Intelligent control for cellular radio access networks

An edge computing device, configured to:

• obtain, from a radio access network (RAN), network state information of a communication network;
• receive a machine learning policy from a cloud computing device;
• apply the machine learning policy to the network state information to determine control actions for modifying operational settings of the RAN to provide communication service to a user equipment in the communication network via the RAN;
• and
• transmit the control actions to the RAN.

An emulated edge computing device, configured to:

• implement, in an emulated network environment configured to emulate a communication network, a machine learning policy for control of operational characteristics of an emulated radio access network (RAN);
• receive network state information of the emulated network environment;
• apply the machine learning policy to the network state information to determine control actions for modifying operational settings of the emulated RAN;
• and
• transmit the control actions to the emulated RAN;
• receive a reward associated with operation of the emulated RAN according to the control actions, the reward determined according to a machine learning reward function;
• and
• train the machine learning policy according to the reward.