Optimization of Resource Allocation in Cognitive Radio Network Using Machine Learning Algorithm

Abstract

The growing demands of communication network bandwidth for emerging technology raised the issue of spectrum scarcity. The management and allocation of spectrum in wireless communication are major challenges. A cognitive radio network can help alleviate a wireless network’s spectrum shortage. The optimal allocation of resources in cognitive radio networks boosts the wireless communication system’s capability. Machine learning was employed to enable optimal resource allocation in cognitive radio networks in this study. The proposed power allocation strategy for a cognitive radio network. Because of its low processing overhead, the suggested technique is referred to as lightweight resource allocation in the cognitive radio network. The MLP network is coupled with a cognitive radio network channel in the suggested machine learning technique. In a cognitive radio network, the proposed technique increases spectrum use. MATLAB tools are used to evaluate the proposed technique against RLA and CMA resource optimization strategies. The results reveal that the suggested strategy for distributing resources is extremely effective.