Artificial Intelligence based hierarchical Cognitive Radio Network

Abstract

Faced with ever-increasingly complex communication network architectural difficulties and rising traffic demand across wireless systems, cognitive radio (CR) technology alone is insufficient for dynamic spectrum resource allocation in 5th-generation (5G) networks. A distributed cognitive cellular network is presented in this research work for an efficient real-time procedure, which merges artificial intelligence with CR technology into a sophisticated multi-agent system (MAS). It is a new approach to 5G cellular communication networks. For dynamic time-frequency-space resource allocation to increase the usage of spectrum resources in the cognitive cellular network, balancing resource allocation among primary users, secondary users, and base stations is critical. In this study, a hierarchical MAS model is built and a four-layer distributed networking system is introduced. The study also describes the essential approaches and technologies and evaluates their efficacy by using numerical simulations.