Energy Efficiency Optimization Algorithm of CR-NOMA System Based on SWIPT

Table 3

Genetic algorithm of optimal partition coefficient.

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Algorithm: genetic algorithm with optimal partition coefficient

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1. Initialize the remaining variables and constant terms , , , .

2. Set the number of individuals in the genetic algorithm population M, maximum evolution algebra G, cross probability , mutation probability , initial algebra  = 1.

3. Randomly generate M individuals who meet the constraints, calculate the fitness of the initial population according to the objective function and select the individual with the highest fitness as the best individual.

4. While  < G+1:

5. Select M/2 to cross the mother chromosomes according to the probability of crossing to generate M new individuals,

6. Make these M new individuals mutate according to the set mutation probability,

7. Let the M chromosomes be a new population and update the most adaptive individual in the population,

8. Let  =  + 1.

9. The best individual found is the segmentation coefficients and that satisfy the maximum energy efficiency

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