Transceiver with machine learning for generation of communication parameters and cognitive resource allocation

Abstract

Embodiments of the disclosure provide a system for operating a radio frequency (RF) network having a plurality of communication nodes. A network transceiver communicates with communication nodes in the RF network. A computing device coupled to the network transceiver performs actions including: evaluating a state of the RF network using a machine learning model, based on a spectrum environment and a communication objective, generating a set of communication parameters based on the state of the RF network, causing the network transceiver to communicate with the a communication node using the generated set of communication parameters, and modifying the machine learning model based on a result of causing the network transceiver to communicate with the communication node.