Cognitive radio method based on improved genetic algorithm

Abstract

The invention discloses a cognitive radio method based on an improved genetic algorithm in the technical field of radio communication. The cognitive radio method comprises the steps of: setting initial parameters of cognitive radio and using the initial parameters as chromosomes of the genetic algorithm; setting initial mutation probability, population size and maximum evolutional generations, and setting target functions which reflect current link quality and the weight of each target function; calculating a population fitness value; conducting scale transformation of the fitness value; selecting the chromosomes; using self-adaptive crossover probability and mutation probability to conduct two-point crossover and individual mutation on the chromosomes; judging whether a condition of convergence is reached or not, and if not, returning to calculate the population fitness value; and if so, outputting a result set and using the results as the parameters of the cognitive radio. The cognitive radio method solves the problem that the final solution set is apt to be converged into a locally optimal solution in the genetic algorithm, and guarantees the diversity of populations and the convergence of the genetic algorithm at the same time.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a cognitive radio method based on an improved genetic algorithm. Background technique [0002] The continuous increase in demand for wireless communication services leads to an increasing demand for spectrum resources in wireless communication systems, so that wireless spectrum resources become increasingly scarce. However, research on spectrum measurement shows that the utilization rate of licensed spectrum is very low, the waste of licensed spectrum holes is serious, and the static spectrum allocation system does not match the dynamic spectrum utilization method. The basic idea to solve this problem is to improve the existing spectrum utilization as much as possible. Cognitive radio technology emerges as a technology that can meet this requirement. [0003] The concept of cognitive radio (Cognitive Radio, CR) was proposed by Dr. Joseph Mitolo in 199...

AI Technical Summary

Problems solved by technology

However, the simple genetic algorithm does not control the chromosomes. If individuals with high fitness appear in the population, it is very easy to obtain a local optimal solution.

In addition, the simple genetic algorithm uses fixed crossover probability and mutation probability, does not protect good individuals, suppresses poor individuals, and does not treat them differently according to different situations before and after evolution, which will affect performance

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