Energy Efficiency Optimization of Super Dense Heterogeneous Network Based on Improved Genetic Algorithm

In order to solve the problem of low node survival in traditional network energy efficiency optimization method, an energy efficiency optimization method based on improved genetic algorithm is proposed. According to the principle of the improved genetic algorithm, the super-dense heterogeneous network is encoded in the coding space, and the fitness function is determined. By establishing the mathematical model of network energy consumption and using cluster selection algorithm to assign the encoded genetic algorithm operators, the problem of network energy consumption is optimized by using convex optimization. The multi-objective programming function is established, the optimal solution of the optimization problem is obtained by using the prior preference method, and the energy efficiency optimization scheme of the network is obtained. Experimental results show that this method can improve the energy utilization efficiency of the network, and has the advantage of more nodes surviving after optimization