Design of optimal engine for cognitive radio parameters based on the DUGA

Cognitive radio is an intelligent wireless communication system, which can dynamically adjust its parameters depending on environment change and service demands to improve system performance. As the parameter adjustment of CR is a typical multi-objective optimization problem, this paper proposes a scheme of CR-optimized engine based on the Discrete Uniform Genetic Algorithm (DUGA), considering the optimization of joint PHY layer and MAC layer. DUGA can select non-dominated population by calculating individual crowding distance. Some operations, such as discrete uniform distribution, crossover, mutation, and gradual iteration, are applied to achieve population diversity and rapid convergence. The engine is embedded into the CR node to achieve the optimizations. The results show that the performance of the DUGA is better than the typical NNIA through testing in MATLAB, besides, the engine can effectively improve the CR system performance under the NS2 simulation.