Spectral efficiency enhancement of green metric cognitive radio network using novel channel design and intellectual African buffalo optimization

In an advance world, the field of information technology is full of contemporary wireless approaches as because of this the spectral efficiency and spectral sensing technology brings a broad interest in the Cooperative Cognitive Radio Network (CCRN). Besides, the Green metric CCRN spectral sharing is one of the efficient modern approaches compared with other traditional wireless technologies. Nevertheless, the distribution of spectral between the cooperative cognitive customers has dramatic challenges due to the collaboration between the licensed and unlicensed customers. Therefore, the motivation of this research work is to show the better performance of green metric CCRN using novel techniques. Here, a novel Markov Gaussian Wideband Distribution (MGWD) and Dynamic First-Rate Relay Protocol is developed for communication. Moreover, a novel Intellectual African Buffalo Optimization (IABO) is proposed to estimate the finest spectral sensing and false alarm detection. The implementation of this work is done on the MATLAB platform. Sequentially, the performance of green metric CCRN is estimated in terms of the communication ratio, spectral efficiency, outage probability, and throughput. Moreover, the simulation outcomes show that the developed method in CCRN attain higher throughput and diminished power consumption in terms of both Primary User (PU) and Secondary User (SU) successful transmission of probability compared with the other conventional strategies.

Automated summary

In an advanced world, the field of information technology is full of contemporary wireless approaches, leading to a broad interest in Cooperative Cognitive Radio Networks (CCRN) due to spectral efficiency and sensing technologies. The research aims to demonstrate the superior performance of green metric CCRN using novel techniques, showing higher throughput and reduced power consumption compared to traditional strategies.