Mathematical Problems in Engineering / 2019 / Article / Tab 1

Research Article

Performance Analysis and Optimization of CRNs Based on Fixed Feedback Probability Mechanism with Two Classes of Secondary Users

Table 1

PSO algorithm to find the optimal value of feedback probability.

Algorithm: find the optimal value of feedback probability

Step 1Initialize the number of particles t, acceleration factors and , maximum value of the speed, maximum value of the inertia weight and the minimum value , maximum iteration number , upper limit and the lower limit of the feedback probability

Step 2Set a random initial feedback probability and initial velocity for each particle, and make the value satisfy , ; set the initial iteration number to 0

Step 3Formula (25) is used to calculate the cost function value corresponding to the feedback probability of each particle

Step 4Search for the current individual optimal value (the minimum value of the cost function) of the particle and the corresponding individual optimal probability

Step 5Find the minimum value of the cost function in the whole particle swarm, that is, the global optimal value, and assign the feedback probability corresponding to the global optimal value to , i.e.,

Step 6Calculate the weight according to the formula

Step 7Update the speed and feedback probability of each particle. Take the particle as example: , , where and are an random variables uniformly distributed from 0 to 1, and is kept in the range

Step 8The number of iterations is increased by one, i.e., ; if , return to the third step; otherwise, output the optimal feedback probability

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