Adaptation of Transmission Parameters in Cognitive Radio Using GWO Technique

Abstract

Cognitive radio works on important area of wireless communication system. Cognitive radio has two main functions that are sensing unutilized spectrum and adaptation of transmission parameters in wireless system. For real time scenario, the cognitive radio commonly can sum up with some artificial intelligence related techniques so that an intelligent and adaptive radio system get generated in terms of parameter adaptation and spectrum sensing. The work has done on parameter adaptation function. For parameters adaptation, different optimization techniques has applied and observed their advantages and challenges. This thesis initially, represents the cognitive radio, its functions, its characteristics, environmental and transmission parameters. Then, it introduces nature inspired artificial intelligence techniques and highlights the part of knowledge in cognitive radio. The new proposed technique has applied i.e., GWO for adaptation of transmission parameters. The result for this algorithm has analyzed and compares its result to the existing algorithm such as Genetic algorithm, stimulated annealing, Spider monkey optimization. The literature survey of mentioned optimization techniques has been done with their pros and cons. Then present the simulation results for given algorithms. The literature survey is planned that depends upon various artificial intelligence techniques like GA, PSO, ABC, CSO, CBR, Cuckoo search, SMO and SA.