Reinforcement learning of beam codebooks for millimeter wave and terahertz MIMO systems

A neural network for training of a beam codebook for multi-antenna wireless communications, the neural network comprising:

• an actor network configured to predict one or more beam patterns for the beam codebook;
• and
• a critic network configured to evaluate the one or more beam patterns predicted by the actor network based on receive power measurements of an environment,
• wherein the training of the beam codebook is achieved without knowledge of positions of wireless users within an environment accessed by a network node associated with the beam codebook.

A network node, comprising:

• communication circuitry coupled to a plurality of antennas and configured to establish communications with a wireless device in an environment;
• and
• a processing system configured to:
• obtain receive power measurements from the plurality of antennas;
• perform a machine learning-based analysis of the environment based on the receive power measurements;
• and
• adapt the communications with the wireless device in accordance with the machine learning-based analysis of the environment,
• wherein training of a beam codebook associated with the network node is achieved without knowledge of positions of wireless users of the wireless device within the environment accessed by the network node.