein when utilizing the set of initial uplink power control parameters in an operating radio access network, apply each uplink power control parameter of the set for a predetermined amount of time.