Controlling radiating elements

A method, comprising:

• receiving a performance metric for an antenna array comprised of a plurality of radiating elements, the antenna array having a radiating configuration represented by configuration parameters;
• automatically updating the configuration parameters to adapt to real-time network conditions dependent on the received performance metric by estimating new configuration parameters for moving the performance metric towards a target value, wherein the updating of the configuration parameters comprises estimating, using a machine learning model based on stored training data, updated configuration parameters likely to move the performance metric towards the target value, and wherein the machine learning model is trained with data derived from initial connections quality and subsequently updated based on the results caused by the updated configuration parameters, or with initial configuration parameters and subsequently updated based on the results of re-configurations caused by the updated configuration parameters;
• and
• re-configuring the radiating configuration of the antenna array based on the updated configuration parameters such that a physical geometry of the antenna array is changed.

A non-transitory computer readable medium comprising program instructions stored thereon for performing a method, comprising:

• receiving a performance metric for an antenna array comprised of a plurality of radiating elements, the antenna array having a radiating configuration represented by configuration parameters;
• automatically updating the configuration parameters to adapt to real-time network conditions dependent on the received performance metric by estimating new configuration parameters for moving the performance metric towards a target value, wherein the updating of the configuration parameters comprises estimating, using a machine learning model based on stored training data, updated configuration parameters likely to move the performance metric towards the target value, and wherein the machine learning model is trained with data derived from initial connections quality and subsequently updated based on the results caused by the updated configuration parameters, or with initial configuration parameters and subsequently updated based on the results of re-configurations caused by the updated configuration parameters;
• and
• re-configuring the radiating configuration of the antenna array based on the updated configuration parameters such that a physical geometry of the antenna array is changed.