Betterment of Resource allocation in OFDM-based Cognitive Radio with Weightage based Dynamic Group Search Optimization

The maximization of transmission rate of the cognitive ratio (CR) system in concerned resource allocation is a challenging point up to date in the field of wireless communication. Hence in this paper, modified Group Search optimization (GSO) is proposed to overcome such limitation. The proposed GSO is performed by varying the maximum pursuit angle of GSO for different sub-channels. Here, the Cognitive Radio system under the orthogonal frequency division multiplexing (OFDM) is simulated using proposed GSO algorithm. Further the experimentation of the proposed method is compared with the existing algorithms like GSO, firefly algorithm (FA), artificial bee colony algorithm (ABC), particle swarm optimization algorithm (PSO) and genetic algorithm (GA). The efficiency of the algorithms is validated based on the whisker analysis, statistical analysis and comparative analysis. Subsequently, the result shows, the proposed GSO provides significant enhancement in transmission rate of CR with optimal resource allocation against the conventional algorithms.