Abstract
This paper presents the problem formulation, development, and use of a robust dynamic genetic algorithm (GA) for channel allocation in cognitive radio. This approach offers an efficient way to access available spectrum for both primary and secondary users. The proposed dynamic genetic algorithms based on the new sophisticated crossover and mutation operators ensure the validity of channels and the fast convergence to the best solution in a highly dynamic environment. Compared with existing methods, simulation results demonstrate that our approach algorithm produces satisfactory results with reduced network interference and enhance efficiently the spectrum throughput.
Highlights
With the recent growing increases of wireless devices, radio spectrum scarcity occurs and mandates the establishment of methods for developing technical description to access efficiently the available radio spectrum
Several algorithms have been proposed for channel allocation in cognitive radio, whether they are local or distributed search methods
genetic algorithm (GA) is well suited for multi-objective performance and non-mathematical optimization problems in cognitive radio networks as it can search for multiple sets of solutions over a large search space and can enforce constraints [20]
Summary
With the recent growing increases of wireless devices, radio spectrum scarcity occurs and mandates the establishment of methods for developing technical description to access efficiently the available radio spectrum. Several algorithms have been proposed for channel allocation in cognitive radio, whether they are local or distributed search methods. Fuzzy logic is a far powerful and flexible method, based on learning in transmission rate and prediction It has potential in either specific problem-solving areas or as a part of cognitive radio system, to reduce its complexity. GA is well suited for multi-objective performance and non-mathematical optimization problems in cognitive radio networks as it can search for multiple sets of solutions over a large search space and can enforce constraints [20]. According to the logic diagram of the proposed resolution model, the channel assignment problem in a cognitive radio system is based on opportunist channel exploitation where each channel will be used by the maximum number of nodes. The problem of assigning each node a set of colors (channels) may be solved by coloring the graph in sequence with individual colors:
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