Abstract:At present, there is a rapid growth in communication services in mobile communication systems. To alleviate the power consumption caused by the increasing base station load, renewable energy production equipment has been equipped for mobile communication system base stations. By matching the information flow and energy flow in the communication system, communication services and renewable energy storage in the communication system can be accurately paired. This can further improve the utilization rate of renewable energy within the communication system, which is the key to optimizing the network performance of the communication system and reducing system operating costs in the next step of research. Therefore, this paper constructs a multi-dimensional utility function. This function comprehensively considers three factors: user signal interference noise ratio, renewable energy utilization, and base station load. This paper solves the initial problem of minimizing the operating cost of a multi base station system by transforming it into a problem of maximizing the utility value of a multi-dimensional utility function. The transformed problem is a non-convex problem of mixed integer nonlinear optimization. To solve this problem, this paper proposes the Multidimensional Utility Function Iterative Optimization Algorithm. This algorithm divides the problem into three subproblems: user scheduling, power allocation, and load balancing. Then, this problem can be iteratively solved by using alternating optimization and continuous convex approximation techniques. The simulation results show that compared to the Maximum SINR Association Optimization Algorithm and the "Maximum SINR and Renewable Energy Utilization" Optimization Algorithm, the algorithm in this paper has improved the utilization efficiency of renewable energy by 58.68% and 29.74%, respectively. At the same time, the total cost of applying the algorithm proposed in this paper has been consistently lower than other algorithms during the simulation period. This indicates the advantages of the algorithm proposed in this paper.