Performance Optimization of Multi-Base Station Heterogeneous Network Based on New Energy Power Supply

The future mobile communication system will face a challenge of explosive growth of access devices, which leads to a sharp increase of energy consumption at base stations (BSs). How to gain signal to interference and noise ratio (SINR) of more users while assuring system stability becomes a problem that has to be solved urgently. In this article, a multi-BS heterogeneous network system model which is equipped with renewable energy (RE) production devices is constructed and a hybrid optimization algorithm which is composed of a linear programming (LP) algorithm and multiobjective genetic algorithm is proposed. The hybrid algorithm considers RE output and existing inventory of batteries of BSs comprehensively and maximizes the sum of SINR (sum-SINR) of users in the system through user scheduling and beam forming. First, the hybrid algorithm relaxes the binary parameters of user scheduling into a continuous value during user scheduling, thus changing the mixed integer nonlinear programming problem into an LP problem. As a result, user scheduling scheme of maximizing sum-SINR of the system is solved. Subsequently, the algorithm changes the maximum sum-SINR problem of the system into a multiobjective optimization (MOP) problem of maximum SINR of different BSs during beam forming. The fast nondominated sorting genetic algorithm II that carries the elitist strategy gains the Pareto frontier of MOP based on semidefinite programming constraint and finds the beam forming scheme of maximum sum-SINR of the system. According to stimulation results, the proposed hybrid optimization algorithm can increase sum-SINR of system users effectively while assuring the system stability.

Automated summary

This article presents a multi-BS heterogeneous network system model equipped with renewable energy production devices. A hybrid optimization algorithm is proposed to maximize the sum of SINR of users in the system through user scheduling and beam forming. Simulation results show that the proposed algorithm effectively increases system users' sum-SINR while ensuring system stability.