The embodiment of the invention discloses an unlicensed
frequency band conflict modeling and backoff optimization method and device based on a graph neural network, and aims to solve the conflict problem when multiple devices share a
frequency spectrum in an unlicensed
frequency band. The method comprises the steps of collecting and preprocessing multi-dimensional information of
wireless equipment, constructing a time-space associated conflict graph, predicting a conflict probability by using a graph
attention network, optimizing a backoff strategy through multi-agent
reinforcement learning, and feeding back and updating a model in real time. The device comprises a
data acquisition unit, a
data processing unit, a graph construction unit, a conflict modeling unit, a strategy optimization unit and a feedback optimization unit. Through integration of the graph neural network and multi-agent
reinforcement learning, precise modeling of conflicts and
adaptive optimization of a backoff strategy are realized, the spectrum
utilization rate and the
system throughput on an unlicensed
frequency band are significantly improved, the probability of conflicts between devices is reduced, and the method is suitable for high-density
wireless communication scenes such as
the Internet of Things and smart home.