Improved scheme for spectrum allocation in cognitive wireless sensor networks

In order to effectively allocate the idle spectrum and improve spectrum utilization of cognitive wireless sensor networks, it is necessary to design an efficient spectrum allocation algorithm. Aiming at the problem of spectrum allocation in cognitive wireless sensor networks, an improved method for spectrum allocation is suggested. A new chaotic dynamic clonal evolution algorithm is designed. Then the graph theory coloring model is established with the corresponding fitness function derived. Traditional evolutionary algorithms have the problem of premature convergence, so chaotic operators, adaptive operators and cloning operators are added to the traditional evolutionary algorithms to accelerate the convergence of the algorithm. The chaotic dynamic clonal evolutionary algorithm is compared with the simulated annealing algorithm and the ant colony algorithm by simulation. The simulation results show that compared with the ant colony algorithm and the simulated annealing algorithm, the chaotic dynamic clonal evolution algorithm can effectively improve the global search ability, and significantly improve the network benefit value of spectrum allocation. The results also show that the proposed chaotic dynamic clonal evolution algorithm can make full use of existing spectrum resources and improve the system throughput.