Method and system for optimizing a mobile communications network

A method, implemented by a data processing system, of adjusting modifiable parameters of network cells of a self-organizing cellular mobile communications network, comprising:

• retrieving a current configuration of network cells currently deployed on field, the current configuration of network cells including, for at least some of the network cells, modifiable parameters;
• starting from the retrieved current configuration of the network cells, exploring different configurations of the network cells, each different configuration of the network cells differing from the retrieved current configuration of the network cells and from other different configurations of the network cells by a change in the value of at least one of the modifiable parameters of at least one network cell;
• evaluating the explored different configurations of the network cells, wherein:
• said exploring different configurations of the network cells comprises iterating the following steps:
• building a search tree in which each node of the search tree corresponds to a respective different configuration of the network cells, said building a search tree comprising:
• selecting a path of nodes of the search tree from a search tree root node to a search tree leaf node, wherein the nodes in the path are selected by means of a node selection policy;
• expanding the search tree by identifying if at least one new tree child node in respect of the search tree leaf node is available and, if available, assigning to each new tree child node a respective child node value, wherein said assigning values to the new tree child nodes comprises:
• predicting, by means of a machine learning model, values of network performance indicators corresponding to the different configurations of network cells that correspond to each of the new tree child nodes, and
• calculating values of a reward function in respect of the predicted values of the network performance indicators;
• selecting, among the new tree child nodes, at least one new tree child node according to a ranking of the calculated values of the new tree child nodes;
• subjecting to simulation by a network simulator the selected at least one new tree child node for obtaining simulated values of the network performance indicators corresponding to the different configuration of network cells that corresponds to the selected at least one new tree child node;
• calculating values of the reward function in respect of the simulated values of the network performance indicators;
• updating a respective node information of the selected at least one new tree child node and of the search tree nodes back along the path from the selected at least one new tree child node to the search tree root node;
• based on the calculated values of the reward function, assessing a goodness of the different configuration of network cells corresponding to the selected at least one new tree child node compared to the configuration of network cells corresponding to the search tree root node, and
• when a suitable goodness is assessed for the al least one new tree child node, terminating said iterating and automatically deploying on field a new configuration of network cells by modifying one or more of the modifiable parameters of network cells.